New approach to predicting battery failure could help maintain electricity for millions around the world

The new method of predicting battery failure is 15 - 20% more accurate than current approaches. Millions of people around the world lack access to electricity. Decentralised solar-battery systems are key for addressing this whilst avoiding carbon emissions and air pollution, but are hindered by relatively high costs and rural locations that inhibit timely preventative maintenance. When batteries in such systems fail, it can be difficult to replace them and can leave people stuck without access to power. Knowing when the batteries are likely to fail is therefore crucial in planning repair logistics and minimising power supply downtime. Now a unique approach to calculating battery failure, affiliated to the Faraday Institution's  Multiscale Modelling project , has been shown to make predictions that are 15-20% more accurate than current approaches used on the same dataset. The paper, from the University of Oxford and the Faraday Institution, has been published today in  Joule .