Machine Learning Based Methodology for Fast Assessment of Battery Health Status

Rapid growth of global electric vehicle (EV) market, strongly supported not only by government authorities but also by many private sectors created the challenge of managing life cycle of Li-ion batteries mainly due to the limited resource of raw materials. One of the main ideas to surmount the issue is the reuse or recycle of the retired batteries from the initial use with EVs. In doing so, a fast and reliable methodology for the estimation of static capacity of the retired batteries are a must for the success. Traditional evaluation method, however, is quite time-consuming which takes longer than a few hours. To overcome this shortcoming, the current research showed a machine learning-based approach that can reliably estimate the static capacity of the retired batteries.