Sign up today to get the best of our expert insight in your inbox.
How to optimize EV battery research and development
Transforming EV battery development through the power of AI
David Banmiller
Head of Americas Sales and host of The Interchange Recharged
![](https://www.woodmac.com/siteassets/photography---our-people/david-banmiller_web.jpg?w=600&h=360&mode=crop¢er=0.5,0.5)
David Banmiller
Head of Americas Sales and host of The Interchange Recharged
David manages the Global Strategic Banking team and hosts The Interchange Recharged
Latest articles by David
-
Opinion
American competitiveness in the energy sector: the DOE’s ARPA-E department is focusing on advanced nuclear
-
Opinion
Out with lithium and nickel, in with salt and bricks?
-
Opinion
Distributed energy storage is taking off
-
Opinion
The evolution of the solar industry in the US since 2021
-
Opinion
Demand for solar power and energy storage is only going to increase. What’s the plan for meeting it?
-
Opinion
Two years on from the IRA and the impact on solar and storage is clear
The traditional process of battery development is slow, expensive, and capital-intensive. AI can help overcome the challenges of predicting battery performance, exploring the vast design space, and conducting time-consuming cycle life testing. David Banmiller is joined by Alán Aspuru-Guzik, a professor at the University of Toronto specializing in Chemistry and Computer Science, and Jason Koeller, the CTO and Co-founder of Chemix, to examine the role of machine learning in EV battery development.
Chemix is exploring new ways of developing batteries for electric vehicles (EVs) by utilizing AI, aiming to make it faster and more efficient compared to the traditional, slower, and costlier methods. AI not only speeds up the development process by predicting performance and exploring design options, but also – as Professor Aspuru-Guzik explains - leads to innovative battery compositions that improve performance. The machines can do calculations in timeframes inconceivable for a human.
There are wide-ranging applications for AI in areas beyond battery development, including grid optimization and materials design. Professor Aspuru-Guzik shares insights into the work of the Acceleration Consortium, which aims to be a leading hub for AI-driven scientific advancements in various sectors. Jason addresses some of the practical challenges in the EV industry, such as the need for adaptable battery solutions and the hurdles in introducing new manufacturing technologies. Technological advancement in battery technology and charging infrastructure are progressing together, enabling growth in the EV market.
Subscribe to the Interchange Recharged so you don’t miss an episode on Apple Podcasts or Spotify. Find us on X – we’re @interchangeshow