Permanent magnet synchronous motor (PMSM) drive has emerged as one of the most preferred motor drives for industrial applications owing to its distinguished advantages such as high torque density, high efficiency, and wide speed range operation. However, accurately updated knowledge about the PMSM parameters is crucial to designing a high-performance trajectory tracking controller. This paper presents a state-of-the-art comprehensive review and up-to-date progress of the offline and online parameter estimation techniques of the PMSM drives. First, the problems associated with parameter estimation of the PMSM are systematically summarized to identify the parameters having fast and accurate convergence. Second, the offline parameter estimation techniques are categorized based on the frequency and time responses. Third, the recent advances and developments of the online parameter estimation techniques for PMSMs are assessed. Finally, there is a discussion of extensive industrial applications and future research trends for the parameter estimation techniques.

The increasing emissions created by the large-scaled number of automobiles around the world pose severe threats to modern life by causing global warming issues and deteriorating air quality. These serious issues stimulate the essential demand for cleaner, safer, and more efficient vehicles, such as battery electric vehicles (BEVs). Unlike other studies on the charging technologies of BEVs, this paper gives a comprehensive state-of-the-art review on the charging technologies available for BEVs: wired charging and wireless charging technologies. First, the wired charging technologies are systematically classified into AC charging (indirect charging) and DC charging (direct charging) methods based on how the BEVs batteries are fed from the grid. Next, the configurations and commonly used topologies of wireless charging technologies for BEVs are thoroughly discussed. The leading institutes/companies driving advancements in both technologies are also acknowledged. Finally, this paper extensively highlights the recent and future research trends along with the industrial applications.

Due to the continuously increasing demand on switched-mode power converters (i.e., dc-dc, dc-ac, ac-dc, and ac-ac) that can achieve high efficiency at high switching frequency, soft-switching techniques have received much attention in the area of power converter applications over recent years. This article provides a comprehensive review of the state-of-the-art soft-switching techniques used to achieve the zero-voltage switching and zero-current switching supplied by power switching devices. First, the auxiliary-circuit-based and nonauxiliary-circuit-based techniques that perform soft switching are systematically classified according to power converter. Next, soft-switching techniques for each power converter are comprehensively classified and reviewed in detail. Unlike the existing review papers that only categorize the soft-switching techniques used in dc choppers and inverters, this article offers further helpful categorization for all types of power converters. Further, it provides the merits, demerits, and suitable applications for each soft-switching technique. Finally, it suggests future research issues for soft-switching techniques in power converters.

This paper designs a simple model reference adaptive control based speed controller (MRAC-SC) for a surface-mounted permanent magnet synchronous motor drive. The proposed adaptive scheme is designed to track a reference model that ensures the desired exponential decay of a controlled speed error trajectory. Also, the proposed MRAC method includes an adaptive compensating control term and a stabilizing feedback control term. The former is proposed to compensate for uncertain model parameters (i.e., inertia, friction, and load torque) and the latter is constructed to asymptotically stabilize the error dynamics. The asymptotic stability of the closed loop is guaranteed with both control terms using the Lyapunov approach. The comparative studies between the proposed MRAC-SC, the nonadaptive model reference speed controller, and the conventional proportional-integral SC are performed to justify a fast transient response, a good tracking possibility, and robustness against the parameter uncertainties of the proposed MRAC technique.

This paper proposes a finite control set model predictive control (FCS-MPC) to guarantee the stability and robustness for surface-mounted permanent magnet synchronous motor (SPMSM) drives. Continuous-input-based control laws are first developed from a control-Lyapunov function in order to both stabilize the closed-loop system via feedback control laws and ensure the robustness via online adaptive laws. Because the asymptotic stability of the proposed control method is guaranteed by at least one discrete switching-state, the continuous-input-based control laws are converted into relevant constraints of the FCS-MPC optimization problem. To validate the advantages of the proposed FCS-MPC, comparative studies with the conventional FCS-MPC and space vector modulation based adaptive control are conducted on a prototype SPMSM testbed with a TI TMS320F28335 DSP. The effectiveness of the proposed FCS-MPC is verified by the comparative schemes with/without the additional constraints. Superiority of the proposed schemes such as zero steady-state error, fast speed-tracking capability, well-regulated stator currents, and low average switching frequency are experimentally validated under the step-changes of load torque and speed reference.

This paper proposes an effective model predictive control (MPC) scheme using a modulated optimal vector (MOV) and finite control options for a three-phase inverter with an LC filter. Unlike other MPC methods, the proposed MPC strategy exploits the unconstrained optimal vector (OV) of the continuous-control-set (CCS) MPC to limit the control options for the unconstrained mode. First, the analytical OV is derived based on a least-squares optimization. If the input constraints are not violated, the OV is applied with a space vector modulation (SVM) technique like the CCS-MPC. Otherwise, the OV is scaled into the MOV and only three control options are online evaluated to reselect the control input. Experiments are conducted on a three-phase inverter test bed with a TI TMS320F28335 digital signal processor to validate the improvements of the proposed method, especially the robust performances and fast responses. The comparative results with the FCS-MPC show the superior performances of the proposed scheme with smaller steady-state error and lower total harmonic distortion due to the analytical OV with SVM, more robustness to parameter uncertainties due to the disturbance observer, and faster dynamic response due to the online reselection of control inputs.