A study conducted by researchers from Uppsala University’s Ångström Advanced Battery Center has found that artificial intelligence can be used to improve the safety and lifespan of electric vehicle batteries. Led by materials chemistry Prof. Daniel Brandell, the research team built an artificial intelligence model that can accurately map how an EV battery will degrade as it ages over time, potentially opening the door to safer and longer-lasting electric vehicle batteries.
With the global transition from internal combustion engine (ICE) cars to EVs losing momentum due to the rapid degradation of EV batteries, the AI tool could not have come at a better time.
EV batteries are arguably the most important component of any battery electric car. In addition to being the most costly EV components, they are entirely responsible for powering an EV’s electric motor and all its other energy needs. The average electric vehicle battery will last around 10 to 20 years depending on factors such as climate, driving and charging habits, and the battery’s chemistry and thermal management systems, before either being recycled or reused in stationary energy storage systems.
However, with the world’s limited supply of electric vehicle batteries degrading faster than they can be replenished, automakers have been forced to slow down electric vehicle production. This issue is especially prevalent in Western markets like Europe and the U.S. that don’t have a mature EV battery supply chain and are largely reliant on China for critical EV battery raw materials.
As a result, electric vehicle adoption is plateauing in several Western markets where automakers aren’t manufacturing enough EV batteries for new electric cars or to replace worn EV batteries.
Using Uppsala University’s AI tool, automakers may be able to address one of the main challenges facing EV adoption; EV battery lifespan and safety. According to Professor Brandell, the AI tool his team developed could help automakers improve electric vehicle control systems by providing greater insight into how electric vehicle batteries degrade and age.
This enhanced understanding represents a significant breakthrough in battery management technology. The AI model can allegedly provide a 70% improvement in the accuracy of EV battery health predictions by analyzing the complex chemical reactions that generate electricity and tracking how these processes change over time.
Rather than relying on extensive vehicle data collection, the system works with short charging segments, addressing both industry privacy concerns and user anonymization issues. The research team believes this approach will enable manufacturers to optimize battery performance while extending operational lifespans, ultimately making electric vehicles more reliable and cost-effective for consumers. By predicting potential safety issues before they occur, the technology could also prevent the design flaws and side reactions that currently plague battery systems.
This AI tool could be a valuable complement or addition to the systems that EV makers like Bollinger Innovations, Inc. (NASDAQ: BINI) leverage in a bid to bring to market vehicles with batteries that perform reliably for a long time.
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