Tag Archives: transportation

How to Keep the Automotive Chip Shortage From Happening Again

Post Syndicated from Samuel K. Moore original https://spectrum.ieee.org/tech-talk/transportation/advanced-cars/how-to-keep-the-automotive-chip-shortage-from-happening-again

“The automotive supply chain is a very complicated animal,” said Bob O’Donnell president of TECHnalysis Research at an automotive technology panel held Monday at GlobalFoundries Fab 8 in Malta, N.Y. “And very few people understand it.”

O’Donnell made this observation as part of a discussion involving executives from the auto and chip industries. The panelists portrayed a supply chain whose shortcomings have recently brought car makers to their knees. The panelists—who consisted of executives from chip manufacturer GlobalFoundries, IC maker Analog Devices, system integrator Aptiv, and automaker Ford—all agreed that this must never happen again. 

Meanwhile, the semiconductor content in cars is growing at an unprecedented rate—and those semiconductors are being integrated into new architectures driven by the change to electric vehicles.

“We have to revisit risk management across the board,” said Jonathan Jennings, vice president of global commodities purchasing and supplier technical assistance at Ford. He explained that the industry thought it had been covering itself against risks by using multiple suppliers. However, they did not realize that those suppliers or the suppliers of those suppliers were all using the output of the same small set of semiconductor foundries.

Kevin P. Clark, president and CEO of Aptiv, which as a Tier 1 supplier builds electronics systems for automakers, presented a sense of the scale of his company’s part of the supply chain, saying, “We receive 220 million parts from 400 suppliers daily. Of which we produce more than 90 million components shipped to 7000 to 8000 customers daily.”

Car makers typically deal closely with their Tier 1 suppliers, and Jennings said people in his position rarely met with chip manufacturers directly. “But we have now,” he said.

The suppliers agreed that they need deeper relationships with the car makers. “What it requires is strategic relationships all the way down the chain,” said Aptiv’s Clark. It will take, he continued, “co-investment not just from a dollars standpoint, but from a relationship standpoint.”

What might that mean for chip manufacturers like GlobalFoundries? According to GlobalFoundries senior vice president Mike Hogan, car maker involvement could lead to faster introduction of new chip technologies. For example, the first version of new tech could be designed to meet auto industry standards rather than today’s model, where tech developed for other industries are adapted to car makers’ needs.

This reimagining of the supply chain is happening as the car industry confronts big changes. “If you look at where we’re going from a technology standpoint, we will advance more in the next ten years than we will have in the last hundred,” Jennings said.

The move to battery electric vehicles presents a major chance to simplify the way the electronic systems in vehicles are designed. With existing internal combustion cars, those electronics have been layered on as new technologies were developed and deployed leading to a lot of complexity in both hardware and software, explains Hogan. (For a deep dive into just how complex the software situation has gotten, read “How Software Is Eating the Car.”)

Battery electric redesigns offer “a real opportunity to rethink how a vehicle is architected,” said Aptiv’s Clark. But for the supply chain to work efficiently, he thinks suppliers need to participate in that rearchitecting.

How long will it take before this dream supply chain emerges? It will likely be the work of years, executives say.

Tesla Places Big Bet on Vision-Only Self-Driving

Post Syndicated from Edd Gent original https://spectrum.ieee.org/cars-that-think/transportation/self-driving/tesla-places-big-bet-vision-only-self-driving

The latest update to Tesla’s self-driving technology ups the company’s stake in a bold bet that it can deliver autonomous vehicles using cameras alone. But despite improving capabilities in vision-based self-driving, experts say it faces fundamental hurdles.

Last Saturday, Tesla rolled out the much-delayed version 9 of its “Full Self-Driving” (FSD) software, which gives Tesla vehicles limited ability to navigate autonomously. The package, which is already on sale as a $10,000 add-on, has been in beta testing with a select group of drivers since last October. But the latest update marks a significant shift by ditching input from radar sensors and relying solely on the car’s cameras.

This follows the announcement in May that Tesla will be removing radar altogether from its Model 3 and Model Y cars built in the US and suggests the company is doubling down on a strategy at odds with most other self-driving projects. Autonomous vehicles built by Alphabet subsidiary Waymo and GM-owned Cruise fuse input from cameras, radar and ultra-precise lidar and only ply streets pre-mapped using high-resolution 3D laser scans.

Tesla CEO Elon Musk has been vocal in his criticism of lidar due to its high cost and has instead advocated for a “pure vision” approach. That’s controversial due to the lack of redundancy that comes with relying on a single sensor. But the rationale is clear, says Kilian Weinberger, an associate professor at Cornell University who works on computer vision for autonomous vehicles.

“Cameras are dirt cheap compared to lidar,” he says. “By doing this they can put this technology into all the cars they’re selling. If they sell 500,000 cars all of these cars are driving around collecting data for them.”

Data is the lifeblood of the machine learning systems at the heart of self-driving technology. Tesla’s big bet, says Weinberger, is that the mountain of video its fleet amasses will help it reach full autonomy faster than the smaller amount of lidar data its competitors relying on a small number of more sensor-laden cars driven by employees.

Speaking at the Conference on Computer Vision and Pattern Recognition last month, Tesla’s AI chief Andrej Karpathy revealed the company had built a supercomputer, which he claimed was the fifth most powerful in the world, to process all this data. He also explained the decision to drop radar, saying that after training on more than 1.5 petabytes of video augmented with both radar data and human labeling the vision-only system now significantly outperforms their previous approach.

The justification for dropping radar does make sense, says Weinberger, and he adds that the gap between lidar and cameras has narrowed in recent years. Lidar’s big selling point is incredibly accurate depth sensing achieved by bouncing lasers off objects—but vision-based systems can also estimate depth, and their capabilities have improved significantly.

Weinberger and colleagues made a breakthrough in 2019 by converting camera-based depth estimations into the same kind of 3D point clouds used by lidar, significantly improving accuracy. Karpathy revealed that the company was using such a “pseudo-lidar” technique at the Scaled Machine Learning Conference last year.

How you estimate depth is important though. One approach compares images from two cameras spaced sufficiently far apart to triangulate the distance to objects. The other is to train AI on huge numbers of images until it learns to pick up depth cues. Weinberger says this is probably the approach Tesla uses because its front facing cameras are too close together for the first technique.

The benefit of triangulation-based techniques is that measurements are based in physics, much like lidar, says Leaf Jiang, CEO of start-up NODAR, which develops camera-based 3D vision technology based on this approach. Inferring distance is inherently more vulnerable to mistakes in ambiguous situations, he says, for instance, distinguishing an adult at 50 meters from a child at 25 meters. “It tries to figure out distance based on perspective cues or shading cues, or whatnot, and that’s not always reliable,” he says.

How you sense depth is only part of the problem, though. State-of-the-art machine learning simply recognizes patterns, which means it struggles with novel situations. Unlike a human driver, if it hasn’t encountered a scenario before it has no ability to reason about what to do. “Any AI system has no understanding of what’s actually going on,” says Weinberger.

The logic behind collecting ever more data is that you will capture more of the rare scenarios that could flummox your AI, but there’s a fundamental limit to this approach. “Eventually you have unique cases. And unique cases you can’t train for,” says Weinberger. “The benefits of adding more and more data are diminishing at some point.”

This is the so-called “long tail problem,” says Marc Pollefeys, a professor at ETH Zurich who has worked on camera-based self-driving, and it presents a major hurdle for going from the kind of driver assistance systems already common in modern cars to truly autonomous vehicles. The underlying technology is similar, he says. But while an automatic braking system designed to augment a driver’s reactions can afford to miss the occasional pedestrian, the margin for error when in complete control of the car is fractions of a percent.

Other self-driving companies try to get round this by reducing the scope for uncertainty. If you pre-map roads you only need to focus on the small amount of input that doesn’t match, says Pollefeys. Similarly, the chance of three different sensors making the same mistake simultaneously are vanishingly small.

The scalability of such an approach is certainly questionable. But trying to go from a system that mostly works to one that almost never makes mistakes by simply pushing ever more data through a machine learning pipeline is “doomed to fail,” says Pollefeys.

“When we see that something works 99 percent of the time, we think it can’t be too hard to make it work 100 percent,” he says. “And that’s actually not the case. Making 10 times fewer mistakes is a gigantic effort.”

Videos posted by Tesla owners after the FSD update showing their vehicles lurching out into highways or being blind to concrete pillars in the middle of the road demonstrate the gulf that still needs to be bridged and suggests Musk’s prediction of full autonomy by the end of the year may have been overly optimistic.

But Pollefeys thinks it’s unlikely Tesla will abandon the narrative that full autonomy is close at hand. “A lot of people already paid for it [Tesla’s FSD package], so they have to keep the hope alive,” he says. “They’re stuck in that story.”

Tesla didn’t respond to an interview request.

When Infrastructure Confronts a Searing Heat Dome

Post Syndicated from Peter Fairley original https://spectrum.ieee.org/energywise/transportation/infrastructure/how-heat-domes-can-cripple-trains-power-grids

The “heat dome” that’s seared the U.S. Pacific Northwest and Western Canada since last week is afflicting both beings—human and otherwise—and infrastructure. I’ve been riding out this latest long-predicted signal of climate change in Victoria, British Columbia, where the temperature hit 39.7 ºC (103.6 ºF) yesterday—a day whose average high was (previously) 20.5 ºC. A small town in B.C.’s interior hit 47.5 ºC yesterday, breaking Canada’s longstanding temperature record recorded in Saskatchewan 80 years ago, for the second day in a row.

Many residents of coastal Oregon, Washington, and B.C. don’t have air conditioning, and they’re making do as best they can. Some are taking advantage of pop-up municipal cooling shelters. One friend outside Victoria has been giving her cats rides in her air-conditioned car, after they showed signs of heat stroke.

The region’s stretched infrastructure has gratefully held together so far, with two prominent exceptions—roads and rail.

Heat buckled road surfaces in Washington, as if Earth’s atmosphere is striking back against the petroleum-fuelled cars, trucks and buses that are the state’s #1 contributor to climate change. But the road damage caused only delays. Same goes for regional rail services under the heat dome, which cut speeds and lengthened commutes to avoid derailments from heat-distorted rails.

Even the power grids have kept humming despite A.C. users like me setting new records for peak summer demand. Utilities in this region can take more. They are designed to handle higher winter peaks driven by inefficient electric baseboard heating.

However, infrastructure did grind to a halt in Portland—the Pacific Coast city most scorched by the heat dome. It smashed temperature records Saturday, Sunday, and Monday when it may have briefly hit 47.2 ºC (117 ºF). Which, as meteorolgist Eric Holthaus noted via Twitter, would be one of the hottest temperatures recorded worldwide in a major city).

High heat combined with electric current pushed metropolitan Portland’s streetcars and light rail systems past their limits.

