Electro-Thermal Battery Model for Automotive Applications

Battery modeling plays a crucial role in improving the performance of battery powered systems, especially in electric vehicle (EV) applications. In the present paper, a methodology is investigated to predict the electrical and thermal behaviors of a battery cell. This work describes a model identification procedure for identifying an electro-thermal model of lithium-ion batteries used in automotive applications. The dynamic model structure adopted is based on equivalent circuit model whose parameters are scheduled on the state-of-charge, temperature, and current. The model identified in this way is valid inside a large range of temperatures and state-of-charge, so that the resulting model can be used for automotive applications such as on-board estimation of the state-of-charge and state-of-health. The model coefficients are identified using a multiple step algorithm-based optimization procedure. The validity of the procedure is demonstrated experimentally for A123 commercial LFP/graphite battery cells.