Lithium Battery SOC Estimation Method Study Based on Principal Component Analysis

Battery SOC is acted as an essential parameter for EV and HEV, its accurate estimate relates to whether the vehicle control strategy is implemented correctly. There has been no other prediction method, which can obtain a more accurate prediction result. To overcome this deficiency, this paper presents a method to build a battery SOC estimation models using principal component analysis (PCA). PCA cannot manage to extract nonlinear factors in the parameters, which may induce prediction error based on the analysis result, in view of this kernel principle component analysis (KPCA) is applied to establish the prediction model. Corresponding simulation and experiments are conducted to verify the proposed model. The simulation results have shown that the revised model can be applied to various working condition with superior real-time ability, reliability and improved precision. The average error of the prediction results can be reduced to 1.46% in comparison with Ah measurement.