“In case you’re wondering why we’re canceling service for the day, here’s what the heat is doing to our power cables,” tweeted the PDX Streetcar system on Sunday, along with a photo of a seared power line. PDX Streetcar spokesperson Andrew Plambeck told me that cable warped, shifted and pressed up against superheated steel hardware on Portland’s Broadway Bridge.

Heat-induced stretching of cables posed the most widespread challenge to PDX Streetcar and regional transit operator TriMet’s MAX light-rail system. Overhead copper cables carrying 750 volts of direct current power both systems. As Portland crested above 110 ºF (43.3 ºC) on Sunday—the MAX system’s design limit—those copper cables expanded, stretched, and sagged.

Sagging lines can become entangled in the pantographs that reach up from train cars. They can even touch the train cars, creating a dangerous electric arc according to this video from French rail operator Groupe SNCF. So Portland’s operators eventually pulled their cars back to maintenance yards on Sunday, and kept them off the rails on Monday.

They returned to service Tuesday at reduced speeds. For PDX Streetcar it was to be a late start, Plambeck told me. “We had people out there trying to fix things today,” he said. “And we’ve pulled them back in because it’s simply too hot to work safely.”

Under normal conditions, pully-mounted counterweights maintain tension as temperatures rise and overhead cables expand. But on Sunday, the cables stretched so far that mechanism literally ran out of room. “Once temperatures reach a certain point the counterweight system reaches the ground. It has nowhere else to go,” TriMet spokesperson Tyler Graf told me.

TriMet tweaked its tensioning systems a few years ago to adapt its equipment to Portland’s steadily warming summers. That was back when Portland’s highest recorded temperature was still 41 ºC and, as Graf put it, exceeding 43 ºC was still “unthinkable.”

Graf couldn’t say whether the system could be tweaked further to survive the next heatwave of this magnitude. And it’s not just heat they have to worry about. In February Portland’s light rail systems shut down amidst the city’s worst ice storm, which coated overhead cables with more ice.

“We’re now coming to the conclusion that we need to invest some thought into how we, as an agency, can become more climate resilient,” said Graf. “Things we were worried about happening seem to be happening now.”

Being overtaken by climate change is a recurring theme today, according to energy experts. For decades climate scientists have been predicting more extreme weather events, and engineers and physicists have been calculating what that will mean for energy systems. Adaptation, meanwhile, has been comparatively slow.

As a trio of U.C. Berkeley researchers wrote in a San Francisco Chronicle op-ed last August: “Scientists have made more progress in developing climate data than society has made in understanding how to use it.”

Little has changed since then, especially in the electric power sector, according to Anna Brockway, a Ph.D. student in Berkeley’s Energy & Resources Group and coauthor of a 2020 review of grid planning for climate change in the journal Climate Risk Management. “The electricity sector is lagging behind,” Brockway told me by email.

That’s true even in California, wrote Brockway, which is a global leader in climate mitigation and is on the front lines of climate-driven drought and wildfires. She says that “climate adjustments” added into models that the state uses to predict future demand for electricity do not represent “the actual range of uncertainty predicted by climate scientists.”

As Brockway put it: “It seems that impacts from climate change are being felt more quickly than our decision-making processes are evolving.”

What Full Autonomy Means for the Waymo Driver

Post Syndicated from Evan Ackerman original https://spectrum.ieee.org/cars-that-think/transportation/self-driving/full-autonomy-waymo-driver

In January, Waymo posted a tweet breaking down what “autonomy” means for the Waymo Driver, which is how the company refers to its autonomous driving system. The video in the Tweet points out that Level 1, 2, and 3 autonomy are not “fully autonomous” because a human driver might be needed. Sounds good. The Waymo Driver operates at Level 4 autonomy, meaning, Waymo says, that “no human driver is needed in our defined operational conditions.” This, Waymo continues, represents “fully autonomous driving technology,” with the Waymo Driver being “fully independent from a human driver.” 

Using the term “full autonomy” in the context of autonomous vehicles can be tricky. Depending on your perspective, a vehicle with Level 4 autonomy fundamentally cannot be called “fully” autonomous, because it’s autonomous in some situations and not others, which is where the defined operational conditions bit comes in. The folks behind these levels of autonomy, SAE International, are comfortable calling vehicles with both Level 4 and Level 5 autonomy “fully autonomous,” but from a robotics perspective, the autonomy of the Waymo Driver is a little more nuanced.

While humans may not be directly in the loop with Waymo’s vehicles, there’s a team of them on remote standby to provide high-level guidance if a vehicle finds itself in a novel or ambiguous situation that it isn’t confident about handling on its own. These situations won’t require a human to take over the operation of the vehicle, but they can include things like construction zones, unexpected road closures, or a police officer directing traffic with hand signals— situations a human might be able to interpret at a glance, but that autonomous systems notoriously find difficult.

There’s nothing wrong with the approach of having humans available like this, except that it raises the question of whether a Level 4 autonomous system should really be called fully autonomous and fully independent from a human driver if it sometimes finds itself in situations where it may decide to ask a remote human for guidance. It may seem pedantic, but having a clear understanding of what autonomous systems can and cannot do is very important, especially when such topics are becoming more and more relevant to people who may not have much of a background in robotics or autonomy. This is what prompted Waymo’s tweet, and Waymo now has a whole public education initiative called Let’s Talk Autonomous Driving that’s intended to clearly communicate what autonomous driving is and how it works.

In this same spirit, I spoke with Nathaniel Fairfield, who leads the behavior team at Waymo, to get a more detailed understanding of what Waymo actually means when it calls the Waymo Driver fully autonomous.

IEEE Spectrum: Can you tell us a little bit about your background, and what your current role is at Waymo?

Nathaniel Fairfield: I’m currently a Distinguished Software Engineer at Waymo looking after what we call “behavior,” which is the decision-making part of the onboard software, including behavior prediction, planning, routing, fleet response, and control. I’ve been with the team since we were founded as the Google self-driving car project back in 2009, and my background is in robotics. Before Waymo I was at the Carnegie Mellon University Robotics Institute (where I received my Ph.D. and Masters) working on robots that could map complex 3D environments (ex: flooded cenotes in Mexico) and before that, I worked at a company called Bluefin Robotics building robots to map the ocean floor. 

How does Waymo define full autonomy?

When we think about defining full autonomy at Waymo, the question is whether the system is designed to independently perform the entire dynamic driving task in all conditions in our operational design domain (ODD) without the need to rely on human intervention, or whether it requires a human to intervene and take control in such situations to keep things safe. The former would be full autonomy, and the latter would not be. The delta between the two is the difference between the L4 system we’re developing at Waymo (the Waymo Driver) which is responsible for executing the entire dynamic driving task, and L2 or L3 systems.

What are the specific operational conditions under which Waymo’s vehicles cannot operate autonomously?

Our current ODD in Phoenix, where we have our fully autonomous service Waymo One, is around 130 km2 (larger than the city of San Francisco). This area is broad enough to cover everyday driving, which includes different roadway types, various maneuvers, speed ranges, all times of day, and so on. Our ODD is always evolving as our technology continues to advance.
Just like a competent human driver, the Waymo Driver is designed so that it will not operate outside of its approved ODD. The Waymo Driver is designed to automatically detect weather or road conditions that would affect safe driving within our ODD and return to base or come to a safe stop (i.e. achieve a “minimal risk condition”) until conditions improve.

If Waymo’s vehicles encounter a novel situation, they ask a remote human supervisor for assistance with decision making. Can you explain how that process works?

Imagine you’re out driving and you come up to a “road closed” sign ahead. You may pause for a bit as you look for a “Detour” sign to show you how to get around it or if you don’t see that, start preparing to turn around from that road and create your own detour or new route. The Waymo Driver does the same thing as it evaluates how to plot the best path forward. In a case like this where the road is fully blocked, it can call on our Fleet Response specialists to provide advice on what route might be better or more efficient and then take that input, combine it with the information it has from the onboard map and what it’s seeing in real time via the sensors, and choose the best way to proceed. 
This example shows the a few basic properties of all our fleet response interactions:

  • The remote humans are not teleoperating the cars
  • The Waymo Driver is not asking for help to perceive the surrounding environment; it can already do that. It’s asking for advice on more strategic planning questions based on what it’s already perceived. 
  • The Waymo Driver is always responsible for being safe
  • Human responses can be very helpful, but are not essential for safe driving

What are some examples of situations or decision points where the Waymo Driver may not be able to proceed without input from a human?

In addition to construction, another example would be interpreting hand gestures. While that’s something we’ve improved a lot on over the last few years, it’s a common scenario the Waymo Driver likes to call on Fleet Response for at times. The Waymo Driver can perceive that someone may be using hand signals, such as another road user waving their hands, and then it will call on Fleet Response to confirm what the gesture appears to be signaling and use that input to make a decision about when and how to proceed.

This is completely dynamic and depends on the specific scenario; not “all construction zones” or “all novel situations” will the Waymo Driver engage with Fleet Response. There are some dead ends or construction zones, for example, where the Waymo Driver may not need to call on Fleet Response at all. Those are just examples of some common scenarios we see Fleet Response utilized for—cases where the Waymo Driver may call on Fleet Response, but does not have to.

So the “driving task” is sometimes separate from “strategic planning,” which may include navigating through situations where a human is giving directions through hand signals, busy construction zones, full road closures, and things like that. And remote humans may at times be required to assist the Waymo Driver with strategic planning decisions. Am I understanding this correctly?

Zooming out a bit (this may get a little philosophical): are tasks made up of layers of behaviors of increasing levels of sophistication (so as to be able to cover every eventuality), or is it possible to carve off certain domains where only certain behaviors are necessary, and call that the task? A simplistic example would be tying your shoelaces. Does it include what I do most every day: putting on the shoe, tying the knot? Or does it also include dealing with a nasty knot that my son put in the laces? Or include patching the laces if they break? Or replacing if the break is in a bad place? Or finding new laces if I have to replace the lace? Or going to the store if I need to buy a new lace?

If it’s the first case, even humans aren’t really individually autonomous, because we rely on other individuals for assistance (changing a tire), public works (installing a traffic light), and social decision-making (traffic management of a small-town July-4th parade). If it’s the second case, then there is an endless discussion to be had about exactly where to draw the lines. So in some sense, it’s arbitrary, and we can agree to disagree, but what is the fun of that? I would argue that there are certain “useful” distinctions to draw—where there are certain sets of capabilities that allow an agent to do something meaningful.

And to clarify—this isn’t just Waymo’s perspective, it’s actually how SAE makes these distinctions. SAE essentially defines the dynamic driving task (DDT, or what the Waymo Driver is responsible for) as involving the tactical and operational functions required to operate a vehicle, which are separate from strategic functions.

EDITOR’S NOTE: According to SAE, the dynamic driving task includes the operational (steering, braking, accelerating, monitoring the vehicle and roadway) and tactical (responding to events, determining when to change lanes, turn, use signals, etc.) aspects of the driving task, but not the strategic (determining destinations and waypoints) aspect of the driving task. SAE’s definition of Level 4 autonomy involves the driving mode-specific performance by an automated driving system of all aspects of the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene.

