Research On Vector Control Of Vehicle PMSM Based On Parameter Identification

With the rapid development of pure electric vehicles in recent years,interior permanent magnet synchronous motor has been more and more widely used as pure electric vehicle drive motor because of its excellent performance.The control quality of the motor controller affects the safety,comfort and power of the vehicle.Faced with the complex driving conditions,it is very important to be able to accurately and quickly respond to the required output torque of the vehicle.So efficient control methods and motor parameter identification technology have become a hot spot for electric vehicle electronic control system.In this paper,an IPMSM of a car as the controlled object is carried out the following aspects of research:First of all,this paper retrieves a number of related databases for the contents of the subject,and collects a lot of relevant information,as well as summarizes the PMSM parameter identification methods,and analyzes the current research situation at home and abroad.Secondly,according to the characteristics of electric vehicle,the mathematical model of IPMSM is established,and the current vector control strategy is chosen,and the MTPA and the flux-weakening control method are proposed and analyzed.In addition,the double closed loop control system including current loop and velocity loop is built,and the effective feasibility of the control strategy and model is proved by simulation test,which provides theoretical support and model carrier for the design of parameter identification method of IPMSM.Based on the mathematical model,the method of off-line identification of IPMSM parameters is given,and the adaptive law of online identification of IPMSM parameters is deduced by Popov 's hyperstability theory.In the absence of additional test signal,the adaptive law can identify the direct axis inductance,quadrature axis inductance,rotor flux and stator resistance,and verifies the theoretical correctness and feasibility of the method by simulation experiment.Because the identification speed of model reference adaptive method is slow,this paper proposes two improved methods based on MRAS.The first method is to combine MRAS with neural networks.Firstly,the results of MRAS identification as training samples are used to train the neural network,and the trained neural network model is used to identify the motor parameters online.Another method is to use the double-layer structure ANN instead of MRAS adjustable model,with the weight adjustment to replace the adaptive mechanism,that is,using the error backtracking algorithm instead of adaptive mechanism,and the process of parameter identification is the neural network learning process,without training in advance.Through the analysis of the above three kinds of online identification method simulation results,it is found that the third method of parameter identification is more quick and accurate.Then,the influence of inductance and flux change on MPTA control strategy is analyzed,and the identification quantity is fed back into the model of motor control.Finally,the experimental platform of IPMSM drive control system with Infineon TC1782 as the core control chip is built,including the hardware and software development of the control system.The feasibility of the identification method and the accuracy of the vector control are proved by experiments.