Battery lifespan project takes shape in the UK
The battery analytics specialist Silver Power System partnered with Imperial College, London EV Company (LEVC) and JSCA, the research and development division of Watt Electric Vehicle Company, on an electric vehicle battery research programme designed to predict battery lifespan.
The project will make use of digital twin technology, which simulates a digital counterpart to a real-world system. Funding was partially awarded by the Advanced Propulsion Centre, enabling the Real-Time Electrical Digital Twin Operating Platform (REDTOP) project to create and trial digital twins of real EV batteries.
Data is critical for a digital twin, in order for the computer system to properly understand how its’ real world counterpart interacts with its environment. The data for this project was taken from a 500,000 km-spanning, nine month on-road trial of 50 LEVC TX battery-electric taxis and an EV sports car from the Watt EV Company. The designers now promise the “highly sophisticated algorithms unlock an unprecedented view of battery performance and state-of-health”.
“Understanding how an electric vehicle’s battery is performing right now – and predicting how it will perform over the coming years – is absolutely critical for many sectors. But to date there has been a lack of data and predictive modelling has been largely lab-based,” said Pete Bishop, CTO of Silver Power Systems, adding: “By combining a robust real-world trial with our EV-OPS machine-learning analytics capability through the REDTOP programme, we have not only been able to unlock an unprecedented view of real-time battery performance and state-of-health but also create the world’s most advanced digital twin enabling prediction of battery future life.”
Liam Mifsud, Program Manager, Silver Power Systems added: “On top of using a combination of real-world data, machine learning and the digital twin to predict future battery degradation, we can use this technology to update an EV’s software via the cloud to change algorithms or parameters to optimise the performance of the battery as the cells age and maximise battery life.”