What is the disengagement rate for Waymo’s vehicles when they are operating with passengers? What are the most frequent causes of disengagements?

“Disengagement” usually refers to when a vehicle operator in the car switches the mode from autonomous to manual. With our fully autonomous service, we don’t have vehicle operators in the car so there’re technically no “disengagements” the way the term is generally understood. We do have a roadside assistance team who can assist the vehicle (and switch it over to manual control, if appropriate) while on the road but we don’t have metrics to share on those interactions.
But, the idea that these disengagement rates should be deducted from autonomy and that anything that ever gets stuck isn’t “fully autonomous” is flawed. Under that definition, human drivers aren’t “fully” autonomous! It would be sort of silly to say that “Nathaniel is 99.999% autonomous because he had to call a tow truck that one time.” 

I agree that it would be silly to say that Nathaniel is only 99.999% autonomous because he had to call a tow truck, but that’s because most people don’t consider that to be part of the driving task—I think it might be less silly to say that Nathaniel is only 99.999% autonomous if he sometimes can’t drive through construction zones or can’t reroute himself if he encounters a road closure.

When you get into a taxi, you don’t ask yourself whether the driver has a particular license to drive on a particular road, or whether you’ll have to jump into the front seat to grab the steering wheel. You just assume that they can get you to your destination without any intervention. When you get in a vehicle driven by the Waymo Driver, you can safely make that assumption! It doesn’t mean that your human taxi driver can’t look for advice in some situations, nor does it mean that the Waymo Driver can’t do the same. 

Additionally, and as noted above, we think the SAE distinctions are helpful in determining what constitutes the dynamic driving task that an L4 automated driving system like the Waymo Driver must be able to perform, including that the DDT does not involve strategic functions. The examples you reference here are either functions the Waymo Driver can perform (such as driving through a clearly marked construction zone) or are examples of where the Waymo Driver receives information or clarification of some facts to facilitate its performance of the DDT. Human drivers (like the taxi driver!) receive information to inform their driving from radio reports, navigation devices, or even from asking adjacent motorists in stopped traffic what they see ahead, and in a confusing situation might ask a traffic officer how to get around a crash area.

So your perspective is that a system can be accurately described as “fully autonomous” if it sometimes relies on a human for strategic decision making?

Yes. the Waymo Driver is a fully autonomous driver in the Phoenix service area, and I think most roboticists would agree with me there! This is because for the purpose of driving our riders to their destinations, the Waymo Driver makes all the decisions related to the dynamic driving task.

What robotics research (besides your own, of course!) are you most excited about right now?

I’ll be honest, our research at Waymo into high-capability decision-making systems that promote safety and interact naturally with humans is about as cool (and challenging) as it gets! It involves reasoning about uncertainty (and our own limitations in sensing and interpretation), reasoning about the intentions of other agents, and how the actions of other agents will change depending on our actions, and using millions of miles of real world driving experience and cutting-edge machine learning to accelerate progress in behavior.
I’m also very impressed by both the mechanical engineering and sophisticated footstep planning shown by Boston Dynamics they are doing some really elegant robotics. And a part of my heart belongs to exploration robotics too, be it under water, under ice, or on other planets (or in the case of Europa, all three). It’s the combination of rock-solid mechanisms, robust autonomous capability, and ground-breaking scientific discovery.

The need to have a human somewhere in the loop for strategic edge cases is a very robot-y thing, and perhaps that’s why it’s incorporated into the SAE’s autonomy levels. And technically, Waymo is absolutely correct to call its vehicle fully autonomous based on that definition. I think the risk, though, is that people may not intuitively understand that “full autonomy” only applies to the dynamic driving task, and not the strategic planning task, which (for humans) is an integral part of what we tend to think of as “driving.”

What I’d really like to know is what happens, some number of years from now, after Waymo has solved the strategic planning part of driving (which I’m sure they will). Because at that point, the Waymo Driver will be more autonomous than it was before, and they’ll have to communicate that somehow. Even fuller autonomy? Full autonomy plus? Overfull autonomy? I can’t wait to find out.

Poster: Automotive Radio Frequencies

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/poster-automotive-radio-frequencies

automotive radio frequencies

Sign up and get a concise overview of the radio frequency bands and regulations in today’s and tomorrow’s cars for free Being able to manage the coexistence and interference of the various radio frequencies in an (electric) car is a major challenge for research, development and testing of in-car.

Why the Shipping Industry Is Betting Big on Ammonia

Post Syndicated from Maria Gallucci original https://spectrum.ieee.org/transportation/marine/why-the-shipping-industry-is-betting-big-on-ammonia

There’s a lot to like about ammonia. This colorless fuel emits no carbon dioxide when burned. It’s abundant and common, and it can be made using renewable electricity, water, and air. Both fuel cells and internal combustion engines can use it. Unlike hydrogen, it doesn’t have to be stored in high-pressure tanks or cryogenic dewars. And it has 10 times the energy density of a lithium-ion battery. 

For all these reasons, ammonia (NH3) is gaining favor in the global shipping industry, a multitrillion-dollar machine in need of cleaner fuels to power the freighters and tankers that haul manufactured goods and bulk materials across the ocean. Shipping companies seek climate-friendlier alternatives to petroleum that can propel their behemoth vessels for days or weeks at sea and still leave room on board for cargo.

Maritime shipping contributes nearly 3 percent of annual carbon-dioxide emissions, according to the International Maritime Organization (IMO), the United Nations body that regulates the industry. In 2018, delegates agreed to reduce emissions by 50 percent from 2008 levels by 2050. Meeting that target will require swift and widespread development of diesel-fuel alternatives and new designs for freighters, tankers, and container ships.

Shipowners and industry analysts say they expect ammonia to play a pivotal role in decarbonizing cargo ships. But there’s a crucial caveat: No vessels of any size today are equipped to use the fuel. Even if they were, the supply of renewable, or “green,” ammonia produced using carbon-neutral methods is virtually nonexistent. Most ammonia is the product of a highly carbon-intensive process and is primarily used to make fertilizers and chemicals. 

Recently, though, a handful of projects aim to change that. Finland’s Wärtsilä plans to begin testing ammonia in a marine combustion engine in Stord, Norway, by late March. Germany’s MAN Energy Solutions and Korean shipbuilder Samsung Heavy Industries are part of an initiative to develop the first ammonia-fueled oil tanker by 2024. 

Also by 2024, the Viking Energy is poised to become the first vessel propelled by ammonia fuel cells. The Norwegian energy company Equinor (formerly Statoil) charters this offshore supply vessel, which currently runs on liquefied natural gas. Chemical giant Yara will provide the green ammonia, which it plans to produce at a plant in southern Norway.

The initiative “will open up a completely new option for zero-emission shipping,” says Henriette Undrum, Equinor’s vice president of renewable and low-carbon technology. “We are not just solving one small problem for one ship. It’s part of the bigger picture. It will be a starting point to build up the market for zero-carbon fuels.”

Still, industry experts say that revamping the global shipping fleet will be extraordinarily expensive. Researchers estimate that up to US $1.4 trillion will be needed to achieve the IMO’s emissions-reduction target. And fully eliminating emissions will require an additional $500 billion, according to a January 2020 study by a panel of maritime experts.

A number of climate-friendly technologies are being considered to reach that goal, including fuel cells, hydrogen-storage systems, and large battery packs. Spinning metal cylinders, towing kites, and other propulsion methods are already helping to curb diesel fuel consumption by harnessing the wind. But ammonia will likely dominate among ocean-crossing vessels, which sail for days or weeks between refueling and rely on common infrastructure worldwide. For such ships, “ammonia is the lowest-cost zero-emission fuel that we could find,” says Tristan Smith, a researcher at University College London’s Energy Institute, which evaluated more than 30 different shipping fuels.

Smith predicts green ammonia will be produced in large volumes and will start to be used on ships during the coming decade. Other researchers make similar predictions. According to a September 2019 report from the international consultancy DNV, ammonia could make up 25 percent of the maritime fuel mix by midcentury, with nearly all newly built ships running on ammonia from 2044 onward. 

For ammonia-fueled shipping to become a reality, though, several things need to go right. Manufacturers and engineers must overcome key technical hurdles and safety issues in the design of ammonia engines and fuel cells. Port operators and fuel suppliers must build vast “bunkering” infrastructure so ships can fill ammonia tanks wherever they dock. And energy companies and governments will need to invest heavily in solar, wind, and other renewable-energy capacity to produce enough green ammonia for thousands of ships. Globally, ships consume an estimated 300 million tons of marine fuels every year. Given that ammonia’s energy density is half that of diesel, ammonia producers would need to provide twice as much liquid ammonia, and ships will need to accommodate larger storage tanks, potentially eating into cargo space.

But if these efforts succeed, it will mark a dramatic revival for a transportation fuel that’s largely sat on the sidelines since World War II.

Diesel shortages prompted the first real-world use of ammonia as a fuel. In 1942, German-occupied Belgium was struggling to find enough diesel to run its public buses, just as ridership was increasing. Engineers considered using compressed coal gas, but that fuel’s low energy density and awkward storage requirements made it impractical. 

In April 1943, Ammonia Casale (now part of the Swiss fertilizer maker Casale) introduced an internal combustion engine that could run on a blend of ammonia and coal gas. Some 100 buses in Belgium adopted the system, dubbed Gazamo. But the bus operator returned to using diesel once supplies reappeared.

Over the ensuing decades, research on ammonia engines has come in fits and starts, even as ammonia supplies soared. In the 1930s, worldwide annual production of ammonia was about 300,000 metric tons. Today, the world produces about 150 million metric tons of ammonia every year. While ammonia is valuable as a chemical feedstock, the transportation sector has had little incentive to use it. Petroleum has a higher energy density and is easier and cheaper to produce.

“Now, with a focus on having carbon-neutral fuels, it’s obviously a different discussion. The economics around it are very different,” says Peter Kirkeby of MAN Energy Solutions. “Everybody wants to know, ‘When can we have the ammonia engine?’ ” 

Kirkeby spoke from Copenhagen, where the company has a large waterfront facility on the city’s south harbor. MAN, a subsidiary of Volkswagen, develops multimegawatt diesel engines for ships and power generators. The Danish outpost has designed marine engines that run on methanol, liquefied natural gas, liquid petroleum gas, and other alternative fuels. Kirkeby says the industry’s recent push for ammonia comes as renewable-energy producers are seeking new markets, and as shipping companies look for emission-cutting solutions.

Ammonia is a simple molecule, composed of three hydrogen atoms bonded to a single nitrogen atom. Today, most industrial hydrogen is produced using an energy-intensive method called steam methane reforming, which causes the methane in natural gas to react with steam and releases hydrogen, carbon monoxide, and a small amount of carbon dioxide. Nitrogen is mainly produced by cooling air to separate it into its constituent gases: nitrogen, oxygen, argon, and carbon dioxide. 

