Multi-objective optimal design of permanent magnet eddy current retarder based on NSGA-II algorithm

As a new type of vehicle auxiliary braking device, permanent magnet eddy current retarder has a wide application prospect. In this paper, the linear layer analysis method and non-dominated sorting genetic algorithm-II (NSGA-II) are combined to optimize the parameters of permanent magnet eddy current retarder. Firstly, based on the linear layer model, the mathematical optimization model of permanent magnet eddy current retarder is established by taking the radial length of permanent magnet, the thickness of permanent magnet, the number of permanent magnets and the thickness of conductor disk as design variables, the braking torque and eddy current loss as optimization objectives. Secondly, the NSGA-II algorithm is used to optimize the braking torque and eddy current loss of the permanent magnet eddy current retarder. Finally, the performance of the permanent magnet eddy current retarder after the optimization of the structural parameters is carried out by using ANSYS software to verify the accuracy and feasibility of the optimization results. The optimization algorithm used in this article solves the problem of poor adaptability to environmental changes and premature convergence in the late evolution of standard genetic algorithm. The results show that the NSGA-II algorithm based on the layer analysis model has better computational results in the optimal design of structural parameters than the standard genetic algorithm. (C) 2021 Published by Elsevier Ltd.