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. <\/p>\n\n\n\n
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, writes the British university in a press release<\/a>.<\/p>\n\n\n\n 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.<\/p>\n\n\n\n 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. <\/p>\n\n\n\n The health of a battery, whether it\u2019s in a smartphone or a car, is far more complex than a single number on a screen. \u201cBattery health, like human health, is a multi-dimensional thing, and it can degrade in lots of different ways,\u201d said first author Penelope Jones, from Cambridge\u2019s Cavendish Laboratory. \u201cMost methods of monitoring battery health assume that a battery is always used in the same way. But that\u2019s not how we use batteries in real life. If I\u2019m streaming a TV show on my phone, it\u2019s going to run down the battery a whole lot faster than if I\u2019m using it for messaging. It\u2019s the same with electric cars \u2013 how you drive will affect how the battery degrades.\u201d<\/p>\n\n\n\n The researchers developed a non-invasive probe that sends high-dimensional electrical pulses into a battery and measures the response, providing a series of \u2018biomarkers\u2019 of battery health. This method is gentle on the battery and doesn\u2019t cause it to degrade any further.<\/p>\n\n\n\n The electrical signals from the battery were converted into a description of the battery\u2019s state, which was fed into a machine learning algorithm. The algorithm was able to predict how the battery would respond in the next charge-discharge cycle, depending on how quickly the battery was charged and how fast the car would be going the next time it was on the road. Tests with 88 commercial batteries showed that the algorithm did not require any information about previous usage of the battery to make an accurate prediction.<\/p>\n\n\n The experiment focused on lithium cobalt oxide (LCO) cells, which are widely used in rechargeable batteries, but the method is generalisable across the different types of battery chemistries used in electric vehicles today.<\/p>\n\n\n\n The researchers say that in addition to manufacturers and drivers, their method could be useful for businesses that operate large fleets of electric vehicles, such as logistics companies. \u201cThe framework we\u2019ve developed could help companies optimize how they use their vehicles to improve the overall battery life of the fleet,\u201d said\u00a0Dr. Alpha Lee, who led the research. \u201cThere\u2019s so much potential with a framework like this.\u201d<\/p>\n\n\n\n The researchers are now working with battery manufacturers to accelerate the development of safer, longer-lasting next-generation batteries. They are also exploring how their framework could be used to develop optimal fast charging protocols to reduce electric vehicle charging times without causing degradation.<\/p>\n","protected":false},"author":2084,"featured_media":516789,"template":"","meta":{"_acf_changed":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":""},"categories":[26049],"tags":[29474,23535,35789,46284],"location":[55977],"internal_archives":[],"class_list":["post-397038","selected","type-selected","status-publish","has-post-thumbnail","hentry","category-mobility","tag-battery","tag-electric-vehicles","tag-sustainable-mobility","tag-university-of-cambridge","location-united-kingdom"],"blocksy_meta":[],"acf":[],"featured_img":"https:\/\/ioplus.nl\/archive\/wp-content\/uploads\/2022\/07\/continental_pp_current-sensor-module.jpg","coauthors":[],"author_meta":{"author_link":"https:\/\/ioplus.nl\/archive\/author\/mauro-mereu\/","display_name":"Mauro Mereu"},"relative_dates":{"created":"Posted 4 years ago","modified":"Updated 4 years ago"},"absolute_dates":{"created":"Posted on August 24, 2022","modified":"Updated on August 24, 2022"},"absolute_dates_time":{"created":"Posted on August 24, 2022 11:30 am","modified":"Updated on August 24, 2022 11:30 am"},"featured_img_caption":"","tax_additional":{"category":{"linked":["Mobility<\/a>"],"unlinked":["Mobility<\/span>"],"slug":"category","name":"Categories"},"post_tag":{"linked":["battery<\/a>","electric vehicles<\/a>","sustainable mobility<\/a>","University of Cambridge<\/a>"],"unlinked":["battery<\/span>","electric vehicles<\/span>","sustainable mobility<\/span>","University of Cambridge<\/span>"],"slug":"post_tag","name":"Tags"},"language":{"linked":["EN<\/a>"],"unlinked":["EN<\/span>"],"slug":"language","name":"Tags"},"post_translations":{"linked":["pll_630637e33ba28<\/a>"],"unlinked":["pll_630637e33ba28<\/span>"],"slug":"post_translations","name":""},"location":{"linked":["United Kingdom<\/a>"],"unlinked":["United Kingdom<\/span>"],"slug":"location","name":"Locations"},"internal_archives":{"linked":[],"unlinked":[],"slug":"internal_archives","name":"Internal Archives"}},"series_order":"","_links":{"self":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/selected\/397038","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/selected"}],"about":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/types\/selected"}],"author":[{"embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/users\/2084"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/media\/516789"}],"wp:attachment":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/media?parent=397038"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/categories?post=397038"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/tags?post=397038"},{"taxonomy":"location","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/location?post=397038"},{"taxonomy":"internal_archives","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/internal_archives?post=397038"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Avoiding battery’s degrade<\/h2>\n\n\n\n
Battery’s ‘biomarkers’<\/h2>\n\n\n\n
Potential for several areas <\/h2>\n\n\n\n