Optimal model predictive control method for double-inverter open winding induction motor

Abstract

The invention belongs to the technical field of double-inverter open winding induction motors, in particular to an optimal model predictive control method for a double-inverter open winding inductionmotor. The optimal model predictive control method comprises the following steps: (1) constructing a weightless factor value function; (2) studying and establishing a virtual ideal vector FCS-MPC; (3)and introducing a loss factor to construct a low switching frequency control strategy. The problem of high switching loss of OEWIM in high power applications can be analyzed and solved.

Description

technical field [0001] The invention belongs to the technical field of double-inverter open-winding induction motors, and in particular relates to an optimization model predictive control method for double-inverter open-winding induction motors. Background technique [0002] Double-inverter-fed open-winding asynchronous motor (OpenEndWindingInductionMotor, OEWIM) has been rapidly promoted and applied in high-power applications in recent years due to its high fault tolerance and ability to provide more levels. High-performance AC speed control methods include field-oriented control (FieldOrientedControl, FOC) and direct torque control (DirectTorqueControl, DTC). In FOC, good torque and flux linkage control of the motor can be achieved, but the internal current loop requires complex tuning , the simple control structure in DTC can achieve fast dynamic response, but the output torque ripple is large. [0003] Model predictive control (Model Predictive Control, MPC), as a contr...

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Problems solved by technology

High-performance AC speed control methods include field oriented control (FieldOrientedControl, FOC) and direct torque control (DirectTorqueControl, DTC). In FOC, good torque and flux linkage control of the motor can be achieved, but the internal current loop requires complex tuning , the control structure in DTC is simple to achieve fast dynamic response, but the output torque ripple is large

[0003] Model predictive control (Model Predictive Control, MPC), as a control strategy emerging in recent years, has the advantages of simple structure, fast dynamic response, and good control effect; currently, MPC is applied to high-performance closed-loop control of asynchronous motors, and good control effects are obtained. However, it is difficult to adjust the weight factor in the value function, which is not conducive to practical application; in order to solve this problem, a predictive current control is proposed, although the adjustment process of the weight factor is omitted, the output torque ripple of the motor is relatively large; and A non-weight factor MPC applied to permanent magnet synchronous generators is proposed. This method can solve the problem of weight factor tuning, but the calculation process is complicated and not applicable to OEWIM; a method based on multi-objective sorting analysis is also proposed to eliminate The purpose of the weighting factor, however, this method makes the forecasting process more complicated due to the complex mathematical derivation involved

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