Formula E Charges GENBETA Prototype Race Car Using Regenerative Braking in Groundbreaking AI-powered Feat
In a remarkable demonstration of energy efficiency and AI-powered innovation, Formula E successfully charged its GENBETA prototype race car using only regenerative braking during a 1,000-vertical-meter mountain descent.
This achievement generated enough energy to complete a full lap of the iconic Circuit de Monaco, showcasing the potential of sustainable technologies in motorsports. This pioneering "Mountain Recharge" project, made possible through the collaboration with Google Cloud, leverages the Gemini API via Google AI Studio to analyze real-time data and optimize the energy recuperation process.
Formula E's race car, driven by Test Driver James Rossiter, descended the Col de Braus mountain road in free-wheel mode, relying solely on gravity and optimized braking to regenerate the energy needed to complete the 3.337 km Monaco lap.
The Role of Google Cloud's AI and Technology
Formula E teamed up with Google Cloud to optimize its "Mountain Recharge" challenge using AI. Google AI Studio analyzed variables like speed and gravity to refine braking and energy regeneration. BigQuery processed real-time car telemetry, Firebase powered the live dashboard, and NotebookLM streamlined collaboration by organizing technical and logistical data.
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Achieving Energy Regeneration through Braking
The challenge started with the GENBETA car having minimal energy for system power-up. However, by utilizing regenerative braking, the car generated 1.6 to 2.0 kWh of energy solely from the mountain descent. This energy was enough to complete the Monaco lap, equivalent to fully charging nearly 60 Google Pixel 9 Pro XL devices.
Guillaume Roques, Senior Director of EMEA Marketing at Google Cloud, said, "Google Cloud thrives on helping partners solve unique challenges with data and AI, and the 'Mountain Recharge' project is a fantastic demonstration of how AI can tackle complex, real-world challenges.”
He added. “Using our technologies, we were able to model the intricate physics of the descent and precisely calculate the regeneration potential. This isn't just about race cars; it's about how our AI capabilities can help any organization optimize for efficiency and sustainability by turning data into actionable insights."
This groundbreaking effort is part of Formula E's ongoing mission to demonstrate the significant energy efficiency of its vehicles.
As part of the race series, cars must regenerate around 40% of their required energy through braking during races. The "Mountain Recharge" project highlights this capability on a real-world scale, setting a new benchmark in energy optimization for the motorsports world.
