Multiobjective gearshift optimization with Legendre pseudospectral method for seamless two-speed transmission

Abstract Most researches on transmission gearshift optimization have converted multiobjective problems into single-objective problems using the linear weighted method. A new framework for the multiobjective optimization of the gearshift, in the form of a Pareto solution set, is proposed in this study. Shift duration, friction work, and continuous jerk are selected as the gearshift optimization objectives for a seamless two-speed transmission, utilized in electric vehicles. For this multiobjective optimization, numerous iterations were performed using the Legendre pseudospectral method, which includes advantages such as faster convergence and larger radius of convergence. The numerical results presented as a Pareto solution set provide the optimal gearshift trajectories for different performance orientations. By comparing the selected samples, the inherent relationships among the gearshift objectives were investigated in detail and revealed. This framework for solving multiobjective problems can also be applied to other optimization problems with different complex constraints and objective functions.

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