Blab Tech
Formula Es Gen 4 Race Cars Turn to Artificial Intelligence for Performance Gains
The roar of Formula E is about to be replaced by a whisper of data.
When the 2026‑27 season opens, the grid will be dominated by the brand‑new Gen 4 electric race cars. Beyond a slick chassis and a power‑train that can flash‑charge at 600 kW, the biggest upgrade comes from software: artificial intelligence will be the engine that drives strategy and energy management.
Dan Cherowbrier, the championship’s chief technology officer, calls the shift “the biggest thing to happen to our industry since the birth of the Internet.” He warned that even a modest slice of the hype could be “game‑changing” for how teams operate. The new cars will feature permanent all‑wheel drive, a rear wing that can switch between two aerodynamic configurations, and a battery that can accept the full 600 kW charge. Those hardware changes are impressive, but the real competitive edge lies in AI that predicts and optimises power use in real time.
Historically, Formula E’s advantage came from hardware efficiency. Jaguar TCS Racing’s principal, Ian James, notes that modern electric motors and batteries now hit 91.5 % drivetrain efficiency. That level of performance has compressed the gap between suppliers, making software the new differentiator. James said, “This means that there’s a lot more focus now on the software as the performance differentiator.” The same trend is visible in the consumer market, where Tesla, Rivian, XPENG, NIO and Volvo compete on digital experiences as much as on horsepower or battery size.
ABB, the championship’s long‑standing sponsor, plays a dual role. It supplies the BrightLoop DC‑to‑DC converter that manages power flow between the battery and the car’s electrical systems. Cherowbrier explained that the converter must deliver the right amount of power at the right moment, a requirement that demands precise timing. ABB’s involvement gives the company a “living laboratory” where new electrification technologies can be tested under extreme racing conditions before being adapted for commercial use.
ABB also supplies the charging infrastructure that can recharge up to 20 Formula E cars simultaneously during sessions. The system uses buffer batteries and load‑balancing techniques similar to those employed at busy public charging stations, and the knowledge gained from this work is expected to inform ABB’s commercial charger installations.
Beyond hardware, Formula E is experimenting with AI in several arenas. The championship has teamed with Google and ABB to develop AI‑driven broadcast features that predict race events in real time, offering viewers insights rather than only post‑race analysis. Cherowbrier highlighted that the shift from explanatory to predictive analytics is a fundamental change for both motorsport and road cars.
FIA technical engineering director Thomas Chevaucher emphasised that understanding how energy is used can be more valuable than the hardware itself. He said, “There is a technology aspect, including the battery, efficiency of the motors and so on, but a very important part is the way you are driving it.” Formula E’s emphasis on balancing speed with energy consumption mirrors the challenges faced by electric vehicles on the road, where drivers must consider traffic, weather and charging infrastructure.
Simulation and digital twins are another area where Formula E leads. Jaguar TCS Racing works with Tata Consultancy Services to create the Virtual Vehicle Validation Model (V3M), a high‑fidelity digital twin that models vehicle behaviour before a race weekend and refines predictions after each lap. The system downloads data at the end of each race, allowing engineers to adjust strategies for the next event. The automotive industry increasingly uses similar digital twin technologies to design and validate software and battery systems before physical prototypes are built.
Mahindra Racing’s CEO and team principal Frédéric Bertrand noted that AI can filter the vast amounts of data generated by modern vehicles. He said, “AI helps a lot with this, because you can have an initial management of the data, which just eliminates all the noise around the real topic.” As vehicles become more connected and autonomous, the ability to identify relevant patterns will become more critical.
Former Formula E champion Lucas di Grassi, who has long explored AI in racing through the autonomous Roborace project, believes AI can help teams optimise energy management, accelerate development and improve strategy. Di Grassi said, “There is the AI implementation into the sport… It could eventually help teams optimise energy management, accelerate development, improve strategy, and process information more efficiently.” He added that motorsport remains fundamentally human, but AI can act as a coach or assistant.
In short, the Gen 4 era of Formula E is about smarter, not just faster, cars. The championship is becoming a laboratory for energy intelligence, using AI, predictive analytics and digital twins to manage power, strategy and data. The lessons learned on the track are already influencing the design of road‑legal electric vehicles, where software that can anticipate and adapt to driving conditions may become the next major performance differentiator.
