{"id":728,"date":"2021-04-29T10:50:27","date_gmt":"2021-04-29T10:50:27","guid":{"rendered":"http:\/\/localhost:10109\/?post_type=white-paper&#038;p=728"},"modified":"2025-07-30T13:16:10","modified_gmt":"2025-07-30T13:16:10","slug":"artificial-intelligence-ai-points-the-way-to-better-ev-battery-management","status":"publish","type":"post","link":"https:\/\/eatron.com\/artificial-intelligence-ai-points-the-way-to-better-ev-battery-management\/","title":{"rendered":"Artificial Intelligence (AI) points the way to better EV battery management"},"content":{"rendered":"\n<p><strong>Enhanced artificial intelligence is an enabler for greater battery durability, energy density and charging speed. Eatron Technologies experts explain.<\/strong><\/p>\n\n\n\n<p>After two decades of significant advances in electric vehicle (EV) battery development, innovations continue to bring promises of greater battery performance, safety, faster charging, longevity and durability. One area of fresh thinking concerns battery management systems (BMS) using artificial intelligence (AI) as an enabler. Or more specifically, a novel dimension of AI, according to Dr. Umut Genc, managing director of Eatron Technologies, a U.K.-based company specializing in intelligent software for electric and autonomous vehicles.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><a href=\"https:\/\/eatron.com\/wp-content\/uploads\/2025\/05\/Screen-Shot-2021-04-29-at-13.18.26.png\"><img decoding=\"async\" data-src=\"https:\/\/eatron.com\/wp-content\/uploads\/2025\/05\/Screen-Shot-2021-04-29-at-13.18.26.png\" alt=\"\" class=\"wp-image-80590 lazyload\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 999px; --smush-placeholder-aspect-ratio: 999\/582;\" \/><\/a><\/figure>\n\n\n\n<p>\u201cWe define [it] as physics-based modeling with selective AI,\u201d he said. \u201cIt is vital to understand AI\u2019s limitations. First, the amount of memory and processing power required by an AI system is substantial, increasing cost and energy consumption. Second, AI is still in the early stages of application, so it is often seen to be not without risks. Any mission-critical system that is solely dependent on AI is currently difficult to validate to automotive standards,\u201d Genc explained.<\/p>\n\n\n\n<p>The solution, he noted, is the same for both challenges, starting with understanding the value that AI brings to objectives. Eatron\u2019s technical director, Can Kurtulus, underlined the importance of OEMs recognizing that there will not be a huge step in battery chemistry for some time. Therefore, many improvements in durability, usable energy density and charging speed must come from improved battery management.<\/p>\n\n\n\n<p>Kurtulus said he believes the key to be the application of physics-based software \u2013 control systems with embedded system models. This is a control technique in which look-up tables are replaced by an embedded software model of the system.<\/p>\n\n\n\n<p>\u201cIn other areas of vehicle design, accurate digital simulations have helped to eliminate the need for over-engineering. This has brought down cost and weight in a \u2018virtuous circle,\u2019\u201d he said. \u201cOur approach to BMS is similar, except we will be embedding the model in the control system of every battery pack and applying it in real time throughout the vehicle\u2019s life, not just during the design stage, so rather more than regular AI technology.\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image\"><a href=\"https:\/\/eatron.com\/wp-content\/uploads\/2025\/05\/1.png\"><img decoding=\"async\" data-src=\"https:\/\/eatron.com\/wp-content\/uploads\/2025\/05\/1.png\" alt=\"\" class=\"wp-image-80591 lazyload\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1200px; --smush-placeholder-aspect-ratio: 1200\/627;\" \/><\/a><\/figure>\n\n\n\n<p><strong>First for EV diagnostics<\/strong><\/p>\n\n\n\n<p>With the backing of an unnamed German Tier 1 supplier and engineering teams in the U.K. and Turkey, Eatron\u2019s initial production programs concerned chassis management systems and SAE Level 2 automated driver-assist systems. But BMS has now become a major R&amp;D program. The immediate benefits claimed for Eatron\u2019s selective AI applications are the reduced need to over-specify the battery to protect durability and hence lower warranty costs.<\/p>\n\n\n\n<p>\u201cThe biggest influences on battery life are currently the state of charge window: how close to full charge and full discharge the battery is allowed to go, and then the rate of charge,\u201d Kurtulus said. \u201cSo, in today\u2019s production systems, warranty claims are minimized by calibrating the BMS to prevent the battery being charged to full capacity, to never approach deep discharge even if the vehicle is only a few miles from a charging station, and to always restrict the fast-charge capability.\u201d<\/p>\n\n\n\n<p>An Eatron innovation is to use its physics-based modeling techniques to predict the remaining useful life (RUL) of the battery. The company expects to be the first supplier of production technologies offering this feature for lithium-ion EV batteries. It also aims to be first to offer vehicle OEMs an opportunity to include a RUL indicator in the vehicle diagnostics.