Research On Maximum Torque Per Ampere Control Strategy Of Permanent Magnet Synchronous Motor

Permanent Magnet Synchronous Motor(PMSM)has been widely used because of its high power density and strong overload capacity.In the drive technology of PMSM,Maximum Torque Per Ampere(MTPA)can make full use of the inherent characteristics of the interior permanent magnet synchronous motor with unequal inductances in q-axis and d-axis.There is a reluctance torque component in the electromagnetic torque,which improves the torque output capacity and operation efficiency of the motor.Usually,the realization of MTPA control depends on accurate motor parameters,but in practical engineering applications,motor parameters will be affected by high temperature,magnetic saturation and other factors,which will lead to the deviation of MTPA control working point and reduce the accuracy of MTPA control.For this reason,taking the MTPA control of PMSM as the main research object,the vector control,forgetting factor recursive least squares parameter identification,MTPA control based on parameter identification and MTPA control based on gradient descent method are studied.The double closed loop vector control system of PMSM is designed with reference to the existing literature,and the MTPA control system is built on the basis of vector control.Because there are motor parameters in formula MTPA control,and the motor parameters will inevitably fluctuate in the actual operation,the influence of motor parameters on MTPA control trajectory is analyzed.In order to reduce the influence of motor parameter variation on MTPA control,a motor parameter online identification algorithm is added to the formula MTPA control.The recursive least squares parameter identification algorithm is deeply studied,but with the accumulation of time and the increase of iteration times of identification algorithm,there will be a problem of data saturation.To solve this problem,a forgetting factor recursive least square algorithm is designed.When the system is not stable,a smaller forgetting factor is used.And when the system is stable,a larger forgetting factor is used.Online identified parameters are applied to MTPA control to solve the problem of MTPA trajectory deviation caused by motor parameter changes.Although the combination of parameter identification algorithm and MTPA control based on formula solves the problem caused by the change of motor parameters during operation,parameter identification algorithm and the high-order operation in MTPA control based on formula will make the system too complex.Therefore,the MTPA control based on the gradient descent method is proposed.According to the geometric relationship of MTPA control points in dq frame,the angle between the constant torque direction and the current gradient is obtained,which can represent the position of motor operating point relative to the MTPA control point.According to the relative position,the q-axis and d-axis current commands are adjusted to move the motor operating point to the MTPA control point.Because the calculation of the angle between the constant torque direction and the current gradient involves the operation of inverse trigonometric function,the calculation process is more complex.The dot product of the constant torque direction and the current gradient can also represent the position of the motor working point relative to the MTPA control point,so the calculation process is simplified by using the scalar product instead of the included angle.The principle of MTPA control based on gradient descent method is simple and easy to implement,and the complex formula calculation and motor parameter identification algorithm are omitted.At the same time,the MTPA control can be realized more accurately.In order to verify the MTPA control algorithm based on online parameter identification and the MTPA control algorithm based on gradient descent,the simulation control systems are built in MATLAB / Simulink software.After the correctness and effectiveness of the proposed method are verified by simulation,the control method is verified by simulating the actual working conditions on the motor experimental platform,and the results show that the control method has high control performance.There are 55 figures,2 tables and 103 references in this thesis.