To make ammonia, hydrogen and nitrogen are reacted with a catalyst at high temperature (about 500 °C) and high pressure (20 to 40 megapascals) via an industrial process developed by the German chemists Fritz Haber and Carl Bosch more than a century ago. To be stored in large quantities, ammonia can be liquefied by putting it under pressure (about 1 MPa at 25 °C) or refrigerating it (to –33 °C). All told, the Haber-Bosch process accounts for 1.8 percent, or half a billion metric tons, of human-caused global CO2 emissions each year.

If ammonia is to play a part in reducing maritime emissions, the fuel must be made in a cleaner way. For example, the hydrogen can be made through electrolysis, splitting water into hydrogen and oxygen using electricity from a renewable source such as wind or solar power. Renewable energy can also be used to separate nitrogen from air.

Boosting fuel supplies and building fuel-distribution infrastructure are the biggest challenges to ammonia-powered shipping, experts say. Only tiny amounts of green ammonia are now being produced. A trial plant at the Fukushima Renewable Energy Institute in Japan uses solar power and water electrolysis to produce 20 to 50 kilograms of green ammonia per day. A demonstration system at the Rutherford Appleton Laboratory, in Oxfordshire, England, is powered by an on-site wind turbine and makes up to 30 kg of green ammonia daily. [For a look at how a farmer in Iowa is using solar power to produce green ammonia, see “A Retired JPL Engineer’s Journey: From Space Probes to Carbon-Neutral Farming.”] 

Larger initiatives are underway in Australia, Chile, and New Zealand. In Queensland, for example, the Australian Renewable Energy Agency recently backed a A$3.9 million (US $3.0 million) feasibility project for a plant that could produce 20,000 metric tons of ammonia annually, using 208 gigawatt-hours of electricity. The global shipping industry used the equivalent of 3.05 million GWh in 2015. Substituting just 10 percent of that total with green ammonia will require some 550,000 GWh of renewable electricity, according to the Korean Register of Shipping.

As green ammonia slowly scales up, the shipping industry will have to solve some other problems. The top concern is ammonia’s toxicity. In concentrated form, the pungent, colorless gas can be deadly. In January 2020, a spill of nearly 3,000 liters of liquefied ammonia fertilizer in Illinois sent more than 80 people to the hospital with chest pain, eye irritation, cough, and severe headache. Ammonia manufacturers and distributors must follow strict handling and safety guidelines to minimize the potential for disaster. To use ammonia fuel, ships will need additional safety equipment, such as emergency ventilation and gas-absorption systems. 

Fortunately, operators of chemical tankers—large vessels designed to transport hazardous products—already have experience handling ammonia. About 10 percent of annual production is transported by sea. These ammonia tankers may be among the first vessels to use the chemical for fuel, in the same way that today’s liquefied natural gas carriers burn some of their own cargo while sailing.

Still, using ammonia in the engine room poses new risks. MAN’s engine will likely include double-walled fuel pipes to prevent gas from escaping should the inner pipe leak or rupture. A mechanical ventilation system will intercept any leaking gas and alert the ship’s crew.

Ammonia is also corrosive to some alloys containing copper and nickel and to some plastics. The fuel is difficult to ignite and doesn’t sustain combustion well. Engineers could solve the ignition problem by combining ammonia with a liquid pilot fuel, such as diesel, though that would boost the ship’s carbon footprint. Or they could potentially combine it with better-burning liquid hydrogen; that would require adding hydrogen tanks or equipment to separate hydrogen from the ammonia as needed.

Air pollution from burning ammonia presents another puzzle for engineers to solve. When burned at high temperatures, ammonia produces nitrogen dioxide, which contributes to smog and acid rain and can harm people’s respiratory systems. Combustion also yields small amounts of nitrous oxide—a greenhouse gas that’s significantly more potent than carbon dioxide and methane. If necessary, shipbuilders could install special equipment, such as for selective catalytic reduction, to avoid such outcomes. Japan Engine Corp. and the National Maritime Research Institute, in Tokyo, evaluated such devices on a 7.7-kilowatt, single-cylinder engine using a diesel-ammonia mixture.

Another option for eliminating harmful emissions is to use fuel cells rather than an internal combustion engine. In simple terms, a fuel cell converts chemical energy into electrical energy without burning the fuel, thus avoiding the release of harmful gases or particles into the air. Although existing fuel cells don’t have an adequate power capacity for ships, experts believe the devices will eventually be able to provide a higher efficiency and lower emissions profile than internal combustion engines.

About two dozen projects have successfully demonstrated that fuel cells can power and propel smaller vessels. Many of these involve the electrochemical reaction of hydrogen and oxygen in what’s known as a proton-exchange membrane fuel cell, which operates at low temperature and pressure. But ammonia is not a suitable fuel for  these devices. NH3 is more difficult to oxidize than hydrogen is, and so it requires higher temperatures to speed up the reaction.

Researchers say a better fit may be the solid-oxide fuel cell, which uses a solid ceramic material such as zirconia as the electrolyte. These devices can operate at high temperatures of about 1,000 °C. A 2-megawatt system is being installed on the Viking Energy supply ship in Norway and will be tested beginning in 2024.

In France, meanwhile, a new cruise vessel will demonstrate a 50-kW solid-oxide fuel cell system when delivered in 2022. Shipbuilder Chantiers de l’Atlantique and the Swiss line MSC Cruises are spearheading the initiative. Although the fuel cell will initially run on liquefied natural gas, it will also be compatible with ammonia, methanol, and other gaseous fuels, the partners say.

In the near term, fuel cells are expected to play only a complementary role on ships, supplying electricity for auxiliary systems and navigational equipment. If developers can scale up the technology to propel large ships and bring down manufacturing costs, fuel cells could eventually provide the least expensive way to operate ammonia vessels, says Carlo Raucci, who was a principal consultant of University Maritime Advisory Services, in London, at the time of our interview. A big container ship would need more than 60 MW of fuel-cell capacity, while a small bulk carrier might need only 2 MW, he says.

Other experimental systems aim to prove the viability of ammonia at sea. MAN plans to start full-scale tests on a two-stroke ammonia engine in Copenhagen this year, Kirkeby says. In 2019, the company partnered with Japan’s Kyushu University to assess the combustion and heat-release characteristics of ammonia on a smaller combustion rig. Separately, MAN is developing an ammonia engine for a medium-size container vessel in a project with the Shanghai Merchant Ship Design & Research Institute.

“On the technology side, we see some work ahead for ammonia,” Kirkeby says. “But it’s doable.”

All of the forecasting and speculation around ammonia, fuel cells, and the like assume that the shipping industry will embrace such climate-friendly approaches. Critics say the International Maritime Organization’s emission-reduction goals aren’t ambitious enough, and it’s unclear how the IMO will ultimately enforce the rules. Regulators will need to compel, not just encourage, companies to eliminate greenhouse-gas emissions, Raucci says. “There is a need for policy-driven objectives to decarbonize the shipping industry.”

A May 2020 survey by the American Bureau of Shipping captures the uncertainty sowed by today’s vague policies. Nearly two-thirds of shipowners and operators said they have no decarbonization strategy in place. Even so, nearly 60 percent of respondents said they view hydrogen and ammonia as the most attractive fuel choices in the long term—even if they don’t have plans to use them yet.

“We think that the major reason behind this [disparity] was the lack of regulatory framework so far,” says Sotirios Mamalis, who manages the American Bureau of Shipping’s sustainability, fuels, and technology program from Houston. “A lot of the owners, management companies, and operators are not necessarily aware of what they need to do in order to develop a decarbonization strategy.”

One policy tool would be to set a global price on CO2 emissions, Raucci says. This would make it more expensive to use fossil-fuel products, allowing alternative fuels like ammonia to compete. International regulators could also establish standards limiting a fuel’s carbon content by mass, similar to existing restrictions on the sulfur content of fuels.

The new initiatives by MAN Energy Solutions, Samsung, Equinor, and other companies will be critical for determining ammonia’s potential within the shipping industry. Given that vessels can operate for decades, companies “need to make sure that they’re investing in a fuel that has a good chance of being used long-term,” Raucci says. “The maritime industry at this moment has a very complex choice to make.”

This article appears in the March 2021 print issue as “The Ammonia Solution.”

Mining Traffic Data for Insights About The Pandemic

Post Syndicated from Tekla S. Perry original https://spectrum.ieee.org/view-from-the-valley/transportation/efficiency/mining-traffic-data-for-insights-about-the-pandemic

Every year for the past decade TomTom, the location technology company that supplies mapping and traffic data to navigation devices, carmakers, and apps around the world, releases an analysis of the world’s traffic.

This analysis includes an index of congestion levels, created from data collected from 600 million drivers in 416 cities around the world, aggregated anonymously, and crunched with the company’s proprietary algorithms. Their process identifies routes and calculates both optimal and average drive times. The outcome is expressed as a percent, that is, how much extra time the average trip took in a particular city during a particular time period, compared with how long it would take to drive that route with no traffic delays whatsoever.

TomTom’s index features an overall “competition” for the dubious title of most congested city in the world. In 2019, Bengaluru, India (Bangalore) and Manila, Philippines took the top spots, with traffic congestion in those cities increasing drive time by 71 percent.

TomTom also breaks down its results by hours, days, and weeks, highlighting local rush hours and weekly and daily trends. This data gets used by local governments to find ways to improve traffic flow, by employers to adjust work schedules, and by individuals to calculate commute times—all in hopes of making traffic flow a little better.

For 2020, however, TomTom’s results revealed more about the pandemic than about the successes or failures of traffic mitigating efforts.

Indeed, its overall rankings turned out to be basically meaningless: Moscow topped the 2020 charts at 54 percent, but that’s not because Moscow’s drive times increased from 2019; they actually dropped 5 percent. Rather, Bengaluru and Manila dropped in the ranks, because India faced more strict pandemic restrictions.

So in 2020, instead of showing where new development caused snarls or where a infrastructure improvements eased congestion, TomTom’s traffic data painted a picture of the coronavirus spreading around the world. The data also showed the extent of local lockdown orders, how well those were followed in different cities, and the reaction of workers when they were lifted.

Gijs Peters, a data scientist at TomTom, describes the pandemic as viewed through the lens of traffic:

“When Wuhan went into lockdown, traffic there was gone,” he says. “Everything was still normal here in Europe. Then we watched the virus spread by watching traffic data. Traffic collapsed in Milan, then Rome, then the rest of Italy, followed by other European countries. …

 “In the West,” Peters continues, “the first lifts of lockdown restrictions came in the summer, then they went back into place in September, in some cases more strict than in April. However, when we look at the traffic data, while we saw rush hour completely disappear in European cities in March, April, and May, now, even with similar restrictions in place, we see rush hour patterns again. The sense of urgency seems to be lower.”

