Optimization Design And Performance Analysis Of Hybrid Excitation Synchronous Motor For Electric Vehicle

The basic requirements of electric vehicle motor drive system are high efficiency,high torque density and wide speed range.As a new structure motor,the Hybrid synchronous motor is composed of permanent magnet pole and electric excitation pole.The excitation potential can be adjusted through the excitation winding.It has the characteristics of high efficiency of permanent magnet synchronous motor and adjustable air gap flux of electric excitation motor.It has been widely paid attention to and has great application prospects in electric vehicles and other wide range magnetic field.However,the rotor structure of hybrid excitation synchronous motor is very complicated with two excitation modes.Based on this,this paper focuses on the structural optimization design of hybrid excitation synchronous motors for electric vehicles.The main work contents are as follows:Firstly,the basic structure and operation principle of hybrid excitation synchronous motor are studied.The regulating principle of air gap magnetic field is analyzed,and the structure rationality of hybrid excitation synchronous motor is analyzed by finite element simulation.According to the ideal running state of electric vehicle,the performance of driving motor is analyzed,and the rated parameters of motor are determined.On this basis,in order to improve the optimization efficiency,response surface method agent model is selected.The basic principle and process of constructing response surface model were studied.The experiments were arranged through the central composite surface design method,and the second-order response surface function was selected to construct response surface model.The relationship between the objective function and the optimal design variables was obtained,and the accuracy of the constructed model was verified.Then,quantum genetic algorithm is selected on the basis of traditional genetic algorithm.Quantum genetic algorithm has the advantage of fast computation speed.The standard quantum genetic algorithm is improved by adding quantum crossover and mutation operations to improve the computational accuracy.The quantum genetic algorithm and the improved quantum genetic algorithm are tested by the standard test function,and the results prove the superiority of the improved quantum genetic algorithm.Finally,when the hybrid excitation synchronous motor is applied in the field of electric vehicle,it is expected that its vibration noise and torque fluctuation will be less.In order to further improve the rotor coupling ability of the motor,improve the performance of the motor,and reduce the torque ripple and vibration noise of the motor,the optimized design of four structural parameters,namely,the width and thickness of permanent magnet,the width of ferromagnetic pole and the height of ferromagnetic yoke,was carried out by using the improved quantum genetic algorithm to optimize the cogging torque of the motor.The finite element model was used to analyze the low speed performance,high speed performance and magnetic modulation performance of the optimized motor,and the effectiveness of the improved quantum genetic algorithm for the rotor structure optimization of the hybrid excitation synchronous motor and the superiority of the optimized motor are verified.