Advanced digital twin for predicting battery life

September 21, 2021 // By Nick Flaherty
Battery digital twin for predicting battery life
A battery digital twin has been built by Silver Power Systems in the UK as part of the REDTOP project using 500,000km of real world data over the last nine months

Battery analytics specialist Silver Power System (SPS) in Swindon has teamed up with Imperial College, London EV Company and JSCA, the research and development division of the Watt Electric Vehicle Company, on a digital twin to predict battery lifespan.

The Real-Time Electrical Digital Twin Operating Platform (REDTOP) project has created and tested a complex digital twin of real EV batteries using data from a nine month, 500,000km trial. This used 50 LEVC TX taxis and a new EV sports car from the Watt EV Company. This real world data makes it the most advanced digital twin system currently available, says SPS.

Each vehicle was fitted with a data-collection IoT device linked to the SPS cloud-based software. This data has been analysed by SPS’s machine learning-powered platform EV-OPS, and together with Imperial College’s battery researchers, the digital twin of the  EV batteries was created. This gives a real time view of the battery performance and state-of-health with the potential to predict battery lifespan.

“This really is the holy grail,” said Pete Bishop, CTO of Silver Power Systems. “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."

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“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,” said Bishop.

“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. For all automotive sectors the potential to improve battery performance and overall useable life is revolutionary,” said Liam Mifsud, Program Manager, Silver Power Systems.

For electric vehicle manufacturers this monitoring capability gives insights into battery performance enabling them to accelerate the development of battery-powered vehicles. OEMs and battery manufacturers can use the technology to enable more accurately underwritten battery warranties, setting warranties on a new battery or managing risk on existing battery, while other sectors who can benefit include insurance providers, transport authorities, councils and even private EV owners for whom having access to data on their own vehicle’s battery performance is beneficial.

Fleet operators can gain a complete picture of EV health across a vehicle fleet enabling them to more efficiently run their vehicles and potentially extend the the life of the vehicles, while fleet owners can use SPS’s capabilities to predict the future residual value of vehicles based on future battery health. As the market transitions to EVs, this is set to become of ever-increasing importance.

In the future, SPS sees the opportunity to digitally optimise EV batteries during their life.

www.ev-ops.com; www.silverpowersystems.com

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