Machine learning algorithm predicts how to get the most out of electric vehicle batteries

Researchers have developed a machine learning algorithm that could help reduce charging times and prolong battery life in electric vehicles by predicting how different driving patterns affect battery performance, improving safety and reliability. This method could unlock value in so many parts of the supply chain, whether you-re a manufacturer, an end user, or a recycler, because it allows us to capture the health of the battery beyond a single number Alpha Lee The researchers, from the University of Cambridge, say their algorithm could help drivers, manufacturers and businesses get the most out of the batteries that power electric vehicles by suggesting routes and driving patterns that minimise battery degradation and charging times. The team developed a non-invasive way to probe batteries and get a holistic view of battery health. These results were then fed into a machine learning algorithm that can predict how different driving patterns will affect the future health of the battery. If developed commercially, the algorithm could be used to recommend routes that get drivers from point to point in the shortest time without degrading the battery, for example, or recommend the fastest way to charge the battery without causing it to degrade. The results are reported in the journal Nature Communications . The health of a battery, whether it-s in a smartphone or a car, is far more complex than a single number on a screen.