Capgemini has launched a research collaboration with the Chair of Electrical Energy Storage Technology at the Technical University of Munich(TUM) to develop Artificial Intelligence solutions to optimise sustainable advanced virtual battery design.
Electric mobility and vehicles are key elements to aid the fight against climate change, but battery design and related management systems remain a challenge for the industry. In particular, performance, cost, ageing and safety optimisation of battery cell systems remain a crucial area of research. A better understanding, modelling, and simulation of the physical properties of battery cells will significantly improve their performance while reducing the time and costs associated with sustainable battery research.
This new research programme is part of Capgemini’s Strategic University Programme, a key initiative with the primary objective to co-invest with world-class universities to produce high-quality research outputs that contribute to answering the question, “What are the key challenges of a more intelligent industry in our society?” These deeply collaborative projects, where Capgemini experts work alongside leading academics, aim to contribute to the advancement of engineering in a three-to-five-year research horizon. They are designed to harness the power of technology and enhance capabilities in Intelligent Industry.
The collaboration between Capgemini and TUM will focus on developing AI-based parameter simulations for lithium-ion battery systems. The purpose will be to speed up and optimise battery design to improve product performance significantly: modelling and simulating electrochemical-thermal couplings, identifying the right materials, and reducing the use of materials, all to help ensure the best cell design and integration in battery packs.
Dr Andreas Jossen, Head of Chair of Electrical Energy Storage Technology, TUM, said, “Advanced battery models in combination with AI and optimised control enable a cost-, age-, and safety-optimised operation of lithium-ion batteries. Most challenging and time consuming is the parameter identification for these models. The non-invasive parameter identification methods we develop through this new collaboration have the potential to reduce time and effort drastically and enable us to use advanced battery models within highly optimised battery applications.”
William Rozé, CEO, Capgemini Engineering and Group Executive Board Member, noted, “It is essential to accelerate sustainable battery design to develop electric mobility. Thanks to this new collaboration and our expertise in batteries, AI and multi-physics simulation, we are aiming to create advanced engineering designs, a key lever to reach sustainability objectives.”
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