At Its El Segundo Innovation Lab, EVgo Tries to Predict the Future of Car Charging

Zac Estrada

Zac Estrada is a reporter covering transportation, technology and policy. A former reporter for The Verge and Jalopnik, his work has also appeared in Automobile Magazine, Autoweek, Pacific Standard, and BLAC Detroit. A native of Southern California, he is a graduate of Northeastern University in Boston. You can find him on Twitter at @zacestrada.

At Its El Segundo Innovation Lab, EVgo Tries to Predict the Future of Car Charging
The fastest electric car charging stations can replenish a battery from empty in about an hour. As carmakers from Volvo to Tesla race to make charges speedier and more powerful, the next 10 years mean added pressure on charging stations, from the plugs in homes to the stands at supermarkets.

But it's a delicate dance for the companies responsible for those chargers. Overheating and degradation has plagued some models over the last decade, and even Tesla has reduced the charging speed on some of its cars based on battery health and how often fast charging was used.

"The majority can't take more than a 50 kW per hour charging, and the charge rate doesn't stay at that and declines even more as the battery heats up," said Ivo Steklac, chief operations and technology officer of EVgo, one of the predominant electric vehicle charging companies in the U.S. "In order to manage this intelligently, we didn't think it was wise to dedicate this level of charger to vehicles when the majority of them can't take it."

With EV technology evolving at such a rapid clip, EVgo is grappling to make sure its charging stations are outfitted to handle the newest and most powerful electric cars. The company has been pouring resources into figuring out not only where and how many chargers should be placed across the country, but also issues that users might face when pulling up to a station to get some juice for their car. In April it opened a 4,000 square-foot Innovation Lab in El Segundo.

Engineers there are trying to work out a number of hardware, software and logistics problems — some of which exist now, and some that might become apparent later, as batteries get bigger and vehicles can charge more quickly to eventually replace the lines at gas stations.

EVgo, which went public July 2 after an SPAC merger with Climate Change Crisis Real Impact I Acquisition Corp. now has more than 800 chargers dotted across the U.S. as the Biden administration tries to jumpstart an electric vehicle revolution. But the market share remains small as Americans groan about range and access to car chargers.

"We created this lab to do a number of tests, from electric to physical and mechanical," said Steklac. "EV manufacturers are placing their charging ports in all sorts of places on the cars so they can reduce the length of wiring for these very high-powered cables."

It follows, then, that one of EVgo's tests at the lab includes a cable reach analysis to figure out not only an acceptable length for a charging cable, but also a manageable weight for not only the average driver, but shorter people or those with disabilities. EVgo wants to banish problems like pulling up to a gas pump when the car's fuel door is on the opposite side.

EVgo's lab engineers are also busy considering EV charging times. When the company was first installing chargers a decade ago, a charging rate of 50 kilowatts per hour was considered more than sufficient for drivers. Today's Tesla's Superchargers have a 120 kWh rate, while Volkswagen-owned Electrify America is building stations with 350 kWh-capable chargers. But only a few EVs on sale now can handle that charge rate, so Steklac said its chargers have to allow for significant disparities between vehicles.

Similarly, EVgo is looking at how extensive fast charging affects the longevity of an EV's battery pack.

"The majority (of models) can't take more than a 50 kW per hour charging, and the charge rate doesn't stay at that and declines even more as the battery heats up," Steklac said. "In order to manage this intelligently, we didn't think it was wise to dedicate this level of charger to vehicles when the majority of them can't take it."

Steklac said designing the next generation of chargers to go with the next generation of electric vehicles is becoming important as the market becomes less of a niche. EVgo's CEO Cathy Zoi said during the company's Wall Street debut that the EV market in the United States is estimated to grow from just over 1% share of the passenger car segment in 2020 to more than 10% by 2030, just before state mandates like California's go into effect for new vehicle sales.

Even without the Biden administration's 500,000 EV charger pledge, Steklac believes there needs to be 50,000 stations just to support the existing market. And that doesn't even include commercial vehicles, ride sharing services like Uber and Lyft or buses and postal delivery vans that are high on the White House's list to electrify.

EVgo's automaker partnerships currently extend to General Motors and Nissan, both of which sell EVs in the U.S., and are about to introduce new, longer-range models. The charging company touts its network as the largest for fast chargers in the country, with 800 stations across 34 states.

In California, Steklac said electric car hotbeds Los Angeles, San Diego and the San Francisco Bay areas are well-served, but acknowledges there are gaps in the infrastructure. He said the innovation lab uses an algorithm and purchase data to determine where EV owners live to determine where to put new charging stations.

Shopping and entertainment centers are EVgo's target for fast charging hubs right now. Kroger and Whole Foods are among its grocery store partners, too.

"The average American goes to the grocery store twice a week and spends 30 to 45 minutes there," Steklac said. "We target those, we target pharmacies, fast casual restaurants where you spend an hour or less. These include malls and parking garages, particularly in urban areas."

