This article proposes an efficient surrogate-assisted design optimization method based on a multicriteria optimal Latin hypercube design (LHD) for multi-objective optimization of a surface-mounted permanent-magnet vernier machine (SPMVM). An improved iterated local search (ILS) method is proposed to optimize the spatial distribution uniformity and orthogonality of LHDs so that the data feature over the wide ranges of optimization variables can be captured more efficiently. Using the optimal LHD, a highly generalizable surrogate model can be trained with fewer samples, thus greatly reducing the required number of finite element analysis (FEA) cases and improving the optimization efficiency. A prototype corresponding to the optimal design is built and measured to validate the proposed method.

This article proposes a continuous control set predictive speed control (CCS-PSC) strategy for surface-mounted permanent magnet synchronous motor (SPMSM) drives, where the prediction horizon is short and the computational complexity is low. The optimization problem of the proposed CCS-PSC is formulated and analyzed. The current and voltage constraints are transformed into incremental voltage constraints, which can be updated in real-time. A reduced-order incremental model of SPMSM is adopted for the prediction, where integrators are naturally embedded. Hildreth’s quadratic programming algorithm is used to solve the optimization problem, where the active constraints are identified and the reference voltage is calculated. The performance of the proposed strategy is validated through comparative experiments with finite control set predictive speed control (FCS-PSC), cascaded CCS-PSC and field-oriented control. The results demonstrate the superb dynamic performance of the proposed CCS-PSC strategy, while the phase current total harmonic distortion is relatively low.

Optimal currents with appropriate harmonic components injected into the motor windings can effectively mitigate torque ripple for interior permanent magnet (IPM) type brushless DC motors (BLDCMs). However, existing approaches may fail to accurately inject the optimal currents into motors due to the limited current loop bandwidth. This paper proposes a simple enhanced generalized vector control strategy to mitigate the torque ripple for IPM-type BLDCMs. With the proposed vector control strategy, the control block diagram for IPM-type BLDCMs is as simple as that with traditional vector control for sinusoidal permanent magnet synchronous motors. Firstly, an electromechanical energy conversion voltage (EECV), considering the effects of the non-sinusoidal back-EMF and the rotor salience property, is proposed in $\alpha \beta$ -axis. Then, a novel coordinate frame is constructed with the proposed EECV, which is based on the arbitrary reference frame theory. As a result, the currents of IPM-type BLDCMs can be decomposed into two constant components, one being linked to the torque and the other one to the flux linkage. Thus, the bandwidth of current loop with simple proportional integral regulator can be equivalently expanded in the proposed coordinate frame. Finally, comprehensive experiments are conducted in different operation conditions to validate the effectiveness of the proposed vector control strategy.

In this article, an improved surrogate-assisted design optimization method is proposed and applied to the torque performance optimization of a five-phase surface-mounted permanent magnet machine with quasi-trapezoidal permanent magnets. It integrates the Taguchi and surrogate-assisted methods; the training data for surrogate models are generated by the Taguchi method to reduce reliance on the finite-element analysis (FEA), in turn, the local optimum problem caused by the Taguchi method is tackled by the surrogate model. The generalization ability of surrogate models is enhanced by the parameter transfer technique. Using the fuzzy best-worst method, the decision process of multiple solutions is placed before optimization so that the multiobjective optimization can be transformed into a single objective to facilitate the search process for the optimal design. The optimization results are validated by the test results from a prototype. Compared with the FEA-based parametric scanning method, the optimization cycle is shortened by 94% and a globally optimal design can be obtained.

The rapid development of ultra-high voltage direct current transmission systems has placed greater demands on the design optimization of transient parameters for large wound-field synchronous machines (WFSMs) in power systems, such as large synchronous condenser for dynamic reactive power compensation. This paper proposes a novel two-level surrogate-assisted multi-objective optimization method for WFSMs that can optimize transient parameters including per-unit reactance and time constants rapidly and accurately. To facilitate the manufacture of a prototype for verification, the proposed method is applied to the optimization of a WFSM for scale-down generator application. This method is employed to deal with the excessive number of design parameters, issues of multi-objective evaluation and strong coupling between objectives that either result in inaccuracy or become time-consuming by using conventional methods. To generate the training set for the surrogate model efficiently by finite element analysis, an improved arbitrary rotor position standstill time response (SSTR) method is employed to identify all transient parameters simultaneously in a single test, while Latin hypercube design is used to capture data features. The optimal WFSM designed by using the proposed method is prototyped and measured. It confirms that the proposed method can achieve high validity and high optimization efficiency simultaneously.

Large-scale direct-driven wind turbines are preferred for offshore wind generation from the viewpoint of cost of energy and system reliability. However, direct-driven generators of traditional technology are very difficult to be scaled up to a rated power of 10 MW or above. Superconducting generators offer a candidate to fill that gap. A feasible superconducting wind generator topology has rotor field windings made of superconductors and traditional copper stator windings carrying alterative currents. Nowadays, two kinds of superconductors are available in the market: the low-temperature superconductors (LTS) and the high-temperature superconductors (HTS). They have great differences in terms of material characteristics, product performance, price, and the relevant cryogenic and refrigeration system, which have a great influence on the design of superconducting generators. In this paper, a comparison study of superconducting wind generators with HTS and LTS rotor field windings is carried out, considering the performance and cost of superconductors and the cryogenic and refrigeration system. From the viewpoint of initial capital, technology maturity, and engineering feasibility, the LTS wind generator is recommended for subscale or full-sized prototype development in the near future.