The proposed battery state of health estimation adopt discrete quantization algorithm. The proposed technique which can get state of health achieves data collection and analysis in driving electronic vehicle immediately; also compensate the state of charge to decrease the estimation error rate. The proposed technique can embed in battery management system and co-work, it’s a big different from general off-line estimation methods, the proposed technique decrease the estimation time and system cost.

Error rate <15%
dynamic estimation
 

Electronic Vehicle, Energy Management System, Energy Storage System

By using the proposed method achieves battery aging estimation in driving for battery swap station vendor. Advantages are, achieving battery modules aging estimation without time spending and without more energy. Using initial condition setting to replace battery aging database, the increase time to market