LAUSR

In this paper, a novel noise adaptive moving horizon estimation (NAMHE) method is proposed to improve the accuracy of state of charge(SOC) estimation of Li-ion batteries under the unknown noise conditions. Specifically, based on the maximum likelihood principle, the unknown statistical characteristics of the noises can be estimated to modify the recurrence expression of the NAMHE. Then, the SOC estimation algorithm is designed by combining the equivalent circuit model and the proposed NAMHE. Furthermore, the convergence of the estimation error expectation is obtained for the NAMHE algorithm. Finally, the simulation results clarify that the SOC estimation error under the different unknown noise conditions can be effectively reduced by the proposed method, compared with the traditional MHE method.