Remaining Useful Life Estimation of Battery based on MEKF

With the wide application of lithium-ion batteries in the field of new energy vehicle, state of charge (SOC) estimation and remaining useful life (RUL) estimation have become important issues. This paper studies the state of charge estimation and RUL online estimation. Firstly, an experimental platform was setup and the battery cell experiment was conducted, which was used to bulid a battery model. Secondly, a multi-scale extended Kalman filter algorithm was proposed for SOC estimation and RUL estimation. Finally, based on the existing life cycle charge and discharge data, the proposed algorithm was evaluated, and can be effectively applied in practice.