Study On Motor Controller And Inductance Identification Of Electric Vehicle

At present,the global energy shortage and environmental problems are becoming more and more serious.In recent years,academia and industry are increasing the development of new energy vehicles to make new energy vehicles more stable,reliable and safe.The performance of electric vehicles is a key factor affecting its promotion,and the motor drive system is one of its core parts.This paper will mainly analyze and study the series of problems caused by the change of the parameters of the permanent magnet synchronous motor and its controller.The traditional vector control realizes the linear control of the AC motor,which makes the AC motor have the control performance of the DC motor and the static decoupling of the motor.Due to the inductance effect of the dq axis of the permanent magnet synchronous motor,there is still a cross-coupling relationship between the dq.When the dq-axis inductance parameter is known and does not change during operation,the current feedforward decoupling can achieve complete decoupling of the dq-axis current.However,the dq axis inductance of the permanent magnet synchronous motor will obviously change with the change of the operating conditions of the motor,resulting in unstable control performance and difficult to measure and control the inductance parameters in real time.To solve this problem,this paper uses a model reference adaptive algorithm based on Lyapunov function to identify the inductance parameters online,and an adaptive law based on Lyapunov function is designed to find the adjustable model and the reference model.The deviation of the rapid convergence of the Lyapunov function of zero quickly realizes the fast and accurate online identification of the dq-axis inductance parameters,and the identification results are applied to the dq-axis current feedforward decoupling and maximum torque-current ratio control,thereby improving The control performance of the motor is improved,and the robustness of the control system to the changes of the motor parameters is improved.At the same time,this paper also deeply analyzes the coupling relationship between the dq-axis current and the reason why the current feedforward decoupling is not complete.The method adopted in this paper achieves the complete decoupling of the dq-axis current.The stator current distribution caused by the salient pole effect of the built-in permanent magnet synchronous motor is analyzed,and the identification result is used to calculate the dq-axis current distribution to obtain the maximum torque-current ratio.In order to verify the effectiveness and feasibility of this method,the hardware design of the motor controller was studied in depth,part of the hardware design was carried out with the help of the company platform,and the motor controller control board and driver board were made.Using the method based on model design,the corresponding C language subroutine was generated in the Simulink environment and implanted in the motor control program.Finally,the experimental verification of the control of permanent magnet synchronous motors is carried out on the experimental platform.The theoretical analysis,simulation and experimental results are basically the same.The proposed algorithm can accurately identify the dq axis inductance parameters within 5 ms;the algorithm proposed in this paper is used Due to current feedback decoupling,the oscillation of the dq-axis current response process is significantly suppressed,and the electromagnetic torque ripple is less than 1.48%.The inductance identification result is used for maximum torque current ratio control.When the motor reaches the peak torque steady state,the three-phase stator current amplitude is reduced by 6.84%;the dq axis current dynamic decoupling and the maximum torque current ratio control inductance are solved The problems caused by the parameter changes verify the correctness and feasibility of the method proposed in this paper.