Research on Multiple States Joint Estimation Algorithm for Electric Vehicles Under Charge Mode

Abstract

Power battery is the core component of electric vehicles, and its characteristics determine the performance of electric vehicles. Lithium-ion power battery is a kind of time-varying nonlinear system, which has different external features under different application conditions and aging state. In order to implement the optimized charging method under changeable application conditions, the estimation of the internal states is extremely necessary. For this purpose, this paper studies the multiple states joint estimation based on the accurate and reliable battery modeling method. First, the modeling of lithium-ion battery and the parameter identification of the models are studied. A parameter identification method is proposed based on forgetting factor recursive extended least square. The battery model’s order is based on Bayesian information criterions. Second, multiple states joint estimation algorithm for power battery under charging mode is studied. For the estimated accuracy of the battery’s state of charge is associated with the battery usable capacity, state of charge and usable capacity joint estimation algorithm, based on several different order battery models is proposed. State of power estimation algorithm of the battery under multiple factors constraints is proposed based on the solution discrete analysis of the continuous time traction battery differential state equation. Finally, multiple states joint estimation algorithm is achieved. Validation results show that the proposed estimation algorithm can achieve high accuracy.