Silver Power Systems uses digital twin to predict battery lifespan

Battery analytics specialist Silver Power System (SPS) has partnered with Imperial College, the London EV Company and the Watt Electric Vehicle Company on a research program designed to predict battery lifespan.

The Real-Time Electrical Digital Twin Operating Platform (REDTOP) project has created and trialed “digital twins” of real EV batteries. Built using data from a 500,000-km/9-month on-road trial of 50 LEVC TX taxis and an electric sports car from Watt, the algorithms offer a view of battery performance and state of health. SPS says that, combined with the company’s analytics capabilities, this digital twin concept can be applied to any EV battery to predict lifespan.

Various companies, including OEMs, battery manufacturers and fleet operators, have an interest in determining how a particular battery is performing, and predicting how much it is likely to degrade over the vehicle’s lifetime. While digital models of EV batteries have been created, they have lacked accurate real-world data to back them up. What’s more, not all batteries are born equal, and not all batteries are treated equally throughout their life, so they will degrade at different rates.

The developers fitted 50 LEVC taxis and Watt’s sports car with Silver Power Systems’ data-collecting IoT device, which communicates with the company’s cloud-based software. The EVs have collectively travelled over 500,000 km, and the data has been analyzed by SPS’s machine learning-powered platform EV-OPS.

“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,” explained Pete Bishop, CTO of Silver Power Systems. “But to date there has been a lack of data, and predictive modelling has been largely lab-based. By combining a robust real-world trial with our EV-OPS machine-learning analytics capability through the REDTOP program, we have not only been able to unlock an unprecedented view of real-time battery performance and state of health but also to create the world’s most advanced digital twin, enabling prediction of future battery life.”

“On top of [predicting] future battery degradation, we can use this technology to update an EV’s software via the cloud to change algorithms or parameters to optimize the performance of the battery as the cells age, and maximize battery life,” added Silver Power Systems Program Manager Liam Mifsud.

Source: Silver Power Systems