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Rotor shape optimization is crucial in designing synchronous reluctance machines (SynRMs) because the machine performance is directly proportional to the rotor’s magnetic saliency ratio. The rotor geometry in synchronous reluctance machines is complex, and many geometrical parameters must be optimized. When fluid flux-barrier geometry is desirable, using analytic equations to prepare the rotor geometry for finite element analysis could be tedious. This paper aims to provide a robust numerical procedure to draw the fluid flux-barrier geometry in transversally laminated radial flux inner and outer rotor SynRMs by directly solving the magnetic vector potential equation using the finite difference method..

In this paper, the goal is to have a robust procedure for drawing the rotor geometry for an arbitrary number of slots (Ns), poles (p) and flux-barrier layers (Nfb). Therefore, this paper targeted several combinations to investigate the performance of the proposed algorithm. The MATLAB software is used to implement the proposed algorithm. The ANSYS Maxwell software is used for counterpart finite element simulation to check the correctness of the results derived by the proposed method.

Several inner and outer rotor SynRMs considering a different number of poles and a different number of flux-barrier layers per pole are studied to investigate the performance of the proposed algorithm. Results corresponding to each case are presented, and it is shown that the method is robust, flexible and fast enough, which could be used for the generation of the rotor geometry for the finite element analysis effectively.

The value of the proposed algorithm is its simplicity and straightforwardness in its implementation for the preparation of the rotor geometry with the desired fluid flux-barrier layer curvature resolution suitable for the finite element analysis. The procedure presented in this paper is based on the ideal magnetic loading concept, and in future works, a similar idea could be used for linear and axial flux SynRMs.

During the design process of synchronous reluctance motors (SynRMs), one crucial step, after its main dimensioning, is optimizing the rotor geometry for maximum average torque and minimum torque ripple. However, because of the complexity of rotor flux-barrier layers geometry, the number of rotor geometrical parameters is high and this step could be quite complex and time-consuming. To obtain a good performance, one needs a robust algorithm to optimize the rotor geometry. The purpose of this paper is to present a sequential iterative method for rotor shape optimization in SynRMs based on the per-unit rotor model to maximize the average torque and minimize the torque ripple.

In the presented method, at first, rotor geometrical parameters are classified into several groups based on their geometrical similarities, and then optimization is done on these individual groups iteratively. The method starts with an arbitrary feasible rotor geometry and proceeds to optimize it. Because the method’s performance depends on initial rotor geometry, different cases are studied to investigate the convergence and robustness of the method. The MATLAB software is used to implement the optimization algorithm, and the ANSYS Maxwell software is used for the finite element analysis.

The performance of the proposed method is studied on a three-phase 0.75 kW-1,500 rpm permanent magnet assisted SynRM. The results show that the method improves the average torque while reducing the torque ripple. Even if the method starts with an inappropriate initial rotor geometry, it is robust enough and converges within an acceptable number of iterations.

The value of this paper is in introducing a per-unit rotor model. When the authors optimize the rotor geometry for a specific motor rating, it can be scaled up or down for other ratings with little effort. In this work, the number of rotor poles is four and the number of rotor flux-barrier layers per pole is three. Other combinations could be analyzed in future studies.

This paper aims to present an adaptive method based on finite element analysis to calculate iron losses in switched reluctance motors (SRMs). Calculation of iron losses by analytical formulas has limited accuracy. On the other hand, its estimation in rotating electrical machines through fully dynamic simulations with a fine time-step is time-consuming. However, in the initial design process, a quick and sufficiently accurate method, i.e. a value close to that of iron losses, is always welcome. The method presented in this paper is a semi-analytical approach. The main problem is that iron losses depend on d B/d t. Therefore, the accuracy of the calculation of iron losses depends on the accuracy of the calculation of the first derivative of the flux density waveform. When adopting a magnetostatic model to estimate the iron losses, an important question arises: by how many magnetostatic simulations can the iron losses be estimated within the desired accuracy? In the proposed algorithm, the aim is not to accurately calculate the value of iron losses in SRMs. The objective is to find a numerical error criterion to calculate iron losses in SRMs with a minimum number of magnetostatic simulations.

A finite element solver is developed by authors in MATLAB to solve the 2 D nonlinear magnetostatic problem using the Newton–Raphson method. A parametric program is developed to create geometry and mesh. The proposed method is implemented in MATLAB using the developed solver. Counterpart simulations are done in the ANSYS Maxwell software to validate the accuracy of the results generated by the developed solver.

The performance of the proposed method is studied on a 12/8 (500 W) SRM. Three scenarios are studied. The first one is the calculation of iron losses by uniform refinement, and the second one is by adaptive refinement, and the last one is by adaptive refinement started by particular initial points (switching points). According to the results, the proposed method substantially reduces the number of magnetostatic simulations without sacrificing accuracy.

The main novelty of this paper is introducing an error criterion to find the minimum number of magnetostatic simulations that are needed to calculate iron losses with the desired accuracy.

The purpose of this paper is to develop an effective, yet simple analytical framework for optimization of permanent-magnet synchronous machines. Also, single/multi-objective optimizations are performed for a case-study machine with surface-mounted permanent magnets.

First, an accurate magnetic equivalent circuit is developed which takes all the material such as iron saturation and PM parameters into account. Then, through a Fourier analysis, it is combined with the d-q model of PM synchronous machines to achieve an optimization framework including the developed torque, back-EMF and a number of design considerations. Finally, a genetic algorithm (GA) is employed in the single/multi-objective design optimizations, which offers several design characteristics upon different desired outcomes.

An analytical design framework for the optimization of permanent-magnet synchronous machines is developed in this paper that can effectively account for all material properties such as iron saturation and PM characteristics, and take into account the design considerations, all of which are shown as superiorities of the proposed approach over the existing method. In addition, the proposed framework is relatively simpler in terms of implementing. The model is verified by employing finite element method. Moreover, sensitivity analysis is carried out to investigate the influence of the design parameters on the machine performance, which provides valuable information for the designer of such devices. Finally, a GA is utilized to perform single/multi-objective optimization schemes whose objectives are minimizing the torque ripples, back-EMF total harmonic distortion and PM volume.

The proposed framework is new approach that could be employed in the design optimization of PM synchronous machines. Contrary to existing method, it is simpler and more effective in taking the material properties such as iron saturation and PM characteristics into account.