Moving the slider on this interactive graphic shows how traffic changed from 2019 to 2020 as a result of responses to the pandemic.

Peters points out that changes in traffic patterns in the United States varied widely from city to city:

“Minneapolis had stricter lockdowns compared with other U.S. cities. Traffic congestion there went to half in April and still is very low,” he says. “In Florida, however, where the lockdown was lifted on the first of June, traffic seems to be back to normal.

“Meanwhile, in San Jose and the San Francisco Bay Area, we saw traffic drop ahead of the lockdown orders; as soon as employers said [to] start working from home. Working at home was easy for tech employees to do. So though you see traffic in many large U.S. cities catching up in recent months, traffic around San Jose is still very low.”

This kind of pandemic-related data drew the attention of financial analysts, banks, and media, trying to figure out how the pandemic was affecting daily lives and the overall economy.

Meanwhile, for traffic planners, the pandemic brought in data that one could only have dreamed of gathering in normal times.            

For example, Peters says, “When I look at [The] Netherlands, the total number of driven kilometers in April was about 50 percent of what we expected, and congestion was almost gone. In November, with second lockdown, congestion was still almost gone, but we saw the number of driven kilometers back up to 80 to 90 percent. What that tells us is, if we are able to reduce our traffic by 10 or 15 percent, we would be able to limit and potentially completely prevent congestion.”

Peters hopes the work he and other data scientists are doing with TomTom’s pandemic era traffic data will lead to long term changes.

“If we are smarter,” he says, “and only go to work when we need to, that could lead to 10 percent of people staying home on average each day. And then we might be able to spend so much less time in traffic than we do right now. That would help us work towards a congestion-free, emissions-free future.”

A 150kph Boat Powered by Wind Only

Post Syndicated from LEMO original https://spectrum.ieee.org/transportation/marine/a-150kph-boat-powered-by-wind-only

The sailing speed record has been held for 8 years. A team of students and young engineers is in the process of developing a kiteboat to smash this record in 2022. Projected speed: 80 knots. The story of an audacious project told by two of its co-founders.

At 3:30 a.m. on Lake Geneva last July, under clear skies the air is fairly warm. Along the shoreline, you can see the lights of the town of Morges.

On board small boats, protected from indiscreet eyes in the half-light of dawn, a dozen young people are intently watching the behaviour of a 4-m long shape, pulled by a zodiac inflatable boat, cutting smoothly through the dark water. The technical problems revealed during the first test, five nights earlier, have been corrected. This time, the zodiac can accelerate, the shape follows it obediently. Data collected by the sensors confirm the impressions: everything goes according to the simulations. 

This is excellent news for the three initiators of these night tests, Mayeul van den Broek, Xavier Lepercq and Benoît Gaudiot. Yet another step towards realizing their crazy dream – to beat the world sailing speed record. However, this will have to wait another two years if it all goes as planned. The sun is rising over the Mont-Blanc, unveiling its outline over the south shore of the lake: it is time to return the prototype discreetly into its shed.

Lepercq, van den Broek and Gaudiot were made to meet.

All three are French, sailing lovers and have decided to study engineering. Each of them has chosen the Federal Institute of Technology (EPFL), convinced by its naval competence.  The prestigious institute had been a partner to the Swiss syndicate Alinghi (winners of the Americas Cup in 2003 and 2007) and of the “Hydroptère” the first large “flying boat” (sailing speed record in 2009).

Lepercq was already working and van den Broek finishing his Master’s degree in 2017, when they met Gaudiot, a first-year student. Their complicity was immediate. In the newcomer’s notebook, there were even sketches of kiteboats quite similar to theirs. Moreover, their interests were complimentary: engineering, materials, mechanical design, fluid dynamics … and Gaudiot, as an ex-member of the French national kitesurf team and Under-18 sailing speed record man, could be the ideal test pilot. When chances are all on your side to form a “dream team”, you must seize the opportunity. The three men thus decided to work together on a kiteboat project to make their speed world record dream come true. Their eyes riveted on the current record, set in November 2012 on Namibian waters by Paul Larsen. The Australian, at the helm of Vestas Sailrocket 2, beat two confirmed world records: on 500m at the speed of 65.45 knots (121.06kmph) and on the nautical mile (1852m) with 59.37 knots (109.94kmph). A real sporting feat, given that until then the 50-knot barrier seemed impassable for a vessel without an engine.

Just like the sound barrier, this limit is also dictated by the laws of physics. “At such speed, water pressure on the keel or the fin drops so rapidly that water starts boiling at ambient temperature.” explains Mayeul van den Broek. “This change increases drag and makes navigation very unstable – further acceleration becomes impossible.”

This phenomenon is called cavitation. Its powerful effects can blow into pieces the steel blades of a hydroelectric turbine. Their “scorch marks” can also be seen on the fins of tuna fish or dolphins, having paid painfully for their bold desire for speed. 

“Paul Larsen used an innovative super-ventilating fin. This profile is used by hydroplanes, these engine-propelled boats flying at 350kmph, but was unprecedented in the world of sailing.” With its triangular shape and straight edges, this fin does not avoid cavitation, but manages to control the disturbing effect. “At high speed, the air bubbles remain stable”, explains Benoit Gaudiot, “there’s no more drag and so it is possible to continue accelerating.”

For the three friends, this is the key to Larsen’s record, rather than the asymmetrical design of Sailrocket 2 which had attracted full attention so far. They wanted to know for certain, so, in early 2018, they produce super-ventilating fins, in order to become familiar with the technology. They fitted them on a readily available support vessel that they knew well, a kitesurf. After three test runs on the Mediterranean, Gaudiot reached 41 knots (almost 80kmph). It is a proof of concept: combining a kitesurfing sail and a super-ventilating fin is the winning formula indeed.

However, 41 knots are not fast enough to benefit from the real potential of the super-ventilating fins: 50 knots should be the target speed. “We needed more power, so a larger kite” explains van den Broek. A kite that Gaudiot would not be able to hold with his arms. “This is when we came back to our idea of a boat.”

Between September 2018 and early 2019 the first concepts were drafted. Their sailing behaviour had to be simulated. As Velocity Prediction Programs (VPP) used by naval architects are too costly, LepercQ spent several months programming their own. As for van den Broek, with his Master’s degree in hand, he spends his time looking for sponsors and developing cooperation with the EPFL.

The VPP confirmed the design’s stability and the project’s feasibility. During the following months, the dream started taking shape. The EPFL recognized the project, gave access to its infrastructures and authorized students to participate in the project as part of their studies. In October, a student association was created, along with the SP80 company, the project owner. The project was officially launched and presented to the public. It was a success: the technical challenge was met, the exciting record-setting race and the spectacular kiteboat could be launched.

With its streamlined 7m hull, its closed cabin, its “wings” fitted with floats and a rear tailplane, the SP80 looks more like a jet than a boat.

Using composite materials, it weighs only 150kg when empty. At the end of a several-dozen-meter cable, a huge kite – sized between 20 to 50m2, depending on the needs. The power-to-weight ratio is absolutely amazing, “never reached before in the world of sailing!” highlights van den Broek.

It is so powerful, that the weight of the cabin does not even count in the equation. It doesn’t join the kite in the skies simply because its main hydrofoil is curved and “anchors” it into the water. These two opposing forces have also been used by Sailrocket 2. “This avoids capsizing: the stronger the kite pulls, the more the hydrofoil pulls to the opposite side.”  

This permanent balance, created passively, is ensured by what SP80 calls the propulsion module. “It is the heart of the boat’s power, the place where all the forces are centred. The main idea of our design is to separate the rear module pushing the boat, from the cockpit that ensures the pilot’s stability and security.”

The design of the propulsion module, both mobile and robust, has taken up most part of the design phase. “We found solutions that were stable at certain speeds, but not at others. We had to find the best compromise.” The module being the key element of the boat, SP80 keeps these details confidential.

The design of the kiteboat completed, now it had to be tested in real conditions to prove the VPP simulations. A 1:2-scale prototype was designed and assembled by the students. It was this prototype that the SP80 team took for night testing in early July on Lake Geneva. About ten similar sessions have taken place until October.

Every night, several series of tests are run, returned on land in between, for adjustment and modification. The Zodiac pulls the prototype with a mast, simulating the kite and its cable. On the prototype, an inertial system records speed and acceleration and sensors follow the rotation speed, which is all you need to be able to verify the boat’s behaviour. The sensors are connected by robust IP68 LEMO connectors (K and E series) to the navigation system, collecting the data. 

Early morning, the boat’s taken out of the water, dismounted and returned to the SP80 shed, the team analyses the videos and measurements. The aim is to make sure that no element of the boat is overcharged and no unnecessary force is generated. “For instance, that the immersed part of the rudder is not overloaded” explains Gaudiot, “since it is for the pilot to compensate, to be able to steer the boat.”

Lake Geneva does not offer optimal conditions (still waters, regular strong winds would be necessary to beat the record), but the tests are working out very well. As the design of the kiteboat is finally stabilised, SP80 has now started developing the ultimate boat. 

The construction of the boat is scheduled to start early 2021, to be launched at the end of 2021. The world record attempt is planned for 2022.

By a strange coincidence, this agenda corresponds exactly to the plans of Syroco. Co-founded by French kitesurf star Alex Caizergues (the first to exceed 100kmph in sailing), this startup is also working on a kiteboat designed for beating the record and exceeding the 80 knots. However, competition does not intimidate SP80. “ On the contrary”, say Gaudiot and van den Broek. “Why not organise a shared event? It would be a spectacular “first!”

The SP80 Kiteboat

In view of the target speed, the boat’s design is inspired more by motor-boats than by sailing boats. It weighs more, using materials and structures to withstand higher loads. Sailing speed record regulations (drafted when the record stood at only 26 knots!) require human presence, but do not specify anything with regard to the pilot’s security. The SP80 pilot will be protected like off-shore pilots: closed cabin, six-point harness seat belt, oxygen mask in case of capsizing.

  1. Cockpit

This is where the pilot is steering the boat and controls the kite. Since regulations forbid assisted steering, sensors and instruments only provide information to the pilot. They inform him for example if he must immediately drop the kite. 

  1. Hulls

Always on the water, they ensure lateral stability and buffer the impact of waves. They slow down the boat a little bit, but are necessary for the pilot’s comfort.

  1. Main hydrofoil

Strongly curved, it “anchors” the boat into the water by opposing its force to the force of the kite, preventing the boat from lateral drag. Its profile is super-ventilated, limiting disturbance from cavitation and enabling the boat to exceed 50 knots.

  1. Rudder

The boat’s rudder is in an unusually forward position. It also has a super-ventilated profile to control the effects of cavitation.

  1. Power management module

This is where the flying kite’s cables are attached and that all forces are concentrated. The articulated system ensures passively the balance of forces between kite and fins, conferring power and preventing capsizing.