<\/p>\n\n\n\n<p>Genc noted selective AI\u2019s major benefits will be fully gained when the BMS is connected to the cloud. \u201cPrediction of the RUL will allow the vehicle manufacturer to issue over-the-air calibration updates that maximize customer benefits, such as fast charging and range,\u201d he noted, \u201cwhile remaining confident that warranty and durability targets will be met.\u201d<\/p>\n\n\n\n<p>As more data is analyzed, the AI learns; predictions become more accurate and the benefits are automatically incorporated in the decision-making. There is also potential for the vehicle OEM to add new features that bring additional benefits for owners. For example, there is currently no way for a used vehicle buyer to determine the RUL of an EV\u2019s battery.<\/p>\n\n\n\n<p>\u201cFor fleets especially, an ability to manage and then validate the RUL will add significant value when they come to dispose of their vehicles. A dashboard RUL indicator could be fitted,\u201d Genc stated. Added Eatron\u2019s business development director, Amedeo Bianchimano: \u201cThe combination of AI and a connection to the cloud will give battery management software a much more important role, not just as a tool for maximizing e-vehicle attributes but also in offering warranty management and additional software services.\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image\"><a href=\"https:\/\/eatron.com\/wp-content\/uploads\/2025\/05\/Screen-Shot-2021-04-29-at-13.16.32.png\"><img decoding=\"async\" data-src=\"https:\/\/eatron.com\/wp-content\/uploads\/2025\/05\/Screen-Shot-2021-04-29-at-13.16.32.png\" alt=\"\" class=\"wp-image-80587 lazyload\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1080px; --smush-placeholder-aspect-ratio: 1080\/609;\" \/><\/a><\/figure>\n\n\n\n<p><strong>More detailed prognostics<\/strong><br>Eatron has established a joint research project with the U.K.\u2019s Warwick Manufacturing Group (WMG), a department of The University of Warwick, to extend their BMS development into more detailed prognostics. At present, the system can only identify problems with battery cells as they occur (typically no more than a few seconds before failure), shutting down the battery pack or putting it into limp-home mode.<\/p>\n\n\n\n<p>The objective of the research with WMG is to refine an innovation in diagnostics that allows Eatron to identify cell-related problems usefully before failure \u2013 not seconds before as is typically the situation today, but up to several months ahead of a failure.<\/p>\n\n\n\n<p>\u201cWith this technology embedded in a battery pack, the chemistry can be driven much harder,\u201d stressed Kurtulus. \u201cThis has been a goal for many years but previously it required considerable added hardware complexity. Our approach applies machine learning to established signal processing theory to isolate the diagnostic characteristic from the noise, without any additional components.\u201d<\/p>\n\n\n\n<p>For the vehicle owner, the benefits claimed by Eatron will also include BMS calibrations that deliver more range and faster charging, \u201cwhile simultaneously reducing the risk of being left at the side of the road with a disabled vehicle,\u201d Genc said. \u201cOur approach is to create a robust system using proven model-based control technologies, then to carefully add in AI where it is needed for specific calculations. Battery health management is just the starting point. The real excitement is what comes next!\u201d<\/p>\n\n\n\n<p>Reference: https:\/\/www.sae.org\/news\/2021\/03\/battery-management-systems-use-selective-ai<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Enhanced artificial intelligence is an enabler for greater battery durability, energy density and charging speed. Eatron Technologies experts explain. After two decades of significant advances in electric vehicle (EV) battery development, innovations continue to bring promises of greater battery performance, safety, faster charging, longevity and durability. One area of fresh thinking concerns battery management systems &hellip; <a href=\"https:\/\/eatron.com\/artificial-intelligence-ai-points-the-way-to-better-ev-battery-management\/\">Continued<\/a><\/p>\n","protected":false},"author":1,"featured_media":712,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-728","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Artificial Intelligence (AI) points the way to better EV battery management - Eatron Technologies<\/title>\n<meta name=\"description\" content=\"Eatron explores how AI-powered battery management systems boost EV performance, safety, charging speed, and long-term durability.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/eatron.com\/artificial-intelligence-ai-points-the-way-to-better-ev-battery-management\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Artificial Intelligence (AI) points the way to better EV battery management - 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