New York, N.Y. (WENY) - As Formula E prepares for the New York City E-Prix this weekend, one team is using a unique partnership to optimize racing performance and model sustainability. 

Envision Racing was the first Formula E team to be certified carbon-neutral by the Carbon Trust in 2020. The team has partnered with Genpact, a global professional services firm focused on delivering digital transformation, to not only provide track insights but to report on sustainability goals. Genpact has built a carbon calculator that uses AI and analytics to help the team make greener travel decisions. 

Jennifer Babington, the operations director and general counsel at Envision Racing, explained that Genpact's contribution exists far beyond the track. 

“By embedding automation into our carbon reporting process, Genpact not only improved speed and accuracy but also made the approach user-friendly so we can easily access insight into our carbon consumption and offset data, helping us continuously make choices that have a lasting impact on our communities and planet,” Babington said. 

To propel the team to race success, Genpact created a simulator that uses data analytics to recreate the track conditions of each race. Sanjay Srivastava is the Chief Digital Strategist at Genpact. He said the data that goes into the simulator is what drives optimal racing performance. 

"We're actually putting the same computer that is sitting in the racecar in the simulator and you're getting the driver to experience it and go through a practice of being on the track," Srivastava said. "You have to map the track, you have to use radar images of bumps in the road so to say. And you want to represent that in a simulator so that as you're taking a turn around the corner, you're getting the same vibration in the steering wheel and the same impact. The better you can do that, the better you're going to be at the actual race." 

The biggest difference between Formula E racing and Formula 1 racing is, of course, the car's engine type. Formula E cars are battery-powered, and the way in which the battery is used throughout the trace is largely informed by AI. 

"The whole thing is about battery performance and efficiency," Srivastava said. "So you have to know how much battery you have left. And more importantly, not the battery, but the conditions you're driving, in the way that you're driving, and the way that the other teams are driving, how much distance can you go?

What you don't want to do is end the race with 25 percent battery remaining, because that means you haven't really pushed yourself. Equally, on the other hand, you can't end the race by sort of stopping a few feet short of where you need to go because you ran out of battery power. So getting that right is so critical. You can just imagine the fractional difference between how you estimate that and its resulting performance implications is massive. So really, data and AI are key, if you will, to winning this race."