State-of-charge-constraint-based energy management strategy of plug-in hybrid electric vehicle with bus route. (1st November 2019)

• Record Type: Journal Article
• Authors: Guo, Hongqiang; Wang, Xiangyu; Li, Liang
• Is Part Of: Energy conversion and management. Volume 199(2019)
• Publication Date: 2019-11-01
• Subjects: Plug-in hybrid electric vehicle -- Energy management strategy -- State of charge constraints -- Model predictive control -- Chaos particle swarm optimization; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2019.111972
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: A new equivalent efficiency model of engine is proposed. A state-of-charge-constraint-based cost function is designed. A nonlinear model predictive controller is designed. The bench test verified the real-time performance of proposed method. Abstract: For the plug-in hybrid electric vehicle (PHEV) with repeated routes, the route information is very useful for energy optimization. SOC (state of charge) of power battery is the most important parameter for PHEV, so the information is usually utilized to calculate reference SOC. However, it is not the optimal trajectory, which might restrict the improvement of economic performance. In this paper, the route information is processed by dynamic programming and a group of optimal state of charge trajectories are obtained. Then, a novel state-of-charge-constraint-based cost function is firstly proposed, which can be obtained by presented method based on history cycle data. Next, a nonlinear model predictive controller is designed as energy management strategy to evaluate different cost functions. Experiment results show that proposed cost function can save fuel consumption by 5.9% and 10.8% compared with other two common cost functions.