Computationally efficient model predictive control of three‐level open‐end winding permanent‐magnet synchronous motor drive

Abstract

The model predictive current control (MPCC) is popular and widely used method for permanent‐magnet synchronous motor (PMSM) and the tuning of weighting factor in classical cost function (CF) of MPCC of PMSM is not required. A three‐level inversion‐fed open‐end winding PMSM (OEW‐PMSM) would produce lesser torque and stator flux ripples; however, computation time required for the prediction of control variables is large. This study proposes a control method to three‐level inversion‐fed OEW‐PMSM for reduction of computational time without affecting the performance when compared with conventional MPCC. The proposed method uses a maximum four voltage vectors (VVs) instead of 19 VVs in three‐level conventional MPCC. The reduced VVs decrease the number of predictions and computational time for predictions. CF in terms of voltage is used, thereby eliminating the need to predict the currents and faster execution of algorithm is achieved. A higher sampling rate is possible to achieve using the proposed method; thereby, reducing the steady‐state ripples in developed torque and stator flux, and improving the percentage total harmonic distortion of stator current. The effectiveness of the presented control method is practically verified after comparing its computational time, steady‐state response and dynamic response with that of three‐level conventional MPCC.

High-precision angle adaptive control simulation of synchronous motor for automatic lifting and boarding equipment of aircraft platform

“…The results are as follows. At the same time, in order to further illustrate the control performance advantages of the method in this paper, the enhanced emotion and speed deviation control method of synchronous reluctance motor driver in reference 8 and the calculation effective model predictive control method of permanent magnet synchronous motor drive in reference 9 are used as the comparison method, and the method in this paper and the two comparison methods are compared to verify the performance of the method in this paper.…”

“…The controller was designed based on the emotion learning and decision-making mechanism in the brain through emotion clues and sensory input, which can accurately track the speed and d-axis stator current reference, but this control method leads to poor operation stability of synchronous reluctance motor. The error of reverse operation is large.Petkar and Kumar et al studied the predictive control method driven by three-level open winding permanent magnet synchronous motor based on computational effective model 9 . For the open winding permanent magnet synchronous motor powered by three-level inverter, it will produce small torque and stator flux fluctuation.…”

“…( 6) and ( 7) that the ideal transmission ratio can be changed by the rotation speed of the synchronous motor in the automatic lifting and boarding equipment of the aircraft platform. If the rotation angle is too sensitive, it is difficult to determine the specific value of the rotation speed during the rotation angle of the synchronous motor in the automatic lifting and boarding equipment of the aircraft platform, so a rational state can be set 9 , the speed s can be set to 0 to obtain: where I min represents the value of ideal transmission ratio when the angular speed of synchronous motor in automatic lifting and boarding equipment of aircraft platform is 0; ξ i max represents the angular speed under critical state when the synchronous motor in the automatic lifting and boarding equipment of aircraft platform runs to the maximum value; i max represents the angular movement distance under critical state when the synchronous motor in the automatic lifting and boarding equipment of aircraft platform runs to the maximum value. Thus, the ideal transmission ratio of synchronous motor in automatic lifting and boarding equipment of aircraft platform can be obtained.…”

Sampling error‐based model‐free predictive current control of open‐end winding induction motor with simplified vector selection

“…Therefore, the reduction of the computations is more challenging in this structure, and the methods in Refs. [32][33][34], which decrease the calculations of the dual inverter with two isolated DC sources, cannot be applied to it.…”

“…On the other hand, the application of the FS-MPC in the dual inverters demands a high computational burden because the dual inverter has a high number of feasible voltage vectors (VVs). Several articles have been published, aiming to reduce the computational burden of the FS-MPC in the application of dual inverters with two isolated DC sources [32][33][34]. Also, the methods in Refs.…”