Fault-tolerant deadbeat model predictive current control for a five-phase PMSM with improved SVPWM

Abstract

The main drawbacks of traditional finite set model predictive control are high computational load, large torque ripple, and variable switching frequency. A less complex deadbeat (DB) model predictive current control (MPCC) with improved space vector pulse-width modulation (SVPWM) under a single-phase open-circuit fault is proposed. The proposed method predicts the reference voltage vector in the α-β subspace by employing the deadbeat control principle on the machine predictive model; thus, the exhaustive exploration procedure is avoided to relieve the computational load. To perform the constant switching frequency operation and achieve better steady-state performance, a modified SVPWM strategy is developed with the same conventional structure, which modulates the reference voltage vector. This new approach is based on a redesigned and adjusted post-fault virtual voltage vector space distribution that eliminates the y-axis harmonic components in the x-y subspace and ensures the generation of symmetrical PWM pulses. Meanwhile, the combined merits of the DB, MPCC, and SVPWM methods are realized. To verify the effectiveness of the proposed control scheme, comparative experiments are performed on a five-phase permanent magnet synchronous motor (PMSM) drive system.

Time-domain Dynamic-performance-improvement Method for Pulse-width-modulated DC-DC Converters Based on Eigenvalue and Eigenvector Sensitivity

“…For the left eigenvector, the left eigenvector sensitivity ∂ψ i T /∂b can be calculated by simply replacing all the closed-loop Jacobian matrices A cl in Eq. (10) with their transpose T cl A and replacing the right eigenvector with the transpose ψ i of the left eigenvector.…”

“…Although an LQR can also be designed to improve the time-domain dynamic performance by incorporating settling time and overshoot into the linear quadratic function, it requires full-state feedback, which increases the complexity of the control system. Other control methods based on discrete control, such as deadbeat control [9][10] , adjust the duty cycle based on the principle that the controlled variable of the next digital control cycle should be equal to the reference value. Deadbeat control can theoretically achieve a dynamic adjustment of the converter within a limited number of steps in digital control.…”

Three‐vector model‐free predictive control for permanent magnet synchronous motor

“…The above analysis and Equation (5) indicate that the existence of dead-zone can cause an error between the ideal output voltage and actual output voltage, which mainly depends on the duration of the dead-zone time and the direction of the phase current.…”

“…Model predictive control (MPC) has advantages such as good control effect and high current tracking accuracy, and is widely used in the field of motor control [3, 4]. MPC can be divided into Continuous Control Set Model Predictive Control (CCS‐MPC) [5, 6] and Finite Control Set Model Predictive Control (FCS‐MPC) [7, 8]. Although CCS‐MPC has better robustness when parameters change, it has drawbacks such as high computational complexity and slow response [7].…”

Model Predictive Torque Control for a Dual Three-phase PMSM Using Modified Dual Virtual Vector Modulation Method

“…Permanent magnet synchronous motors (PMSMs) have been widely utilized in several high-performance applications owing to their advantages of high efficiency, high torque density, and negligible size [1][2] . An increasing number of multiphase motors, especially six-phase motors, have been applied in applications requiring high-power output at lower voltage and strong fault-tolerant capability, such as electric aircraft, electric vehicles, and railway traction [3][4][5][6][7] . Notably, the torque ripple of the asymmetrical dual three-phase PMSM is lesser than that of the symmetrical six-phase PMSM, which has garnered the attention of engineers.…”