Nonlinear Model Predictive Control of a Power-Split Hybrid Electric Vehicle with Consideration of Battery Aging

[+] Author and Article Information
Ming Cheng

Department of Mechanical Engineering - Engineering Mechanics, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931

Bo Chen

ASME Member, Department of Mechanical Engineering - Engineering Mechanics, Department of Electrical and Computer Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931

1Corresponding author.

ASME doi:10.1115/1.4042954 History: Received March 15, 2018; Revised February 19, 2019


In this paper, the nonlinear model predictive control (NMPC) for the energy management of a power-split Hybrid Electric Vehicle (HEV) has been studied to improve battery aging while maintaining the fuel economy at a reasonable level. A first principle battery model is built with simulation capacity of the battery aging features. The built battery model is integrated with an HEV model from Autonomie software to investigate the vehicle and battery performance under control strategies. The NMPC has simplified battery models to predict the state of charge (SOC) change, the fuel consumption of the engine and the battery aging index over the predicted horizon. The purpose of the NMPC is to find an optimized control sequence over the prediction horizon, which minimizes the designed cost function. The proposed control strategy is compared with that of an NMPC which doesn't consider the battery aging. It is found that, with the optimized weighting factor selection, the NMPC with the consideration of battery aging has better battery aging performance and similar fuel economy performance comparing with the NMPC without the consideration of battery aging.

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