The utilization of the explicit model predictive (EMP) control method for direct speed control (DSC) of permanent magnet synchronous motors (PMSMs) achieves high-bandwidth speed control and excellent dynamic performance. However, the commonly used regular hexagonal current and voltage constraints restrict the motor's operational region, resulting in a narrow speed range and low load capacity. In addition, the conventional formula-based field-weakening method leads to undesirable allocation of $d$ - and $q$ -axis currents, reducing the degree of freedom in adjusting the motor's operating point. These drawbacks restrict the EMP-DSC method's application in the motor's extreme operation. Therefore, this article proposes an expanded limit boundary EMP-DSC method to realize cascade-free speed control with a wider speed range and higher load capacity. First, the proposed method constructs irregular hexagonal constraints, expanding the limit boundary of the motor's operational region in the $i_{\mathrm{d}}$ – $i_{\mathrm{q}}$ plane to broaden the speed and load ranges simultaneously. Then, based on these new constraints, an easily implementable optimal-trajectory field-weakening method is skillfully designed to optimize the current distribution, maintain the operating point near the optimal position, and improve field weakening performance. The proposed method enhances the competitiveness of EMP control in motor servo drive fields, and its feasibility is verified by experiments.

In the past decade, model predictive control (MPC) has been widely used in AC motor drives. Although a series of improved MPC strategies have been proposed, researchers are still seeking more effective solutions for different application backgrounds and application requirements to achieve the goals such as algorithm simplification, weighting factor design, parameter robustness enhancement, current/torque ripple suppression, and so on. In this paper, aiming at the above problems, the MPC strategy and its optimisation technology for AC motor drive system are comprehensively reviewed. Firstly, this paper introduces the classical MPC technology with the permanent magnet synchronous motor drive system fed by two‐level voltage source inverter as the control object. Secondly, this paper introduces and discusses the existing MPC optimisation methods from the aspects of current/torque ripple suppression, algorithm simplification, weight factor design and parameter robustness enhancement. Finally, based on the current industrial development requirements for AC motor drive systems and the research status of MPC optimisation methods in the existing literature, the current challenges and future trends of MPC technology are discussed.

Compared with other topologies, the modular multilevel converter (MMC) has the advantages of higher scalability and lower harmonic distortion. When carrier-based pulse-width modulation approaches are used for the MMC, the number of carriers increases for more sub-modules, and the complexity of the control and the memory required increases as a result. In addition, the synchronization of several carriers is another issue. Due to the unique constructional characteristics of the MMC, circulating currents will be generated internally, causing distortions in the arm currents and, thus, unnecessary converter losses. In this paper, an improved 2N+1 pulse-width modulation approach with low control complexity and a circulating current suppression strategy are proposed. Firstly, the conventional carrier phase-shifted 2N+1 pulse-width modulation approach is improved so that the number of carrier signals adopted in each arm is always two. Secondly, the redundant switching states are used to suppress the circulating current. Finally, the effectiveness of the proposed strategy is verified experimentally. The results show that the proposed method reduces the control complexity while retaining the output performance. Meanwhile, the circulating current can be suppressed.

This study constructs a power switching device open-circuit fault diagnosis model for a three-level neutral point clamped inverter based on the multi-scale shuffled convolutional neural network (MSSCNN) and extracts and classifies the fault information contained in the output current of inverters. The model employs depthwise separable convolution and channel shuffle techniques to improve diagnostic accuracy and reduce model complexity. The experimental results show that the new model has lower model complexity, better noise resistance and higher average diagnostic accuracy compared with fault diagnosis models based on CNN, ResNet, ShuffleNet V2 and Mobilenet V3 networks.

In this paper, a high-precision sensorless control strategy is proposed for the high-speed permanent magnet synchronous motor (HSPMSM). The strategy is based on the prediction methodology and utilizes the HSPMSM mathematical model with filters. On the one hand, a continuous variable boundary-layer sliding mode observer (CVBSMO) is developed to mitigate the buffeting problem caused by rapid sliding mode motion. On the other hand, a position error feedforward compensation method is proposed to enhance the accuracy of HSPMSM position estimation, accounting for various delays and inverter nonlinearities. These two combinations perfectly overcome the influence of non-ideal factors on position estimation, effectively. It can obtain the total position estimation error without necessitating additional controllers and is highly practical. The control performance of the proposed strategy is verified on a 1.1kW, 30000r/min HSPMSM experimental platform, and compared to the traditional method. The experimental results demonstrate the feasibility and effectiveness of the proposed strategy.