The performance of flux-weakening controllers in the multiphase permanent magnets (PM) machines depends on the accurate fundamental voltage limit derivation, and the minimal copper loss design in the flux-weakening operation region has not been well discussed. In this article, the accurate fundamental voltage limit with considering harmonic current suppression is derived at first. Then, two control concepts are addressed, and the corresponding flux-weakening control strategies are designed with the gradient descent method. In the first control strategy, both the fundamental and harmonic voltage vectors are feasible, resulting in the larger amplitude of the phase currents. The second control strategy obtains higher bus voltage utilization by an additional transition stage. At the same time, the harmonic currents cannot be further suppressed in the flux-weakening operation region. Third, the copper loss per electrical cycle is calculated, and a switching scheme is designed to obtain lower copper loss in the flux-weakening operation region. Finally, both strategies are successfully implemented in a dual three-phase PMSM. Moreover, the proposed switching scheme obtains minimal copper loss in the whole flux-weakening operation region.

In this article, an improved hybrid particle swarm optimization (IHPSO) algorithm is proposed to solve the optimization problem of controller parameters in the design of a permanent magnet synchronous motor (PMSM) servo system. The proposed algorithm presents the directional mutation operation to the particles, which fixes the position of some particular particles so as to enhance the searching ability to some remote regions. In order to cooperate with directional mutation operation, the updating formula of particles velocity is ulteriorly improved. Then, the proposed IHPSO algorithm is adopted to optimize parameters of the designed controller. A simulation and an experimental platform of the PMSM servo system are designed using a biological intelligence controller based on hormone regulation for the speed control and feedforward compensation for the position controller, where IHPSO is applied to the parameter optimization for speed and position controllers, which validate the effectiveness of the IHPSO algorithm and the designed control system.

Energy routers are indispensable in deploying energy Internet for electric vehicles (EVs), which flexibly handle the power flow regulation. Combined with the excellent characteristic of wireless power transfer technology for noncontact energy transmission, this article proposes a novel wired/wireless hybrid multiport energy router (HMER) for future EV energy Internet. First, multiple bidirectional power ports are provided to control the power flow among the grid, various dc power sources, and EVs. Moreover, with grid-tied and islanded operations, the proposed HMER enables dynamic wireless energy exchange for EVs on the move. When moving along the energy exchange lane, the EVs can receive power from the HMER and conduct energy feedback, relieving mileage anxiety while creating economic benefits. Furthermore, a mathematical model of the system is derived, and a control algorithm is introduced to perform decoupled power control for each transceiver. Finally, a SIC experimental prototype is constructed to verify the effectiveness of the proposed HMER system. Experimental results prove the transceivers can get bidirectional wireless energy interconnection on the energy exchange lane in both grid-tied mode and islanded mode, and each transceiver can realize independent power regulation.

In this article, we propose a novel cascaded adaptive deadbeat (CADB) control method for permanent magnet synchronous motor drives. First, an adaptive deadbeat (DB) based current controller is proposed with a simplified first-order current loop dynamic model. The motor parameters are compressed into few identifiable coefficients, and an improved gradient method with an adjustable gain factor is employed to identify these time-varying coefficients. Therefore, there is no need to design an extra observer to obtain specific motor physical parameters. Next, on the basis of the differential equation solving method, a similar model of speed loop is presented and adopted for the design of an adaptive speed controller. A robust DB-based tracking control law and a feedback control law are applied to the proposed adaptive controller. The stability of the proposed adaptive controller is confirmed by using the Lyapunov theorem. Finally, the proposed CADB control system is experimentally carried out in the steady state and transient state. The test results indicate that the system has good dynamic performance and robustness to the disturbance of parameters and loads.

A dual permanent magnet synchronous motor (PMSM) system, driven by a five-leg voltage-source inverter, is considered a feasible option for low-cost and fault-tolerant applications. The finite-control-set model predictive control schemes without modulators generate a heavy computational burden and larger current ripple. In this article, an improved predictive control method with a space vector modulation (SVM) scheme is proposed for independent control of a dual-motor system. First, the expected voltage vectors (VVs) of dual motors are obtained with a deadbeat solution, which yields a faster dynamic response. Then, in order to reduce the current ripple and eliminate the candidate VV traversal process, an improved modulator with adaptive overmodulation is adopted to synthesize the expected VVs. The presented SVM method solves the problem caused by the conflicting switching-state demands of the common leg by dual PMSMs. Moreover, an extensive comparison is performed among the proposed control method, the existing model-based control methods, and the field-oriented control method with a proportional–integral controller. All methods are experimentally carried out in steady and transient states. The test results indicate that the proposed control scheme with adaptive overmodulation can effectively reduce current ripple, improve voltage utilization, and preserve good dynamic performance.

There is recognized interest in in-wheel motors for vehicle traction. Studies have gradually focused the design of in-wheel motors on electro-mechanical vibration, subject to the demand of driving comfort. It is crucial to model, analyze, and minimize the air-gap exciting force, the dominant source of vibration. In order to qualitatively and quantitatively study the air-gap vibrational exciting force and evaluate its characteristic for an in-wheel outer-runner permanent magnet synchronous machine (PMSM), this research proposes an air-gap permeance model (APM) and a unique adaptive reluctance network model (ARNM). In the process of motor design, APM is a quick means of determining dominant radial force density (RFD) harmonics and minimizing specific components that may produce considerable vibration. Morphing surface-mounted magnets and nonuniform air-gap length are guided by design optimization which complicates the analysis. Yet, proposed ARNM can account for this geometry variation and handle deformed gap geometry by using modified equation-based local permeance and residual flux. The speed and accuracy of proposed model are verified through the comparison of flux density and force mapping data between the calculation by proposed analytical model and the simulation by finite element tools. A 3-kW prototype is fabricated and tested to explore the effectiveness of ARNM-based performance prediction.