Research On Fault Analysis And Diagnosis Of Electric Vehicle Drive Motor

The depletion of fossil energy and the increasing environmental pollution have caused governments around the world to attach importance to the development of new energy vehicles.Governments have launched a schedule for banning the sale of fuel vehicles.Electric vehicles have become the main representative of new energy vehicles and become the focus of various car enterprises research and promotion.As the driving part of electric vehicle,the motor is the power source of the whole vehicle.The operation performance and electrical characteristics of the motor determine the performance of the entire electric vehicle.If the permanent magnet synchronous motor of the electric vehicle breaks down,it will directly affect the performance of the electric vehicles,and even cause serious traffic accidents,which will pose a serious threat to the property and life safety of drivers and passengers.This paper analyses and studies the diagnosis methods of the possible faults of the electric vehicle drive motor,which can timely find the faults of the electric vehicle drive motor,and it is of great significance to the development of the entire electric vehicle.Combined with the operating conditions and characteristics of electric vehicles,this paper analyzes the operating principle and characteristics of permanent magnet synchronous motor used in electric vehicles,the mathematical model of permanent magnet synchronous motor under normal conditions,the factors that cause the failure and the fault diagnosis strategy,and analyzes the three faults of the rotor inter-turn short circuit,loss of excitation and eccentricity of permanent magnet synchronous motor.Based on the fault characteristics,a fault model is constructed.A fault diagnosis method of permanent magnet synchronous motor based on improved wavelet packet decomposition and CSA-BPSO is proposed,and the improved wavelet packet decomposition and CSA-BPSO are applied to the design of permanent magnet synchronous motor fault diagnosis system.First of all,the development of electric vehicles under the background of the current energy crisis and increasing environmental pollution is analyzed,and the significance of fault diagnosis research on permanent magnet synchronous motor as the main driving motor of electric vehicles is summarized.This paper analyzes the mathematical model of permanent magnet synchronous motor,including the static model and the model after coordinate transformation,and analyzes the voltage equation,magnetic linkage equation,torque equation and motion equation in each coordinate system.According to Clark transformation and Park transformation,the permanent magnet synchronous motor model in the coordinate system is obtained.Secondly,this paper focuses on three faults that may occur in the permanent magnet synchronous motor: inter-turn short circuit,loss of magnetic field and eccentricity,and analyzes the characteristics of these three faults in the rotor of permanent magnet synchronous motor.The fault radar map is drawn according to the fault eigenvalues generated by different faults.The equivalent circuit and the lumped parameters of the fault model in the event of a fault are studied,and the diagnosis models of the rotor inter-turn short circuit fault,loss of excitation fault and eccentric fault of the permanent magnet synchronous motor are established based on the fault eigenvalues,and the methods of fault diagnosis with different fault characteristics and spectrum characteristics are given.Finally,the improved wavelet packet decomposition and the improved binary particle swarm optimization algorithm based on chaos-simulated annealing are analyzed,and the fault diagnosis method of drive motor is designed based on the improved wavelet packet decomposition and the characteristics of CSA-BPSO.The principle of wavelet transform and wavelet packet energy spectrum are introduced,and the wavelet transform algorithm and fault signal feature vector extraction based on energy spectrum are analyzed emphatically.In order to solve the problem that binary particle swarm optimization algorithm is premature and easy to fall into local convergence,an improved binary particle swarm optimization algorithm based on chaos-simulated annealing is proposed based on the approximate random search property and ergodic property of chaos;The related algorithm tests show that the Chaos-simulated annealing improved binary particle swarm optimization algorithm can optimize the search speed of the optimal solution,avoid the simulated annealing failure,and improve the global search ability of the algorithm;Based on the research of chaos-simulated annealing improved binary particle swarm optimization algorithm,the drive motor fault diagnosis method based on wavelet packet analysis and CSA-BPSO is studied.The fault diagnosis CSA-BPSO algorithm flow,the fault diagnosis system structure based on wavelet packet analysis and CSA-BPSO and the drive motor fault diagnosis flow are given.The overall structure of the fault diagnosis system and the hardware block diagram of the control system are designed,and the realization circuit of the main functional modules of the fault diagnosis system with STM32F103 as the core main control module is given.