Steklac said the company is also talking with regional transit agencies, as well as Amtrak where there are EVgo charging stations at Washington, D.C.'s Union Station, because he said the mentality is still to "partner with anyone and everyone" in this still-early EV era.

Because while automakers and analysts expect home stations to be the way most EV owners will charge their vehicles in the long term, Steklac said that won't be the solution for every household and won't allow for the electrification of vehicles as quickly as lawmakers want. That's why the teams at the Innovation Lab have plenty of work to do over the next decade.

"Public charging is there to augment if you have home charging, but it's there to be a reliable source if you don't," Steklac said.

Subscribe to our newsletter to catch every headline.

Creandum’s Carl Fritjofsson on the Differences Between the Startup Ecosystem in Europe and the U.S.

Decerry Donato

Decerry Donato is a reporter at dot.LA. Prior to that, she was an editorial fellow at the company. Decerry received her bachelor's degree in literary journalism from the University of California, Irvine. She continues to write stories to inform the community about issues or events that take place in the L.A. area. On the weekends, she can be found hiking in the Angeles National forest or sifting through racks at your local thrift store.

Carl Fritjofsson
Carl Fritjofsson

On this episode of the LA Venture podcast, Creandum General Partner Carl Fritjofsson talks about his venture journey, why Generative-AI represents an opportunity to rethink products from the ground up, and why Q4 2023 and Q1 2024 could be "pretty bloody" for startups.

Read moreShow less

AI Is Rapidly Advancing, but the Question Is, Can We Keep Up?

Lon Harris
Lon Harris is a contributor to dot.LA. His work has also appeared on ScreenJunkies, RottenTomatoes and Inside Streaming.
AI Is Rapidly Advancing, but the Question Is, Can We Keep Up?
Evan Xie

One way to measure just how white-hot AI development has become: the world is running out of the advanced graphics chips necessary to power AI programs. While Intel central processing units were once the most sought-after industry leaders, advanced graphics chips like Nvidia’s are designed to run multiple computations simultaneously, a baseline necessity for many AI models.

An early version of ChatGPT required around 10,000 graphics chips to run. By some estimates, newer updates require 3-5 times that amount of processing power. As a result of this skyrocketing demand, shares of Nvidia have jumped 165% so far this year.

Building on this momentum, this week, Nvidia revealed a line-up of new AI-related projects including an Israeli supercomputer project and a platform utilizing AI to help video game developers. For smaller companies and startups, however, getting access to the vital underlying technology that powers AI development is already becoming less about meritocracy and more about “who you know.” According to the Wall Street Journal, Elon Musk scooped up a valuable share of server space from Oracle this year before anyone else got a crack at it for his new OpenAI rival, X.AI.

The massive demand for Nvidia-style chips has also created a lucrative secondary market, where smaller companies and startups are often outbid by larger and more established rivals. One startup founder compares the fevered crush of the current chip marketplace to toilet paper in the early days of the pandemic. For those companies that don’t get access to the most powerful chips or enough server space in the cloud, often the only remaining option is to simplify their AI models, so they can run more efficiently.

Beyond just the design of new AI products, we’re also at a key moment for users and consumers, who are still figuring out what sorts of applications are ideal for AI and which ones are less effective, or potentially even unethical or dangerous. There’s now mounting evidence that the hype around some of these AI tools is reaching a lot further than the warnings about its drawbacks.

JP Morgan Chase is training a new AI chatbot to help customers choose financial securities and stocks, known as IndexGPT. For now, they insist that it’s purely supplemental, designed to advise and not replace money managers, but it may just be a matter of time before job losses begin to hit financial planners along with everyone else.

A lawyer in New York just this week was busted by a judge for using ChatGPT as part of his background research. When questioned by the judge, lawyer Peter LoDuco revealed that he’d farmed out some research to a colleague, Steven A. Schwartz, who had consulted with ChatGPT on the case. Schwartz was apparently unaware that the AI chatbot was able to lie – transcripts even show him questioning ChatGPT’s responses and the bot assuring him that these were, in fact, real cases and citations.

New research by Marucie Jakesch, a doctoral student from Cornell University, suggests that even users who are more aware than Schwartz about how AI works and its limitations may still be impacted in subtle and subconscious ways by its output.

Not to mention, according to data from, high school and college students already – on the whole – prefer utilizing ChatGPT for help with schoolwork over a human tutor. The survey also notes that advanced students tend to report getting more out of using ChatGPT-type programs than beginners, likely because they have more baseline knowledge and can construct better and more informative prompts.

But therein lies the big drawback to using ChatGPT and other AI tools for education. At least so far, they’re reliant on the end user writing good prompts and having some sense about how to organize a lesson plan for themselves. Human tutors, on the other hand, have a lot of personal experience in these kinds of areas. Someone who instructs others in foreign languages professionally probably has a good inherent sense of when you need to focus on expanding your vocabulary vs. drilling certain kinds of verb and tense conjugations. They’ve helped many other students prepare for tests, quizzes, and real-world challenges, while computer software can only guess at what kinds of scenarios its proteges will face.

