Abstract
This paper presents an improved control system for a small flux-switching permanent magnet motor (FSPM) to enhance its performance and torque sensing. The analytical magnetic circuit design was used to determine the related motor parameters, such as the air gap flux density, permeance coefficient (Pc), torque, winding turns, pole number, width, length, magnet geometry, and the current density of FSPM. The electromagnetic analysis of this motor was performed by software (ANSYS Maxwell) to optimize the motor performance. In this study, the performance of FSPM was investigated by the uniform design experimentation (UDE). For the control system, the model predictive current control (MPCC) is currently recognized as a high-performance control strategy, due to its quick response and simple principle. This model contained the nonlinear part of the system, to improve the torque ripple of FSPM. A modified MPCC strategy was proposed to improve the distortion of the current waveform and decrease the computational burden. The new modified control architecture was mainly composed of three parts, such as the estimation of electromotive force (EMF), current prediction, and optimal vector selection/vector duration. When the reference voltage vector was obtained, the three-phase duties were easily determined by the principle of space vector modulation (SVM). The results show the different strategy methods between the newly proposed modified MPCC and traditional proportional integral (PI) controller. In the control of FSPM, a modified MPCC strategy was able to achieve a better performance response and decrease the computational burden. At a low speed of 350 rpm, the proposed modified MPCC can achieve a better dynamic response. The nonlinear problem of the startup speed was also effectively resolved. The torque sensing performance of the simulation and the experimental test value were compared. The torque sensing performance of the simulation and the actual test value were also examined. In this study, the optimization focused not only on the motor design and fabrication, but also on an improved motor control strategy and torque sensing, in order to achieve the integrity of the FSPM system.
Highlights
With increasing demand for high-performance motors in various applications from aerospace and automotive to medical equipment, flux-switching permanent magnet (FSPM) motors have aroused considerable attention, due to their high-power densities and high efficiencies
This paper proposes a modified model predictive current control (MPCC) strategy to achieve a better dynamic performance and lower torque ripple
The control parameters for the current loops of the traditional proportional integral (PI) control architecture and the improved MPCC were the same, in which the phase margin was set as ~60◦, Kp was set as 3, and Ki was set as 3500
Summary
With increasing demand for high-performance motors in various applications from aerospace and automotive to medical equipment, flux-switching permanent magnet (FSPM) motors have aroused considerable attention, due to their high-power densities and high efficiencies. Based on the internal model of the system, MPC predicts the future behavior of controlled variables, such as current, torque, and stator flux. As only one voltage vector is applied during one control period, it produces relatively high steady-state ripples, and the current harmonics are distributed over a wide frequency range [27]. The cost function was sampled from eight sets of data, which is really time-consuming, and the control accuracy and the fast response were lacking It produced relatively high steady-state ripple, and current harmonics were distributed over a wide frequency range [27]. The proposed prediction voltage model considers the components of the inductor, which can effectively reduce the torque ripple caused by the reluctance torque of the FSPM motor. Based on the principle of SVM, when the reference voltage vector was obtained, the three-phase duties can be obtained
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