  1. Kitesail

The prototypes are in the design process. As for kitesurf and paragliding, they should be made of fabric, possibly nylon. Among the available kites (between 20 and 50m2) the best adapted to wind conditions will be selected. This will also define the cable length (between 40 and 90m).





MATERIAL :        


TARGET SPEED :               

>80 KNOTS (APPROX. 150 KM/H)

KITE SURFACE:         

FROM 20 TO 50M2

CABLE LENGTH :              

FROM 40 TO 90M

How Is This a Good Idea: Car Dashboard Video Games

Post Syndicated from Stephen Cass original https://spectrum.ieee.org/cars-that-think/transportation/advanced-cars/hitagi-car-dashboard-videogames

Modern cars have become just another computer peripheral. Internally, a host of embedded processors handle tasks that range in complexity from rolling windows up and down to something close to autopilot. Externally, wireless smartphone connections allow a driver to monitor their car’s performance and send remote instructions to warm up the vehicle or unlock the doors. 

So why not lean into the computery nature of the modern car and use it for more than just driving around? Don’t take yourself so seriously: Use this machine, when safely parked, for having some fun. That appears to be the logic behind the notion of using the car dashboard screen—and often the steering wheel—as a platform and interface for video games.

These car-based games fall into three broad categories: Those that use a car’s center touchscreen for casual gaming recreation while the car is parked; those that co-opt the cars’ controls in some way, so that, for example, a virtual racing car can be controlled by a real steering wheel, also while parked; and finally, the as-yet-not-implemented idea that augmented reality and other games could be integrated into the active driving experience.

The first category falls into the domain of “harmless if somewhat pointless.” Looking at the games already on offer in Tesla cars, many of them are ports of classic Atari arcade titles such as Missile Command and Centipede, although some more recent games such as CupheadFallout Shelter and Beach Buggy Racing 2 have also been adapted. These are intended to allow a driver to kill some time while parked, at an EV charging station perhaps (a longer and more passive experience than popping into a gas station to fill a tank). 

But anyone who is driving a Tesla is going to have a much better piece of hardware to play games already on hand, in the form of their smartphone. Admittedly, a phone’s screen is much smaller than the Tesla’s display, but the phone has the advantage that it has a vastly larger selection of titles and can be played in the hands, rather than requiring the driver to extend their arms to play. I expect that the best use case for this category of game will prove to be in the least flashy games—chess and backgammon—where a driver and passenger might use the screen as board to play against each other. Otherwise, it all feels like a feature for a feature’s sake, good for a flex while showing off a new car, but not much else.

The next category of games—those that use a parked car as a glorified controller—edges into more dubious territory. The fundamental issue is that cars are not just another peripheral. They are heavy machinery. The non-profit National Safety Council estimates that in the United States, 38,800 people lost their lives due to car crashes in 2019, with another 4.4 million suffering serious injury. While there are no good statistics for deaths caused by, say, accidents involving laser printers, I’m willing to bet it’s a much, much smaller number. Until autonomous driving technology is good enough to take humans out of the loop entirely—so called Level 5 autonomy—drivers hold life and death in their hands every time they sit behind the wheel. 

This may seem like a moot point if the games can only be played while the car is parked. But the same controls previously dedicated to the licensed operation of a car are now also used for consequence-free light entertainment. 

In user experience terms, having the same input produce different outputs is known as a mode-based or modal interface. Popular in the days of computing when interactive input was often limited to the channel of a single keyboard, modal interfaces have since fallen out of favor. This was in large part because users tended to make so-called mode errors, where the user’s mental model of the system falls out of sync with the actual state of the system—something known as mode confusion. And they sometimes issue inappropriate commands in the belief that they’re using a different mode.

Mode confusion is irritating if you, for example, accidently delete a file while working at a computer. But it can be lethal when it happens elsewhere. For example, a number of aviation accidents have been caused by pilots making mode errors with controls in the cockpit.

Tesla Arcade does lock out some driving controls when playing a game: pressing the accelerator, for example, produces a warning notice. But turning the steering wheel to control a game car still also turns the wheels of the real car. It is easy to imagine a scenario where somebody parks their car with the wheels aligned straight ahead, then becomes immersed in a racing game while their partner runs an errand. Their partner returns and gets back in the passenger seat. The driver immediately turns off the game, starts the car and begins to back out—forgetting that the last thing they were doing in the game was taking a sharp curve. So instead of reversing straight back out, the wheels are set so the cars turn into another vehicle—or a pedestrian. 

The next proposed category of in-car gaming, where the game is tied into the active driving experience, is even more worrisome. In May, Elon Musk mused on Twitter about the possibility of having something like the augmented reality hit Pokemon Go running on Teslas. Whether any such game is played using an in-car display or some kind of heads-up display, the issue is that it will be inevitably adding to the driver’s mental load, raising the likelihood of distraction at a critical moment. 

There have been some very public incidents where drivers, lulled into a false sense of security by autonomous driving systems, have become so distracted as to be practically somnambulant: A pedestrian crossing the road was killed during a 2018 Uber autonomous driving road test in Arizona, and a driver’s overreliance on a Tesla’s autopilot system got him killed when a truck failed to yield properly in 2016. But it doesn’t take the latest in AI technology to beguile drivers. 

Safety experts have previously raised concerns about common in-vehicle information systems, which are intended to help drivers with navigation, provide audio entertainment, or support hands-free phone calls or text messaging. A 2017 report by the AAA Foundation for Traffic Safety warned that many such systems already place excessive visual or mental demands on drivers. The truth is that we are simply not as good at multitasking as we like to think we are. And every additional task we try to perform simultaneously—such as completing a game objective while also paying attention to traffic—pushes us closer to a condition that accident investigators refer to as task saturation

As a person reaches task saturation, their situational awareness becomes more and more spotty, and they can end up simply ignoring critical warnings, or become incapable of completing all the things they need to do in time to avoid disaster. And given that every game designer’s objective is to grab and hold our attention, it’s not much of a stretch to imagine that actively playing a game while driving would make more mental demands than using, say, a satellite navigation display. 

So let’s keep the games where they belong—away from steering wheels and actual car dashboards.

This Year, Autonomous Trucks Will Take to the Road With No One on Board

Post Syndicated from Evan Ackerman original https://spectrum.ieee.org/transportation/self-driving/this-year-autonomous-trucks-will-take-to-the-road-with-no-one-on-board

Companies like Tesla, Uber, Cruise, and Waymo promise a future where cars are essentially mobile robots that can take us anywhere with a few taps on a smartphone. But a new category of vehicles is about to overtake self-driving cars in that leap into the future. Autonomous trucks have been quietly making just as much, if not more, progress toward commercial deployment, and their impact on the transportation of goods will no doubt be profound.

Among nearly a dozen companies developing autonomous trucking, San Diego–based TuSimple is trying to get ahead by combining unique technology with a series of strategic partnerships. Working with truck manufacturer Navistar as well as shipping giant UPS, TuSimple is already conducting test operations in Arizona and Texas, including depot-to-depot autonomous runs. These are being run under what’s known as “supervised autonomy,” in which somebody rides in the cab and is ready to take the wheel if needed. Sometime in 2021, the startup plans to begin doing away with human supervision, letting the trucks drive themselves from pickup to delivery without anybody on board.

Both autonomous cars and autonomous trucks rely on similar underlying technology: Sensors—typically cameras, lidars, and radars—feed data to a computer, which in turn controls the vehicle using skills learned through a massive amount of training and simulation. In principle, developing an autonomous truck can be somewhat easier than developing an autonomous car. That’s because unlike passenger vehicles, trucks—in particular long-haul tractor-trailers—generally follow fixed routes and spend most of their time on highways that are more predictable and easier to navigate than surface streets. Trucks are also a better platform for autonomy, with their large size providing more power for computers and an improved field of view for sensors, which can be mounted higher off the ground.

TuSimple claims that its approach is unique because its equipment is purpose built from the ground up for trucks. “Most of the other companies in this space got the seeds of their ideas from the DARPA Grand and Urban Challenges for autonomous vehicles,” says Chuck Price, chief product officer at TuSimple. “But the dynamics and functional behaviors of trucks are very different.”

The biggest difference is that trucks need to be able to sense conditions farther in advance, to allow for their longer stopping distance. The 200-meter practical range of lidar that most autonomous cars use as their primary sensor is simply not good enough for a fully loaded truck traveling at 120 kilometers per hour. Instead, TuSimple relies on multiple HD cameras that are looking up to 1,000 meters ahead whenever possible. The system detects other vehicles and calculates their trajectories at that distance, which Price says is approximately twice as far out as professional truck drivers look while driving.

Price argues that this capability gives TuSimple’s system more time to make decisions about the safest and most efficient way to drive. Indeed, its trucks use their brakes less often than trucks operated by human drivers, leading to improvements in fuel economy of about 10 percent. Steadier driving, with less side-to-side movement in a lane, brings additional efficiency gains while also minimizing tire wear. Price adds that autonomous trucks could also help address a shortage of truck drivers, which is expected to grow at an alarming rate.

TuSimple’s fleet of 40 autonomous trucks has been hauling goods between freight depots in Phoenix, Tucson, Dallas, El Paso, Houston, and San Antonio. These routes are about 95 percent highway, but the trucks can also autonomously handle surface streets, bringing their cargo the entire distance, from depot driveway to depot driveway. Its vehicles join a growing fleet of robotic trucks from competitors such as Aurora, Embark, Locomation, Plus.ai, and even Waymo, the Alphabet spin-off that has long focused on self-driving cars.

“I think there’s a big wave coming in the logistics industry that’s not necessarily well appreciated,” says Tasha Keeney, an analyst at ARK Invest who specializes in autonomous technology. She explains that electrified autonomous trucks have the potential to reduce shipping expenses not only when compared with those of traditional trucking but also with those of rail, while offering the door-to-door service that rail cannot. “The relationships that TuSimple has made within the trucking industry are interesting—in the long term, vertically integrated, purpose-built vehicles will have a lot of advantages.”

By 2024,TuSimple plans to achieve Level 4 autonomy, meaning that its trucks will be able to operate without a human driver under limited conditions that may include time of day, weather, or premapped routes. At that point, TuSimple would start selling the trucks to fleet operators. Along the way, however, there are several other milestones the company must hit, beginning with its first “driver out” test in 2021, which Price describes as a critical real-world demonstration.

“This is no longer a science project,” he says. “It’s not research. It’s engineering. The driver-out demonstration is to prove to us, and to prove to the public, that it can be done.”

This article appears in the January 2021 print issue as “Robot Trucks Overtake Robot Cars.”

Uber Sells its Robocar Unit

Post Syndicated from Philip E. Ross original https://spectrum.ieee.org/cars-that-think/transportation/self-driving/uber-sells-its-robocar-unit

Uber is selling its robocar development operation to Aurora and calling the move a step forward in its quest for autonomous driving technology.

True, it will now have a big stake in the two companies’ combined robocar projects. But this is the latest wrinkle in the consolidation that is under way throughout the self-driving business. Uber itself has in the past been among the acquisitive companies.

