A world-first, real-life trial of electric vehicles (EVs), involving leading battery analytics specialist Silver Power Systems (SPS), electric vehicle manufacturers and academics, has brought closer the holy grail of battery modelling to accurately predict electric vehicle battery lifespan.
With the rapid growth in electrification driven by the 2030 ban on new internal combustion engine (ICE) sales combined with the battery being by far the most expensive component of an electric vehicle, it is critical for all sectors.
Until now, predicting lifespan has been difficult to predict. While digital models of electric car batteries have been created, they have lacked accurate real-world data to back them up.
What’s more, not all batteries are born equal. Plus, not all batteries are treated equally throughout their life. They degrade at different rates, subject to different drivers and charging routines. This further underlines the need for real-world data to be combined with machine-learning based predictive technology.
Run over the last nine months, the pioneering Real-time Electrical Digital Twin Operating Platform (REDTOP) automotive research programme has sought to bring about a step change in battery understanding. The objective has been to create the world’s most advanced battery ‘digital twin’, a highly-sophisticated virtual model, linked to a real battery.
Part-funded by The Advanced Propulsion Centre UK (APC), the revolutionary project, led by Silver Power Systems, has seen partners Imperial College, London Electric Vehicle Company (LEVC) and JSCA, the research and development division of the Watt Electric Vehicle Company have joined forces on a real-world electric vehicle trial.
Since January, some 50 LEVC TX electric taxis and a new electric sports car from the Watt EV Company have collectively travelled over 500,000km as part of the programme. Each vehicle has been fitted with Silver Power Systems’ state-of-the-art data-collecting IoT device, which constantly communicates with the company’s cloud-based software.
This crucial data has been analysed by SPS’s machine learning-powered platform EV-OPS, and together with Imperial College’s battery researchers, the world’s most advanced digital twins of actual EV batteries have been created.
This offers not just an unprecedented view of real-time battery performance and state-of-health, but also the potential to enable these highly sophisticated battery models to predict battery lifespan.
Pete Bishop, Silver Power Systems CTO, said: “This really is the holy grail. 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.
“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.”
SPS’s technology has enormous benefits for a wide variety of sectors. Unparalleled monitoring gives a total picture of battery activity, identifying differences between batteries, whether performance or charging capability. Plus, in the long term builds up a complete picture of battery health over the life of the vehicle.
For electric vehicle manufacturers, this monitoring capability gives insights into battery performance enabling them to accelerate the development of battery-powered vehicles.
Fleet operators can gain a complete picture of electric vehicle health across their fleet enabling them to more efficiently run their vehicles and potentially extend their life). Fleet owners can also use SPS’s capabilities to predict the future residual value of vehicles based on future battery health. As the market transitions to electric cars, this is set to become of ever-increasing importance.
OEMs and battery manufacturers can use the technology to enable more accurately underwritten battery warranties. Other sectors that can benefit include insurance providers, transport authorities, councils and even private electric vehicle owners for whom having access to data on their own vehicle’s battery performance is beneficial.
Liam Mifsud, Silver Power Systems Program Manager, said: “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.”