The 2026‑27 season will bring the first Gen 4 cars to the grid, and the industry will watch closely to see how AI‑driven energy management translates from the racetrack to the consumer market.
When the 2026‑27 season opens, the grid will be dominated by the brand‑new Gen 4 electric race cars. Beyond a slick chassis and a power‑train that can flash‑charge at 600 kW, the biggest upgrade comes from software: artificial intelligence will be the engine that drives strategy and energy management.
Dan Cherowbrier, the championship’s chief technology officer, calls the shift “the biggest thing to happen to our industry since the birth of the Internet.” He warned that even a modest slice of the hype could be “game‑changing” for how teams operate. The new cars will feature permanent all‑wheel drive, a rear wing that can switch between two aerodynamic configurations, and a battery that can accept the full 600 kW charge. Those hardware changes are impressive, but the real competitive edge lies in AI that predicts and optimises power use in real time.
Historically, Formula E’s advantage came from hardware efficiency. Jaguar TCS Racing’s principal, Ian James, notes that modern electric motors and batteries now hit 91.5 % drivetrain efficiency. That level of performance has compressed the gap between suppliers, making software the new differentiator. James said, “This means that there’s a lot more focus now on the software as the performance differentiator.” The same trend is visible in the consumer market, where Tesla, Rivian, XPENG, NIO and Volvo compete on digital experiences as much as on horsepower or battery size.
ABB, the championship’s long‑standing sponsor, plays a dual role. It supplies the BrightLoop DC‑to‑DC converter that manages power flow between the battery and the car’s electrical systems. Cherowbrier explained that the converter must deliver the right amount of power at the right moment, a requirement that demands precise timing. ABB’s involvement gives the company a “living laboratory” where new electrification technologies can be tested under extreme racing conditions before being adapted for commercial use.
ABB also supplies the charging infrastructure that can recharge up to 20 Formula E cars simultaneously during sessions. The system uses buffer batteries and load‑balancing techniques similar to those employed at busy public charging stations, and the knowledge gained from this work is expected to inform ABB’s commercial charger installations.
Beyond hardware, Formula E is experimenting with AI in several arenas. The championship has teamed with Google and ABB to develop AI‑driven broadcast features that predict race events in real time, offering viewers insights rather than only post‑race analysis. Cherowbrier highlighted that the shift from explanatory to predictive analytics is a fundamental change for both motorsport and road cars.
FIA technical engineering director Thomas Chevaucher emphasised that understanding how energy is used can be more valuable than the hardware itself. He said, “There is a technology aspect, including the battery, efficiency of the motors and so on, but a very important part is the way you are driving it.” Formula E’s emphasis on balancing speed with energy consumption mirrors the challenges faced by electric vehicles on the road, where drivers must consider traffic, weather and charging infrastructure.
Simulation and digital twins are another area where Formula E leads. Jaguar TCS Racing works with Tata Consultancy Services to create the Virtual Vehicle Validation Model (V3M), a high‑fidelity digital twin that models vehicle behaviour before a race weekend and refines predictions after each lap. The system downloads data at the end of each race, allowing engineers to adjust strategies for the next event. The automotive industry increasingly uses similar digital twin technologies to design and validate software and battery systems before physical prototypes are built.
Mahindra Racing’s CEO and team principal Frédéric Bertrand noted that AI can filter the vast amounts of data generated by modern vehicles. He said, “AI helps a lot with this, because you can have an initial management of the data, which just eliminates all the noise around the real topic.” As vehicles become more connected and autonomous, the ability to identify relevant patterns will become more critical.
Former Formula E champion Lucas di Grassi, who has long explored AI in racing through the autonomous Roborace project, believes AI can help teams optimise energy management, accelerate development and improve strategy. Di Grassi said, “There is the AI implementation into the sport… It could eventually help teams optimise energy management, accelerate development, improve strategy, and process information more efficiently.” He added that motorsport remains fundamentally human, but AI can act as a coach or assistant.
In short, the Gen 4 era of Formula E is about smarter, not just faster, cars. The championship is becoming a laboratory for energy intelligence, using AI, predictive analytics and digital twins to manage power, strategy and data. The lessons learned on the track are already influencing the design of road‑legal electric vehicles, where software that can anticipate and adapt to driving conditions may become the next major performance differentiator.
The 2026‑27 season will bring the first Gen 4 cars to the grid, and the industry will watch closely to see how AI‑driven energy management translates from the racetrack to the consumer market.
