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This article proposes a novel parametric equivalent magnetic network (EMN) modeling approach for multiobjective optimization of a surface-mounted permanent magnet (SPM) machine. The key is to apply variable meshes under adjustable topology to establish parametric EMN model. First, a novel adjustable cross-shape mesh method with variable sizes and regular permeance is proposed, which can flexibly vary with parameters. The meshes are combined in EMN model to simultaneously achieve high accuracy, high computing efficiency, and structural parameterization. Second, comprehensive sensitivity analyses are utilized to separate variable EMN parameters with the parametric feature. Significant variables are employed in multiobjective differential evolution algorithm with response surface models. Then, the optimal parameters are balanced and determined from Pareto front with improved torque performance. Finally, a prototype is manufactured, and the effectiveness of the proposed EMN-based optimization design method is verified by finite-element analysis and experimental results. [ABSTRACT FROM AUTHOR]

This paper proposes a new equivalent magnetic network (EMN) model for vehicular dual-permanent-magnet vernier (DPMV) machines by applying a generalized modeling method. First, the magnetic circuit method and the meshing method are combined together to improve the modeling efficiency of the DPMV machine. The magnetic circuit method is used to generate conventional lumped parameter permeances to shorten time consumption, whereas the mesh method is utilized in disordered magnetic fields to obtain high precision. Second, a meshing solution for oblique region is proposed to enhance modeling flexibility. Moreover, the flux distributions in meshes are represented without magnetic field pre-delineation, which enables its utilization as a self-adaptive reluctance network model in design optimization. Finally, the proposed EMN model is used to predict the performance of the DPMV machine, considering leakage magnetic flux, local iron saturation, and magnetic field modulation effect simultaneously. Meanwhile, the effectiveness of the proposed EMN model is verified by comparison with finite-element analysis and experimental tests. [ABSTRACT FROM AUTHOR]

Due to their advantages of high efficiency, high power density, and strong fault-tolerance ability, fractional-slot concentrated-winding permanent-magnet (FSCW-PM) machines are of particular interest in the applications such as wind power generation and electric vehicles. However, FSCW-PM machines suffer from rich winding magnetomotive force (MMF) space harmonics by the armature reaction field, which may increase eddy current loss. In this paper, a new low harmonic FSCWPM machine is designed, which can reduce some space harmonics of low order in the air-gap flux density. A new magnetic equivalent circuit (MEC) model is developed to analyze the designed PM machine, which offers less computation time and more calculation accuracy. Finally, a prototype machine is built and the measured results verify the theoretical analysis and the developed MEC model. [ABSTRACT FROM AUTHOR]

This article proposes a new equivalent magnetic network (EMN) model for predicting the performances of interior permanent magnet (IPM) machines. The proposed EMN model incorporates the features of high accuracy and low time consumption in the reluctance network model and the magnetic equivalent circuit model, respectively, to achieve a tradeoff between the time consumption and calculation accuracy. A new air-gap model is also presented to make the dynamic analysis of the machine more efficient and easier. Moreover, the modeling approach of the rotor provides a standard for the modeling of IPM machines with permanent magnets (PMs) at different locations and of different shapes. In addition, the proposed EMN model takes into consideration the influence of flux leakage and iron saturation. Finally, the example machine is chosen, and the effectiveness of the EMN model is verified by comparison with the finite-element analysis and experimental tests. [ABSTRACT FROM AUTHOR]