Electric motors play a crucial role in modern industrial and domestic applications. With the trend of more and more electric drives, such as electric vehicles (EVs), the requirements for electric motors become higher and higher, e.g., high power density with good thermal dissipation and high reliability in harsh environments. Many efforts have been made to develop high performance electric motors, such as the application of advanced novel electromagnetic materials, modern control algorithms, advanced mathematical modeling, numerical computation, and artificial intelligence based optimization design techniques. Among many advanced magnetic materials, soft magnetic composite (SMC) appears very promising for developing novel electric motors, thanks to its many unique properties, such as magnetic and thermal isotropies, very low eddy current loss, and the prospect of low-cost mass production. This paper aims to present a comprehensive review about the application of SMC for developing various electric motors for electric drives, with emphasis on those with three-dimensional (3D) magnetic flux paths. The major techniques developed for designing the 3D flux SMC motors are also summarized, such as vectorial magnetic property characterization and system-level multi-discipline robust design optimization. Major challenges and possible future work in this area are also discussed.

One of the keys to the success of the fourth industrial revolution (Industry 4.0) is to empower machinery with cyber–physical systems connectivity. The digital twin (DT) offers a promising solution to tackle the challenges for realizing digital and smart manufacturing which has been successfully projected in many scenes. Electrical machines and drive systems, as the core power providers in many appliances and industrial equipment, are supposed to be reinforced on the verge of Industry 4.0 in the fields of design optimization, fault prognostic and coordinated control. Therefore, this paper aims to investigate the DT modelling method and the applications in electrical drive systems. Firstly, taking the high-speed permanent-magnet machine drive system as an example, multi-disciplinary design fundamentals and technologies, aiming at building initial mechanism and simulation models, are reviewed. The state-of-the-art of DT technologies is figured out to serve for high-precision and multi-scale dynamic modelling, by which a framework for DT models of electrical drive systems is presented. More importantly, fault diagnosis and optimization strategies of electrical drive systems in the decision and application layer are also discussed for the DT models, followed by the conclusions presenting open questions and possible directions.

As we face issues of fossil fuel depletion and environmental pollution, it is becoming increasingly important to transition towards clean renewable energies and electric vehicles (EVs). However, designing electric motors with high power density for EVs can be challenging due to space and weight constraints, as well as issues related to power loss and temperature rise. In order to overcome these challenges, a significant amount of research has been conducted on designing high-power-density electric motors with advanced materials, improved physical and mathematical modeling of materials and the motor system, and system-level multidisciplinary optimization of the entire drive system. These technologies aim to achieve high reliability and optimal performance at the system level. This paper provides an overview of the key technologies for designing high-power-density electric motors for EVs with high reliability and system-level optimal performance, with the focus on advanced magnetic materials and the proper modeling of core losses under two-dimensional or three-dimensional vectorial magnetizations. This paper will also discuss the major challenges associated with designing these motors and the possible future research directions in the field.

This article presents improved iron loss analytical prediction models for interior permanent magnet synchronous motors (IPMSMs) used in electric vehicles. The effects of slotting harmonics, pulsewidth modulation (PWM) carrier harmonics, temperature rise, and mechanical stress are considered in the proposed models. Specifically, by investigating the stator flux density as piecewise linear with trapezoidal waveform, the iron losses in the teeth and yoke regions are calculated separately, considering the different magnetic field distributions and waveforms. To deliberate the PWM harmonic influence, a correction coefficient is added to the hysteresis loss models, while the eddy current loss models are updated by summing all the eddy current losses caused by the power supplying current harmonics. Moreover, the coupling interaction effects of magnetic, thermal, and stress fields on the empirical coefficients of hysteresis and eddy current losses are analyzed in detail and also implemented in the iron loss prediction process. The feasibility and superiority of the proposed models are verified by numerical and experimental case studies on an IPMSM prototype.

During the lifecycle of an electric drive system, the electricity cost usually constitutes a dominant portion, leading to extensive research on improving the efficiency of such systems. This article presents an efficient design optimization strategy for permanent magnet synchronous motor (PMSM) drive systems, cooperating with an improved loss minimization control, targeting to reduce the system power loss and improve the overall operating performances. Specifically, a generalized equivalent circuit model with a novel topology that considers rotating magnetization effects is first proposed to accurately predict the core loss of PMSMs under both no-load and load conditions. Moreover, after analyzing the copper and inverter losses, an integrated system-level loss model of the PMSM drive system is developed, based on which an improved loss minimization control is implemented through deriving the relationships among the electromagnetic torque, d-axis and q-axis currents. Then, the system-level optimization strategy that incorporates both the motor and control sides is presented, aiming to maximize the torque and efficiency and minimize the torque ripple and speed overshoot. Finally, a multilevel algorithm based on sensitivity analysis is employed to solve the multiobjective optimization models with reduced calculation costs. Extensive experimental and simulation verifications are demonstrated with a 20 kW interior PMSM drive system platform. Results show that the optimized drive system has promoted steady-state and dynamic behaviors, and the proposed loss minimization control can comprehensively reduce the system losses by about 3.25%.

With the increasing demand for smaller, lighter, and more affordable electromagnetic devices, there is a growing trend toward developing high-power-density transformers and electrical machines. While increasing the operating frequency is a straightforward approach to achieving high power density, it can lead to significant power loss within a limited volume, resulting in excessive temperature rise and device degradation. Therefore, it is crucial to design high-power-density electromagnetic devices that exhibit low power loss and efficient thermal dissipation to address these challenges. Advanced techniques, such as the utilization of novel and advanced electromagnetic materials, hold great promise for overcoming these issues. Specifically, nanocrystalline and amorphous magnetic materials have emerged as highly effective solutions for reducing power loss and increasing efficiency in electromagnetic devices. This paper aims to provide an overview of the application of nanocrystalline and amorphous magnetic materials in transformers and electrical machines, along with key technologies and the major challenges involved.