Multi-objective optimization of gearshift trajectory planning for multi-speed electric vehicles

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.

KEYWORDS:

• Electric vehicles
• multi-objective optimization
• gearshift control
• trajectory planning
• hardware-in-the-loop

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Natural Science Foundation of Guangdong Province [2020A1515010773].