Multi-objective optimization method of novel consequent-pole brushless hybrid excitation motor

Abstract

The invention discloses a multi-objective optimization method for a novel consequent-pole brushless hybrid excitation motor, relates to the field of excitation motors, and aims to optimize an iron core pole arc angle, an outer-layer air gap non-uniformity degree, an outer stator yoke width, an outer stator notch width and an inner-layer air gap length of the motor by using the torque output and the magnetic regulation coefficient of the motor as optimization targets and adopting a layered optimization idea. According to the optimization scheme, the output torque of the motor is effectively improved, and the flux adjusting coefficient of the motor is increased. The novel consequent-pole brushless hybrid excitation motor is complex in topology and large in number of design parameters, and the optimization scheme combining the intelligent optimization algorithm and single-parameter independent optimization effectively solves the problem that in the optimization process of the motor, due to the fact that the number of the design parameters is large and the design parameters are coupled with each other, conflicts are easy to occur among the optimization objectives, and a global optimalsolution is difficult to obtain, and optimization efficiency is improved at the same time.

Description

technical field [0001] The invention relates to the field of hybrid excitation motors, in particular to a multi-objective optimization method of a novel alternating pole brushless hybrid excitation motor. Background technique [0002] Permanent magnet synchronous motors are widely used in the field of electric vehicle drive systems due to their high power density, high efficiency, and flexible drive. Hybrid excitation motor integrates the advantages of permanent magnet motor and electric excitation motor, which can expand the range of motor speed regulation. At the same time, the electric excitation source can undertake the main excitation function under the condition of permanent magnet demagnetization, which enhances the fault tolerance of the motor drive system. The new dual-stator alternating-pole brushless hybrid excitation motor combines the AC excitation winding and the alternating-pole structure to realize the brushless hybrid magnetic regulation. At the same time, b...

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Problems solved by technology

By combining intelligent algorithms and Pareto optimality, multi-objective optimization can be achieved without setting weighting factors, so as to obtain the global optimal solution, but at the same time, this solution has high computational costs, long search time, and low optimization efficiency

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