But this news is not something Uber’s founder would have welcomed. And it puts the lie to two verities common just a few years back: that every big player in road transport needed its own robocar research unit and that the payoff would come soon—like, now. 

The sale is valued at US $4 billion—a far cry, as Reuters reports, from the $7.5-billion valuation implicit in Uber’s deal last year to raise $1 billion from investors, including Toyota. But it’s still a hefty chunk of change, and that means Uber still has access to a trove of IP and, perhaps as important, robotics talent.

Indeed, when the Pittsburgh company’s disgraced founder and former CEO, Travis Kalanick, first bet big on self-driving tech in early 2015, he went on a hiring spree that gutted the robotics department of Carnegie Mellon University (CMU), also in Pittsburgh. Aurora is based there, too, so there won’t be an out-migration of roboticists from the area.

“Uber was losing $1 million to $2 million a day with no returns in sight in the near future,” says Raj Rajkumar, a professor of electrical and computer engineering at CMU. “Aurora has deep pockets; if it wins, Uber still wins. If not, at least this will cut the bleeding.”

Kalanick spent money like water, then was forced out in 2017 amid allegations of turning a blind eye to sexual harassment.  The company’s stock remained a favorite with investors, hitting an all-time high just last week.  At today’s market close the market capitalization stood at just under $94 billion, about half again as much as GM’s value. Yet Uber has never turned a profit.

Not turning a profit was once a feature rather than a bug. In the late 1990s, investors were able to put whatever valuation they pleased on a startup so long as that startup did not have any earnings. Without earnings, there can be no price-to-earnings ratio, and without that, my opinion of a company’s value is as good as yours.

In that tech bubble, and perhaps again in today’s mini-bubble, the value comes from somewhere else. It stems from matters unquantifiable—a certain feeling, a je ne sais quoi. In a word, hype.

Those 1990s dot-com startups were on to something, as we in these pandemic times, living off deliveries from FreshDirect, can testify. But they were somewhat ahead of their time. So is robocar tech.

Self-driving technology is clearly transforming the auto industry. Right now, you can buy cars that hew to their lanes, mitigate head-on crashes, warn of things lurking in your blind spots, and even check your eyes to make sure you are looking at the road. It was all too easy to project the trendline all the way to truly autonomous vehicles.

That’s what Uber (and a lot of other companies) did in 2016 when it said it would field such a true robocar in 2021. That’s three and a half weeks from now.

It was Uber, more than any other player, that showed the hollowness of such hype in 2017 when one of its robocars got into an industry-shaking crash in Arizona. The car, given control by a driver who wasn’t paying attention, killed a pedestrian. Across the country, experimental autonomous car fleets were temporarily grounded, and states that had offered lenient regulation began to tighten up. The coming of the driverless era suddenly got set back by years. It was a hard blow for those vendors of high-tech sensors and other equipment that can only make economic sense if manufactured at scale.

The industry is now in long-haul mode, and that requires it to concentrate its resources in a handful of places. Waymo, Aurora, GM and a handful of big auto companies are obvious choices, and among the suppliers there is the odd clear success, like Luminar. The lidar maker had a stellar coming out party on Wall Street last week, one that put Austin Russellits 25-year-old founder, in the billionaires’ club.

But a shakeout is a shakeout. Despite its stellar market cap, Uber is still a ride-hailing app, not General Motors. The company was wise to get out now.

Ford’s 2021 F-150 Pickup Is a Mobile Power Station

Post Syndicated from Lawrence Ulrich original https://spectrum.ieee.org/cars-that-think/transportation/advanced-cars/fords-2021-f150-pickup-is-a-mobile-power-station

Pickup trucks have suddenly become America’s latest battleground in electrification: Whether General Motors’ reborn Hummer, deep-pocketed start-ups like Rivian, or Tesla’s Mad Max-style Cybertruck, companies are angling for a slice of a wildly popular and lucrative market.

Ford, whose F-Series pickup has been America’s best-selling vehicle of any type for 38 straight years—it finds 900,000 customers in a good year—is targeting mid-2022 for its own all-electric F-150. Until then, its redesigned aluminum-bodied 2021 F-150 delivers a pair of electron-centric gains: Primarily, it has the first full hybrid system in any full-size pickup, with class-leading EPA fuel economy of 24/24 mpg in city and highway driving.

But as with the blistering acceleration of a Tesla, or the 1,000-horsepower and off-road wizardry of the upcoming Hummer, it’s the F-150’s secondary benefit that has the truck world buzzing: An ingenious mobile generator that can deliver up to 7.2 kilowatts of clean, continuous power.

Dubbed Pro Power Onboard, the system recruits hybrid hardware, including a 1.5-kWh, liquid-cooled lithium-ion battery below the cargo bed, and a 35-kilowatt (44 horsepower) motor/generator sandwiched between the 10-speed automatic transmission and twin-turbocharged, 3.5-liter gasoline V-6.

The hybrid powertrain generates 420 horsepower and a mighty 570 pound-feet of torque, enough to propel this roughly 5,850-pound truck to 60 mph in 5.3 seconds. That’s quicker than a Porsche Panamera V-6 sedan, and the Ford can also tow up to 12,700 pounds and haul 2,120 pounds in its cargo bed. To divert some of that electric muscle, Ford adds a power inverter that converts DC power to AC. A covered panel in the cargo bed integrates four 120-volt power outlets, plus a dedicated 240-volt circuit with a NEMA 30-amp twist-lock connector. Inside the passenger cab, 110-volt outlets peer from the front console and back seat.

Whether margarita-blending tailgaters, campers, or construction workers and other hands-on pros, truck fans have been discussing the toys, tools and even houses they might power with 7,200-watts of juice on hand.

“You can hook up your space heater, make your coffee and smores, connect a grille, a mini-fridge—it’s fun,” said Nigar Sultana, Ford’s Pro Power Onboard feature owner.

Ford has produced a chart showing potential uses, including simultaneously powering enough equipment for a construction crew to frame a house. A compound miter saw and circular saw, gang battery charger (for portable tool batteries), hammer drill, air compressor and flood lights would together draw about 7,000 watts. Mobile metal-shop workers could power a TIG welder, plasma cutter, chop saw, angle grinder, air compressor and work light. On the recreational side, beyond typical camping or tailgating gear, truck adventurers could charge a pair of electric dirt bikes and air compressor, with enough left over to griddle some burgers. Ford itself has used the F-150 to charge its Mustang Mach E electric crossover that goes on sale in December—the ouroboros of EV charging, but it can be done. During my test of a top-shelf, $74,000 F-150 Limited version, I plugged in a toaster oven and Bluetooth speaker, while hunting for friends with welders and other gear to give the system a better workout.

Sure, truck owners could do all that with a robust, portable gasoline generator. But Sultana says Pro Power Onboard is a more-elegant, integrated solution: A 5.5-kilowatt generator can weigh more than 200 pounds, takes up roughly 14 cubic feet or of valuable bed space (plus a gas canister for a refill), and is obnoxiously loud and polluting when it’s running. In addition, the F-150’s dedicated power electronics smooth out voltage ripples to produce a clean sine wave, allowing the truck to power laptops or other sensitive electronic equipment.

The truck’s lithium-ion battery supplies power until it’s depleted, at which point the gasoline engine starts up to generate electricity and top off the battery. Ford says the system can operate at maximum output for 32 hours on a full tank of gas, with the truck either in park or in motion. A Secure Idle function, familiar from Ford’s Police Interceptor models, allows the engine to idle while locking doors and the transmission to ensure no one can drive off with the running truck.

The Ford’s enormous, 12.0-inch center touchscreen shows power draw in watts for each of two circuits. The Ford Pass smartphone app monitors usage remotely or controls it within onboard Wifi range. Ground-fault detection shuts the system down if necessary, with a reset via the app or touchscreen.

To put that power in household terms, Ford says the system can power 28 average-size refrigerators. That odd metric aside, the Ford could clearly supply an electrical lifeline in case of power outages, saving a freezer full of steaks, keeping the lights (and widescreen TVs) running, and sparking envy in the darkened homes of neighbors. Energy regulations, Sultana says, prevent Ford from marketing that capability. But the idea of vehicle-to-home power, or vehicle-to-grid, has been in play for some time. That includes Nissan Leafs being used as mobile power backup after Japan’s 2011 earthquake. Companies are also floating bi-directional smart home systems to store grid energy in EVs, return it to homes during emergencies, or save money during peak usage periods.

Ford’s 7.2-kilowatt system adds $750 to models with the PowerBoost hybrid drivetrain. The automaker offers a less-robust 2.0-kilowatt system on non-hybrid models, or a standard 2.4-kilowatt unit for hybrid F-150’s. The hybrid tech itself adds a significant $1,900 to $4,495 to the F-150’s price, depending on the model. But a high-quality gas generator alone can cost more than $2,000, and does nothing to boost fuel economy or trim pollution for the truck itself.

With the F-150, Ram 1500 and Chevy Silverado routinely taking the top three spots in U.S. vehicle sales, pickup fans clearly don’t blink at lavish trucks whose average transaction price soared to $49,888 in 2019, more than $12,500 higher than the average ticket for all new cars. The coming crop of all-electric pickups, with the $112,595 Hummer Edition 1 expected to be first from the gate late next year, may kick those transaction prices even higher. With the F-150 PowerBoost, and electric trucks to come, we’ll see how many truck buyers are willing to pay a premium to cut energy costs and global-warming emissions—or just throw one hell of a tailgate party.

GM Opens Up a New Front in Its Battle With Tesla: Batteries

Post Syndicated from Lawrence Ulrich original https://spectrum.ieee.org/transportation/advanced-cars/gm-opens-up-a-new-front-in-its-battle-with-tesla-batteries

In April of 1966, a shiny white Chevrolet Impala became the first car off the assembly line of a new General Motors plant in Lordstown, Ohio. It was the glorious start of what became a checkered history for the area. This blue-collar town survived an infamous labor strike in 1972, the Chapter 11 bankruptcy of GM in 2009, and a string of unmemorable small cars—including the Chevy Vega and Cavalier—before emerging as a symbol of industrial rebirth with the production of the Chevy Cruze in 2010.

But things soon went to hell again, and GM shuttered the plant in 2019. Even then, the pain wasn’t over. The plant became a political football for President Trump, who urged local residents not to sell their homes, because of jobs he promised to restore. He later rebuked GM for not building COVID-19 ventilators in a factory it no longer owned. (By that time, GM had sold the mothballed plant to Lordstown Motors Corp., a long-shot electric-truck startup.)

Now, nine-lives Lordstown is getting another chance to play a significant role in the automotive future. Whether it succeeds hinges on the biggest multibillion-dollar question in the global auto industry: Can GM, or any legacy automaker for that matter, transform itself into a true rival to Tesla, whose electric cars—and sky-high stock price—dominate the EV space? To do that, it’ll need better, stronger, more-affordable batteries. That’s where GM’s Ultium project comes in.

