A Method of Remaining Capacity Estimation for Lithium-Ion Battery

Combining particle filter (PF) with sample entropy feature of discharge voltage, a method of remaining capacity estimation for lithium-ion battery is proposed. The sample entropy calculated from discharge voltage curve can serve as an indicator for assessing the condition of battery. Under a certain working condition, a functional relationship between sample entropy and discharge capacity is created and estimations computed from the function are taken as observations to propagate particles in PF. The results indicate that the algorithm enhances the accuracy. Due to the establishment of functions at different discharge rates and temperature modification, prognostic accuracy of discharge capacity has been improved under multi-operating working conditions.