A recent Forbes editorial by academic Thomas Davenport suggests that, while AI is getting all the hype right now, other forms of computing or machine learning are still going to be more effective for a lot of basic tasks. From a marketing perspective in 2023, it’s helpful for a tech company to throw the “AI” brand around, but it’s not magically going to be the answer for every problem.

Davenport points to a similar (if smaller) whirlwind of excitement around IBM’s “Watson” in the early 2010s, when it was famously able to take out human “Jeopardy!’ champions. It turns out, Watson was a general knowledge engine, really best suited for jobs like playing “Jeopardy.” But after the software gained celebrity status, people tried to use it for all sorts of advanced applications, like designing cancer drugs or providing investment advice. Today, few people turn to Watson for these kinds of solutions. It’s just the wrong tool for the job. In that same way, Davenport suggests that generative AI is in danger of being misapplied.

While the industry and end users both race to solve the AI puzzle in real time, governments are also feeling pressure to step in and potentially regulate the AI industry. This is much easier said than done, though, as politicians face the same kinds of questions and uncertainty as everyone else.

OpenAI CEO Sam Altman has been calling for governments to begin regulating AI, but just this week, he suggested that the company might pull out of the European Union entirely if the regulations were too onerous. Specifically, Altman worries that attempts to narrow what kinds of data can be used to train AI systems – specifically blocking copyrighted material – might well prove impossible. “If we can comply, we will, and if we can’t, we’ll cease operating,” Altman told Time. “We will try, but there are technical limits to what’s possible.” (Altman has already started walking this threat back, suggesting he has no immediate plans to exit the EU.)

In the US, The White House has been working on a “Blueprint for an AI Bill of Rights,” but it’s non-binding, just a collection of largely vague suggestions. It’s one thing to agree “consumers shouldn’t face discrimination from an algorithm” and “everyone should be protected from abusive data practices and have agency over how their data is used.” But enforcement is an entirely different animal. A lot of these issues already exist in tech, and are much larger than AI, and the US government already doesn’t do much about them.

Additionally, it’s possible AI regulations won’t work well at all if they aren’t global. Even if you set some policies and get an entire nation’s government to agree, how to set similar worldwide protocols? What if US and Europe agree but India doesn’t? Everyone around the world accesses roughly the same internet, so without any kind of international standard, it’s going to be much harder for individual nations to enforce specific rules. As with so many other AI developments, there’s inherent danger in patchwork regulations; it could allow some companies, or regions, or players to move forward while others are unfairly or ineffectively stymied or held back.

The same kinds of socio-economic concerns around AI that we have nationally – some sectors of the work force left behind, the wealthiest and most established players coming in to the new market with massive advantages, the rapid spread of misinformation – are all, in actuality, global concerns. Just as the hegemony of Microsoft and Google threaten the ability of new players to enter the AI space, the West’s early dominance of AI tech threatens to push out companies and innovations from emerging markets like Southeast Asia, Subsaharan Africa, and Central America. Left unfettered, AI could potentially deepen social, economic, and digital divisions both within and between all of these societies.

Undaunted, some governments aren’t waiting around for these tools to develop any further before they start attempting to regulate them. New York City has already set up some rules about how AI can be used during the hiring process while will take effect in July. The law requires any company using AI software in hiring to notify candidates that it’s being used, and to have independent auditors check the system annually for bias.

This sort of piecemeal figure-it-out-as-we-go approach is probably what’s going to be necessary, at least short-term, as AI development shows zero signs of slowing down or stopping any time soon. Though there’s some disagreement among experts, most analysts agree with Wharton professor and economist Jeremy Siegel, who told CNBC this week that AI is not yet a bubble. He pointed to the Nvidia earnings as a sign the market remains healthy and not overly frothy. So, at least for now, the feverish excitement around AI is not going to burst like a late ‘90s startup stock. The world needs to prepare as if this technology is going to be with us for a while.

What the Future of Rivian Looks Like According to CEO RJ Scaringe

David Shultz

David Shultz reports on clean technology and electric vehicles, among other industries, for dot.LA. His writing has appeared in The Atlantic, Outside, Nautilus and many other publications.

What the Future of Rivian Looks Like According to CEO RJ Scaringe

Rivian CEO RJ Scaringe took to Instagram last weekend to answer questions from the public about his company and its future. Topics covered included new colors, sustainability, production ramp, new products and features. Speaking of which, viewers also got a first look at the company’s much-anticipated R2 platform, albeit made of clay and covered by a sheet, but hey, that’s…something. If you don’t want to watch the whole 33 minute video, which is now also on Youtube, we’ve got the highlights for you.

Read moreShow less