An improved adaptive equivalent consumption minimization strategy for parallel plug-in hybrid electric vehicle. (May 2019)

• Record Type: Journal Article
• Authors: Zhang, Yuanjian; Chu, Liang; Fu, Zicheng; Guo, Chong; Zhao, Di; Li, Yukuan; Ou, Yang; Xu, Lei
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 233:Number 6(2019:Jun.)
• Page Start: 1649
• Page End: 1663
• Publication Date: 2019-05
• Subjects: Adaptive equivalent minimization strategy -- floating car data -- equivalent factor adjustment -- parallel plug-in hybrid electric vehicle; Mechanical engineering -- Congresses; Transportation engineering -- Congresses; 629.2
• DOI: 10.1177/0954407018805605
• Languages: English
• ISSNs: 0954-4070

Abstract

Energy management strategies are of the vital importance in fully playing the potential of plug-in hybrid electric vehicles. This paper proposes an improved adaptive equivalent minimization strategy for a parallel plug-in hybrid electric vehicle. In this method, performance of adaptive equivalent minimization strategy is prompted through incorporating information of future driving condition into equivalent factor adjustment. Two main works have been done. First, a novel equivalent factor adjustment method is proposed in the improved adaptive equivalent minimization strategy. Based on the predicted information of future driving condition, equivalent factor is tuned in each running loop of equivalent minimization strategy. Second, information of future driving condition is predicted by harnessing floating car data. Benefit from future driving condition forecasting, the improved adaptive equivalent minimization strategy holds better capability in accommodating road condition switching and preliminary self-regulation for hilly road. Simulation results show that, compared with the convention adaptive equivalent minimization strategy, the improved adaptive equivalent minimization strategy can obtain better fuel economy.