Deep learning model tracks EV battery health with high precision
Tokyo, Japan (SPX) Feb 16, 2026
With electric vehicles and grid storage expanding worldwide, engineers are looking for better ways to track how lithium ion batteries age under real driving and operating conditions. A new study supported by Jilin University and China FAW Group reports a deep learning based method that monitors battery state of health with errors below 1 percent even when current and voltage vary in complex pat
With electric vehicles and grid storage expanding worldwide, engineers are looking for better ways to track how lithium ion batteries age under real driving and operating conditions. A new study supported by Jilin University and China FAW Group reports a deep learning based method that monitors battery state of health with errors below 1 percent even when current and voltage vary in complex pat
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