Honoring its own promise to bring jobs back to northeast Ohio, GM, in partnership with South Korea’s LG Chem, has begun building a US $2.3 billion battery factory in Lordstown. This joint venture, called Ultium Cells, will have the capacity to produce at least 30 gigawatt-hours of batteries each year—50 percent more than can emerge from Tesla’s Gigafactory in Nevada. Huge as it is, that investment is just a small fraction of the $20 billion that GM will be pouring into electric and autonomous cars by 2025, en route to the “all-electric future” touted by the company’s CEO, Mary Barra.

GM’s plan calls for building 1 million EVs a year by mid-decade, for both U.S. and Chinese customers. The first Ultium-powered model, expected to be out late in 2021, will be a GMC Hummer pickup, reborn as an EV with up to 1,000 horsepower. Once the symbol of unrepentant gas-guzzling, the Hummer should now pass muster at any Silicon Valley cocktail party with its electric power train and zero tailpipe emissions.

This electric Hummer will roll out of a revamped $2.2 billion EV plant in Detroit—the vanguard for 20 new electric models bearing the marques of Chevrolet, Cadillac, and Buick by 2023. Slated also for production is the Cruise Origin, a self-driving, ride-sharing EV from GM’s autonomous-car subsidiary. And all of them will, of course, need battery packs.

The sprawling Lordstown battery plant, which will be big enough to encompass 30 football fields, is where GM aims to churn out 250 million Ultium cells a year by 2025. Those will be large-format pouch cells, a marked departure from the cylindrical-can cells Tesla and Panasonic produce for use in EVs.

Tesla originally packed 8,256 of its cylindrical “18650” cells (18 millimeters in diameter and 65 mm long) into the 100 kilowatt-hour versions of the Model S sedan and Model X SUV. These were only mildly reworked versions of the same Panasonic batteries found in many laptops—indeed, using off-the-shelf batteries was key to Tesla’s startup strategy. Yet the batteries have proven reliable in their new role, holding up well for many charge-discharge cycles.

To supply the latest Model 3 and Model Y, Tesla’s Gigafactory began producing the more energy-dense “2170” cell, which has 46 percent more volume than an 18650 but is still barely larger than an AA battery. A Model 3 with a 75-kWh battery holds 4,416 of these cells.

In September, Tesla announced plans to move eventually to a larger, “4680” cell, which will hold five times as much energy as the 2170 cell it will replace. GM is taking a bigger leap in that direction: Its large-format cells each contain about 20 times the energy of Tesla’s 2170 cell.

Each of GM’s large-format cells includes a stack of planar electrodes, which are immersed in a polymer electrolyte and wrapped in an aluminum-polymer pouch. Those cells can be stacked vertically or horizontally within scalable modules. A pack containing from 6 to 24 modules will provide between 50 and 200 kWh, depending on the vehicle. The 200-kWh version will become the largest available for any production EV, with double the storage of Tesla’s biggest pack.

GM’s 200-kWh pack contains two stacks of modules wired in series for a total of 800 volts, allowing 350-kilowatt fast charging, enough to extend range by something like 160 kilometers (100 miles) in just 10 minutes. That matches the Porsche Taycan’s industry-topping charge speeds. Single-stack, 400-V packs will permit charging at a still-robust rate of 200 kW. (The majority of Tesla’s Superchargers are limited to 150 kW.) And whatever the configuration, GM will be tracking the performance of its battery modules with a cloud-based monitoring system [see “EV Phone Home,” below].

How much better are these upcoming batteries and the ingenious architecture that supports them, which GM calls BEV3, compared with GM’s existing BEV2 models?

Consider the 2020 Bolt hatchback, built on the BEV2 platform. In my recent week-long test, the Bolt proved its ability to squeeze 417 km (259 miles) of range from a modest 66-kWh pack, up from 383 km in the previous version. That is similar to the 354 km of range for a standard Tesla Model 3 with a 50-kWh pack. But Tesla can manage 531 km from its longest-range Model 3, with 75 kWh aboard—and 647 km from its thriftiest Model S with 100 kWh of energy storage. GM had work to do to match or beat those statistics.

Tim Grewe, GM’s global director of electrification and battery systems, says that Ultium 1.0 batteries offer 60 percent more energy density than those found in the Bolt. And that’s just the start. “The Bolt had a great lithium-ion chemistry, but we had to take it to the next level,” Grewe says.

Doing so demanded a proprietary nickel cobalt manganese aluminum chemistry, one that reduces by 70 percent the amount of cobalt normally required, which is important because cobalt is the priciest element used in batteries and is often mined under inhumane conditions. Tesla is on a similar track toward low-cobalt cathodes for the cells destined for future Model 3 production in China. Rather than being cylindrical, those cells will be prismatic. But they will be packaged in aluminum housings instead of the laminate pouches used for GM’s cells. Both designs aim to maximize energy content in a given space, though pouch cells lead the industry at the moment, with 90 to 95 percent packaging efficiency.

Grewe describes the cathode in a lithium-ion cell as a “parking garage” for electric ions. The problem is that the cathode’s oxide structure begins to break down after thousands of charge-discharge cycles. Doping the cathode with aluminum can help avoid degradation, as does adding certain kinds of cladding to the structure, while also boosting thermal stability, “so all the parking spaces stay open,” Grewe says. He affirms that such measures put the industry’s much-discussed “million-mile battery” squarely in sight, a battery that will be especially valuable for the upcoming autonomous Cruise Origin EV.

Those Ultium 1.0 batteries are key to the forthcoming Hummer EV, the high-end version of which generates a shocking 1,000 horsepower from a trio of electric motors. This Hummer should combine a 3-second rip from 0 to 60 miles per hour (0 to 97 km per hour) with commando-worthy off-road skills—and still travel about 640 km (400 miles) on a charge.

GM says even its smallest and most-affordable new EVs will have ranges of at least 482 km (300 miles), despite having packs as small as 50 kWh, about 25 percent less energy than the current Bolt. “If you’re not getting at least 300 miles from a new EV architecture, you’re doing something wrong,” says Andy Oury, GM’s lead engineer for high-voltage battery packs.

It’s not all about range and performance, though. Price is key. Because battery packs are so expensive, legacy automakers continue to lose thousands of dollars on every EV they sell. Even Tesla’s minuscule profits have mainly come from selling emissions credits to rival automakers, not from selling cars.

GM is confident that the Ultium program will drive cell costs below $100/kWh, long the holy grail of battery development, hastening the day when EVs achieve price parity with fossil-fueled cars. But that’s still a ways off: Prices for Li-ion cells may have fallen by 87 percent since 2010, according to analysts at BloombergNEF, but remained a daunting $156/kWh in 2019.

“We haven’t seen the bottom of the cost curve,” Grewe says. Company executives estimate that battery costs are dropping 4 percent per year on average, with energy density rising by roughly the same amount. And GM has boldly announced that it will turn a profit on every Ultium-powered EV it sells.

Even as GM races to bring these new EVs to showrooms, the company is developing ways to produce even better batteries, some that contain zero cobalt and zero nickel. Much better performance could also be in store. At GM’s EV Week in March—where reporters were offered sneak peeks of 11 upcoming EVs—the company showed a working prototype of a lithium-metal cell, built at its Tech Center in suburban Detroit. That lithium-metal battery could provide nearly double the energy density of Ultium 1.0 cells—boosting driving range to 800 or more kilometers—if it could be made to perform reliably in the real world, which is still a big if.

Better batteries alone can’t guarantee success for GM or any other automaker looking to transition its fleet to electricity. They’ll also need to produce cars that people really want, in everything from design to technology.

The Chevrolet Bolt was a solid first step in that direction for GM back in 2016. But the Bolt never really caught on, arriving just as the United States was fleeing small cars for SUVs. So GM will reverse the Bolt’s self-effacing, Birkenstock approach with the decidedly in-your-face Hummer pickup (followed by the SUV), aimed at the same Silicon Valley Bro crowd that’s gone wild for Tesla’s prototype Cybertruck. GM plans to follow the Hummer with nearly 20 all-electric stablemates, including the Cadillac Lyriq SUV, a Caddy sedan, Chevrolet Silverado pickup, and crossovers from Chevy and Buick.

Tesla delivered about 367,000 cars in 2019, whereas GM sells 9 million around the world in a good year. But if you consider just electric vehicles, the tables turn: In the United States, GM sold just 16,400 Bolts in the last year, as Tesla raked in 223,000 enthusiastic customers for its all-electric lineup. GM must leverage its global scale and manufacturing know-how, if it intends to become a serious rival to Tesla.

To start, GM plans to simplify. Its full range of BEV3 offerings, from hulking all-wheel-drive pickups to perky front-drive crossovers, can be built with just 19 combinations of batteries and drivetrains. That compares with 550 combinations for GM’s internal-combustion portfolio.

The jigsaw commonalities of BEV3, paired with Ultium battery modules, will drive down cost and complexity, Oury says. The packs incorporate a load-bearing, crash-worthy structure, cooling, a high-current circuit, and electronic sensors—all in an elegant, space-saving design.

To give one example of how simplicity matters, previous GM packs had fiendishly complex cooling systems, some that grew out of hydrogen-fuel-cell development. Pricey, one-off components hogged space, such as the 150 cooling fins used in GM’s now discontinued Chevy Volt, a plug-in hybrid. At scale, that’s millions of parts that couldn’t be used on any other GM model, Oury said: “For even 100,000 vehicles, that’s 15 million fins per year, gone.”

In contrast, the Ultium battery modules integrate their own thermal management, “so each module brings along its own scalable cooling,” Oury says. An aluminum plate with thermally conductive adhesive connects cells to a high-strength steel “cold plate.” Pouch cells are “wrapped like a taco” to eliminate lower flanges, saving both cost and mass.

The single-height battery packs in most EVs require design compromises, Oury says. But GM can work around the usual constraints by being able to orient cells horizontally or vertically. That allows power-packed, double-stacked modules for beefy trucks, or slim, vertically oriented modules that boost range for lower-roofed cars without stealing passenger space.

Some Ultium-equipped EVs will squeeze 22 kWh below the rear-seat footwell alone, more than the plug-in Chevy Volt held in its entire pack. “We call it a multiheight battery pack, and it’s unique in the industry for these large-format cells,” Oury says of the seating-friendly arrangement.

GM’s $20 billion move to develop a giga-topping factory, unrivaled pack storage, and a line of 400-mile SUVs and pickups surely has Tesla’s attention. But that competition might well be seen as a good thing, given the company’s stated mission to spur the transition to sustainable energy. If so, Mr. Musk should be very happy this holiday season: GM has given him the gift of a serious rival. Batteries included.

This article appears in the December 2020 print issue as “GM Bets Big on Batteries.”

About the Author

Lawrence Ulrich, an award-winning automobile journalist, regularly writes about cars for many magazines, including IEEE Spectrum.