In this article, an exact analytical model for predicting irreversible demagnetization in Permanent Magnet Synchronous Machines (PMSMs) under overload and high-temperature conditions is presented. The proposed model includes a nonlinear model combined with a process for determining demagnetization. First, the nonlinear model considers non-uniform magnetization by dividing each permanent magnet (PM) into numerous small segments with separated remanence flux densities (RFDs). Harmonic modeling (HM), combined with an iterative loop, is employed to obtain nonlinear solutions, accurately capturing saturation effects that lead to high demagnetizing fields. The RFDs are iteratively updated until convergence is achieved. The proposed model can accurately predict machine behavior, capturing both demagnetization and saturation effects. Validation using a PMSM shows excellent agreement with both Finite Element Analysis (FEA) and experimental results, significantly reducing computation time compared to FEA simulations. This approach provides a robust tool for engineers to design and evaluate PMSMs, ensuring machine reliability under adverse conditions.

This study presents a two-dimensional analytical method for fast optimization, taking into consideration the influence of the eddy current in a magnet and iron loss within a coaxial magnetic gear. Subdomain modeling was utilized to obtain vector potentials in the air-gap, magnet, and modulation regions by solving Maxwell’s equations. After that, the magnet, rotor, and modulation losses were predicted and then compared using a finite element method simulation within three topologies with gear ratios ranging from five to six. The authors improved the machine performance, specifically the torque density, by employing a multi-objective function with particle swarm optimization. The flux density obtained using subdomain modeling in just 0.5 s benefits the optimization process, resulting in a torque-density optimal model after around 3 h. A 3/19/16 prototype targeting a low-speed, high-torque, permanent generator application was fabricated to verify the analytical and simulation results.

This study presents an approach to calculating the temperature increase in the internal components of permanent magnet synchronous machines by applying lumped-parameter thermal networks and analytical methods. Accordingly, the thermal equivalent circuit method is employed to obtain the temperatures of the machine’s internal components. Furthermore, this analytical method predicts the temperature distribution in the slot area. The 24/6 prototype was used to evaluate the proposed model by comparing the calculated and finite element method simulation.

In this paper, a method for calculating the cogging torque and air-gap flux density of a surface-mounted permanent magnet machine (SPMSM) is studied. First, a simplified model of the SPMSM is presented for electromagnetic analysis, and the magnetic vector potential is derived using the governing equations based on Maxwell’s equations in a two-dimensional polar coordinate system. The air gap flux density is derived using appropriate boundary conditions, and based on analytical solutions, the cogging torque was calculated. The analysis results derived through the proposed method and the skew of the rotor, the skew angle and segment that satisfy the optimal cogging torque of SPMSMs are derived. The accuracy of the proposed method is verified through a comparison with the analysis results with the finite element method.

This study presents a 2-D harmonic modeling (HM) approach for analyzing the non-linear permeability of the core in a yokeless and segmented armature (YASA) axial flux motor. The proposed method formulates Maxwell’s equations in cylindrical coordinates using complex Fourier series and the Cauchy product, effectively addressing local saturation effects. To validate the model, a 3-D finite element method (FEM) analysis was conducted, demonstrating good agreement with the proposed approach. In particular, the HM approach reduces computational time by up to 30 times compared to conventional FEM simulations, making it a promising tool for motor pre-design and optimization in high-value applications that require 3-D analysis.

This study proposes an innovative approach that integrates the subdomain method with sequential quadratic programming (SQP) to optimize the volume of a high-speed surface-mounted permanent magnet synchronous motor in an air compressor operating at 110 000 rpm. Unlike conventional optimization tools that often rely on finite element analysis (FEA) software, by leveraging the subdomain method for electromagnetic modeling, we obtain an analytical solution that rapidly represents the behaviors of the motor. Subsequently, the SQP technique is applied to optimize the volume of the model while satisfying design constraints. The proposed model is verified by FEA simulation.