Enhanced Battery Power Constraint Handling in MPC-Based HEV Energy Management: A Two-Phase Dual-Model Approach

Abstract

This article presents a novel two-phase dual-model approach to more appropriately handle battery power constraint in model predictive control (MPC)-based hybrid electric vehicle (HEV) energy management. The approach fuses two typical battery models with different fidelities in two consecutive phases of MPC's prediction horizon, where more accurate first-order resistor-capacitor (RC) model is adopted in the near phase, while a purely ohmic impedance model is used in the more distant phase. More importantly, it is mathematically rigorously proved that the first-order RC model can be reformulated as an equivalent single-state model while preserving accurate voltage calculation, provided that the length of phase one is properly determined. Finally, the formulated optimal energy management problem is solved using a forward dynamic programming (FDP) algorithm. Both numerical examination and model in the loop (MiL) test using an experimentally validated forward-facing simulator demonstrate that compared with traditional approach, the proposed approach can achieve better optimality in the condition of very sparse state discretization, which is imperative for real-time implementation.