Overview of Battery Modeling Methods in Electric Vehicles

As a critical indicator in the Battery Management System (BMS), State of Charge (SOC) is closely related to the reliable and safe operation of lithium-ion (Li-ion) batteries. Model-based methods are an effective solution for accurate and robust SOC estimation. Its performance heavily relies on the battery model. An abstract representation of components and communications is a phenomenon that displays the relationships between entities and their various variables. Since the experience of all facts and phenomena is not practically possible, models are used to plot events, facts, or situations. In this study, the effect of the battery model on the accuracy of the model-based estimation is analyzed. The features of each modeling method are detailed. This paper divides the battery modeling method into four categories: Empirical Model, Equivalent Circuit Model (ECM), Electrochemical Model, and Data-driven Model. According to the structure of the model-based estimation, the advantages and disadvantages of each modeling method are presented. Moreover, four typical modeling methods in SOC estimation area including the combined model, two Resistance-Capacitance (RC) ECM, Single Particle Model (SPM) and Support Vector Machine (SVM) battery model are compared through an experiment on a LiFePO4 battery in terms of accuracy and computational efforts. Four typical models are compared in terms of accuracy and execution time with the measurement data from a LiFePO4 battery. After optimizing the parameters in each model by GA, the four models obtain acceptable results. The most accurate SVM model obtains 0.0034 V in MAE. The execution time of the combined model is only 6.3649×10-7s (MATLAB 2017b, 64 bit, 2.30 GHz CPU). SVM and SPM obtain better results in terms of accuracy, but the execution time of SVM and SPM is also longer than other two models. However, considering the flaws of SVM and SPM, the combined model and ECM are recommended for a LiFePO4 battery, if their accuracy are acceptable for a specific application. It should be noted that the conclusions obtained from the experimental results in this paper are only limited to the LiFePO4 battery, which has a flat OCV-SOC curve.

کلیدواژه ها:

Battery Modeling ، Electric Vehicle ، SOC ، BMS