Combined SOC and SOE Estimation of Lithium-ion battery for Electric Vehicle Applications

To optimize the energy storage management system of an electric vehicle (xEVs), the accurate monitoring of battery states are needed. In this paper, the simple combined state of charge (SOC) and state of energy (SOE) estimation method is proposed. By using this method, the battery SOC and SOE both can be estimated at a low cost of computational complexity. The relationship between battery SOC and SOE for commercial lithium nickel cobalt chemistry battery is determined and validated under different operating conditions. Experimental results show that the proposed method can effectively estimate the SOC and SOE of the battery under different dynamic operating conditions with high accuracy. The recorded RMSE of SOC and SOE is always less than 1.6 % under all considered operating conditions. The simplicity of the proposed SOC and SOE estimation method helps to reduce the computational burden to the processor used in BMS, and therefore it is suitably implemented in xEV applications.