
First AI-enabled battery management system
Eatron Technologies and About:Energy are to develop an AI-powered decision-engine for battery management systems (BMS).
The aiMAGINE project aims to use machine learning frameworks in the BMS to deliver extended battery lifetimes, ease of integration, and reduced time-to-market
Current battery management systems (BMS) rely on simple, empirical methods that sacrifice accuracy in return for reduced computational effort. Conventional AI-powered methods, meanwhile, remain challenging to integrate within the BMS due to their complexity, demanding training process, and the need for large volumes of input data.
The aiMAGINE project combines About:Energy’s high-fidelity electrochemical battery models developed in the UK that achieve rapid and accurate calibration with Eatron’s edge and AI-powered cloud platform. This should provide more accurate assessments of state-of-charge (SoC), state-of-health (SoH) and patented remaining useful life (RUL) predictions.
- Too little, too late for UK battery strategy
- About:Energy raises £1.5m for battery data tool
- Battery design platform is technology agnostic
AI complements the electrochemical models, enhancing predictions by accounting for complex physical behaviours that cannot be modelled. As a result, the AI-powered decision engine (AI-DE) will provide highly accurate operational parameters to the BMS, significantly increasing battery pack longevity and simplifying integration.
“Implementing our novel AI-powered intelligent battery software layer with this revolutionary AI-DE can extend a battery pack’s first life by up to 20%,” said Dr Umut Genc, CEO of Eatron (above, left). “This makes it possible for OEMs to design optimally-sized, more cost-effective battery packs, and this actively contributes to our sustainable e-mobility goals by reducing raw material consumption and CO2 emissions.”
- WAE launches digital twin and BMS software for EVs
- CEO interview: Dukosi ramps up for volume wireless BMS .
“The use of our advanced electrochemical models vastly streamlines AI model training, and this facilitates both ease of integration and a reduced time-to-market for OEMs and Tier 1s,” said Dr Kieran O’Regan, Co-Founder and COO of About:Energy (above, right). “The high-fidelity modelling reduces the need for physical experiments while delivering a clearer, more accurate picture of battery health. Armed with this information, an AI-DE-equipped BMS can deliver not just a longer battery lifetime, but faster charging times, too.”
Eatron and About:Energy will use their existing relationships with OEMs and Tier 1 suppliers to develop the system for use in both 2- and 4-wheeled electric vehicles.
www.eatron.com; www.aboutenergy.io
