A magnetic flux controllable memory motor online magnetic modulation performance prediction and optimization design method based on nonlinear equivalent variable magnetic network model

Abstract

The invention discloses a magnetic flux controllable memory motor online magnetic modulation performance prediction and optimization design method based on a nonlinear equivalent variable magnetic network model. The method includes: (1) setting material characteristics of each part of the motor; (2) establishing a nonlinear equivalent variable magnetic network model; (3) carrying out simulation calculation on the adjustable magnetic material; (4) optimizing motor structure parameters by combining a multi-objective genetic algorithm based on NSGA II with a nonlinear variable magnetic network; (5) changing the magnitude of excitation current, and obtaining an initial feasible non-dominated solution set; and (6) changing the magnitude of the excitation current, and reducing the range of the non-dominated solution set, so that the non-dominated solution set gradually approaches the optimal solution set suitable for multi-mode operation of the memory motor, wherein the target function of all parameter combinations in the preliminary feasible non-dominated solution set is solved again; And finally, obtaining an optimal parameter combination in the parameter set at the front edge of the optimal solution set, and determining the motor structure.

Description

technical field [0001] The invention relates to a method for predicting and optimizing the online magnetic adjustment performance of a magnetic flux controllable memory motor based on a nonlinear equivalent variable magnetic network model, and belongs to the technical field of motors. Background technique [0002] In the field of motor technology, the permanent magnet synchronous motor (PMSM) has been widely used due to its advantages of simple structure, small size, light weight, low loss and high efficiency. However, due to the inherent characteristics of ordinary permanent magnet materials (such as NdFeB), the air gap magnetic field in the motor is basically kept constant, and the speed regulation range is very limited when it is operated as an electric motor. The adjustable flux permanent magnet motor aiming to realize the effective adjustment of the air gap magnetic field of the permanent magnet motor has always been a hot and difficult point in the field of motor resea...

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Problems solved by technology

However, this method has certain shortcomings, the most prominent of which is that its sensitivity range needs to be set manually, which leads to the participation of human subjective factors in the final optimization result.

The patent application No. 201410836987.0 proposes a genetic algorithm-based multi-objective optimization design method for vehicle motors, aiming at multi-objective optimization of vehicle motors through simple genetic algorithms. However, it uses weighted methods for multi-objective optimization problems. The weight coefficient needs to be involved in human subjective factors, resulting in a certain deviation in the final optimization result

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