In order to effectively monitor the operating status and health of the single battery in the distributed energy storage system, timely issue early warning information of failures and provide decision-making basis for operation, inspection and maintenance, a joint online estimation method of single battery SOC(state of charge) and SOH(state of health)  is proposed in this paper. First, the second-order circuit model of battery is used to construct state space model. Second, the constructed battery state space model is discretized, so a multi-time-scale SOC&SOH joint online estimation method based on the combination of a short-time-scale state filter and a longer-time-scale parameter filter is proposed. Finally, the effectiveness of the method proposed in this paper is verified by simulation.

energy storage,SOC&SOH joint estimation,double extended Kalman filter,multiple time scales