Model-Based Peak Power Estimation of Lithium-Ion Batteries for Electric Vehicles

Abstract

The accuracy estimation of the peak power can guarantee the battery’s safety, and make full use of the battery performance during the allowed safe range, thus improving the safety, power and quick charge performance. Up to now, the peak power in the electric vehicles is usually acquired by the peak power, SOC and temperature map, thus requiring a lot of offline experiments, and not taking the real-time polarization into account. Besides, the map method is strongly influenced by the accuracy of SOC and battery aging. In response to these circumstances, this paper has developed a model-based method for peak power online estimation. Firstly, the one order resistance-capacity equivalent circuit model has been employed to model the battery; Secondly, the parameters of the model have been on-line estimated by the particle swarm optimization (PSO) method; Thirdly, through the model-based method, the peak power of the battery has been obtained; Finally, a simplified version of the federal urban driving schedule (SFUDS) with inserted pulse experiment has been conducted to verify the peak power estimated. The result indicates that the proposed method is accurate and reliable with the 25 W maximum absolute error of the peak power.