New study on EV battery life boasts breakthrough results for preventing degradation

A research project has created ‘digital twins’ of real life EV batteries using data from 50 LEVC TX taxis and the Watt EV Company’s all-new sports car, which have travelled a collective 500,000-km over nine months. The project promises to provide a much clearer picture of real-life battery degradation.

The Real-Time Electrical Digital Twin Operating Platform (REDTOP) is a research program designed to predict battery lifespan. A tribute to the power of collaboration, REDTOP is the brainchild of a partnership between Silver Power Systems (SPS), Imperial College, London EV Company, and Watt Electric Vehicle Company.

EVs are widely recognised as a potentially essential 21st century innovation. But for many, questions around battery lifespan are a barrier to acceptance. Whether you are buying one for your family or a fleet for your business, the ability to forecast performance would be invaluable for investment decision making. While REDTOP has potential to support these decisions, SPS has even bigger ambitions for the program.

SPS Program Manager Liam Mifsud asserts: “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.”

Silver Power Systems Swindon. Pete, Liam, Parminder.

Batteries are far and away the most expensive component of EV cars. Understanding how they will degrade over time is critical to determining how to extend their lifespan. If REDTOP can indeed identify what changes would optimize a battery lifespan, this could be the key to overcoming the last hurdle for EV sceptics. With fuel shortages making headlines, this breakthrough could not be more timely.

In addition to its value for purchasing decisions, the ‘digital twin’ concept has potential application for battery warranty valuations. SPS aims to further refine its technology for future application to optimise EV batteries throughout their lifecycle.

The study, which has been in part funded by The Advanced Propulsion Centre UK, links the EV data to a virtual model through cloud storage.

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