Sensitivity analysis of the battery model for model predictive control implemented into a plug-in hybrid electric vehicle

Abstract

An effective online PMS is critical for the future electrified vehicles as it has direct impacts on fuel economy, greenhouse gasses (GHG) emission, as well as the durability of power-train components. In this paper, we considered a PMS developed based on the concept of model predictive control (MPC) which formulates the control design as an optimization problem that is solved based on forecasted system behaviors over a limited prediction horizon to obtain the optimal control actions for the current time instant. The main contribution of this paper is that we take a systematic approach to examine the link between model fidelity and controller performance for the case of a hybrid energy storage system in a light-duty hybrid electric vehicle. A sensitivity analysis approach is developed and presented in this paper along with preliminary simulation results to demonstrate the impact of battery model fidelity on the performance of the proposed PMS.