A state space thermal model for HEV/EV battery using vector fitting

Abstract

Battery thermal management for high power applications such as electrical/hybrid vehicles is crucial. Modeling is an indispensable tool to help engineers design better battery cooling systems. A fast and accurate battery thermal model using state space representation can be used to predict volume-averaged cell temperature or temperature at user specified locations under transient heat dissipation. The matrices of the state space model are calculated by curve-fitting the step response of the state space model to that of the battery thermal system computed from computational fluid dynamics (CFD) results. In this paper, the vector-fitting (VF) method in the frequency domain is proposed for the curve-fitting. The frequency domain VF method is shown to provide advantages over the time domain Levenberg-Marquardt (LM) method. For batteries using prismatic cells, the VF method is shown to be more accurate. For multiple-input multiple-output (MIMO) battery thermal systems, the VF method generates much smaller state space models compared with those using the LM method. Therefore, for MIMO battery thermal systems, models from the VF method run much faster than those from the LM method.