Model Predictive Control Based Energy Management Strategy for a Plug-In Hybrid Electric Vehicle

Abstract

Keywords: model predictive control (MPC), plug-in hybrid electric vehicles (PHEVs), energy management strategy.Abstract. In this paper, the model predictive control (MPC) method is researched for energy management problem of plug-In hybrid electric vehicle (PHEV). Multi-step Markov prediction method is selected for the prediction. Dynamic programming (DP) is chosen to solve the optimization problem within the prediction horizon. Through the comparison of MPC result with the results of dynamic programming strategy and a rule-based strategy, it is certified that the control effect of MPC strategy is much better than the ruled-based strategy and close to the global optimal control under DP strategy.

A survey on driving prediction techniques for predictive energy management of plug-in hybrid electric vehicles

“…Expand one-order Markov Model to High-order Markov Model [23], [67], [69] Integrating Route-based information into Prediction framework [10], [11], [33]- [35], [56]- [61], [71], [74], [75], [77]- [79], [87], [97], [98], [112], [113], [116] Self-learning/Adaptive Mechanism Adaptive/Self-learning Markov approaches [51], [52], [64], [72], [73] Moving window Approaches [93] Variable prediction horizon…”