Multi-objective optimization of gearshift trajectory planning for multi-speed electric vehicles. Issue 6 (3rd June 2022)

• Record Type: Journal Article
• Authors: Zhao, Kegang; Li, Ziqi; Chen, Yuzhong; Liu, Yanwei
• Is Part Of: Engineering optimization. Volume 54:Issue 6(2022)
• Page Start: 949
• Page End: 972
• Publication Date: 2022-06-03
• Subjects: Electric vehicles -- multi-objective optimization -- gearshift control -- trajectory planning -- hardware-in-the-loop; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2021.1902513
• Languages: English
• ISSNs: 0305-215X

Abstract

Abstract : Multi-speed transmissions can enhance the comprehensive performance of electric vehicles (EVs), while exhibiting potential to further improve their shift quality. In this study, a gearshift control architecture combined with multi-objective trajectory planning was proposed for EVs with two-speed transmission. Three indices, namely shifting duration, jerk and friction work, were selected as optimization objectives. Numerous iterations of multi-objective optimization were conducted using the Legendre pseudospectral method, which is an optimization algorithm with high convergence speed and low sensitivity to initial values. Optimization results were presented through a Pareto solution set which was then used as a reference by the control architecture for optimal trajectory selection in the transmission control unit. In a hardware-in-the-loop experiment, the control architecture was applied in a passenger car to run the New European Driving Cycle, demonstrating the effectiveness and feasibility of the developed multi-objective trajectory planning and gearshift control architecture.