This paper presents a literature review on magnetic gears, highlighting the advantages of using these technologies for mechanical power transmission applications in wind energy conversion systems and transportation, such as in electric vehicles. Magnetic gear technologies have important advantages over their mechanical counterparts. They can perform the speed change and torque transmission between input and output shafts by a contactless mechanism with a quiet operation and overload protection without the issues associated with conventional mechanical gears. The paper describes the fundamentals and operating principle of the field-modulated magnetic gear topologies and investigates the magnetic torque transmission mechanism. However, despite all the advantages highlighted in different research and development reports, there is still no convincing evidence to show that magnetic gear technologies are an acceptable alternative for industrial applications. The aim of this paper is to summarize previous work on magnetic gears to identify the topologies most suited for mechanical power transmission systems in wind energy conversion systems and electric vehicle applications. These applications will show that research and development of magnetic gear technologies contribute significantly to solutions for sustainable systems, a subject to which our current civilization must pay a lot of attention.

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The use of a suitable modeling technique for the optimized design of a magnetic gear is essential to simulate its electromagnetic behavior and to predict its satisfactory performance. This paper presents the design optimization of an axial flux magnetic gear (AFMG) using a two-dimensional (2D) magnetic equivalent circuit model (MEC) and a Multi-objective Genetic Algorithm (MOGA). The proposed MEC model is configured as a meshed reluctance network (RN) with permanent magnet magnetomotive force sources. The non-linearity in the ferromagnetic materials is accounted for by the MEC. The MEC model based on reluctance networks (RN) is considered to be a good compromise between accuracy and computational effort. This new model will allow a faster analysis and design for the AFMG. A multi-objective optimization is carried out to achieve an optimal volume-focused design of the AFMG for future practical applications. The performance of the optimized model is then verified by establishing flux density comparisons with finite element simulations. This study shows that with the combination of an MEC-RN model and a GA for its optimization, a satisfactory accuracy can be achieved compared to that of the finite element analysis (FEA), but with only a fraction of the computational time.

This paper presents a two-dimensional (2D) magnetic equivalent circuit (MEC) model to investigate the magnetic field distribution in the air-gap of an axial-field magnetic gear (AFMG). The MEC model is configured as a meshed reluctance network (RN) with permanent magnet magnetomotive-force sources. The MEC model based on RN is considered as a good compromise between accuracy and computational effort. This is a new model that will allow a faster analysis and design for the AFMG. Flux density in the air-gap is calculated with the proposed model and verified by finite element simulations.