Design and multi‐objective optimisation of switched reluctance machine with iron loss

Abstract

In this study, the design optimisation of a switched reluctance machine (SRM) with the layered method has been studied. Firstly, a multi-physical analytical model for the SRM is established. The proposed model consists of an electromagnetic model, an electrical model, a loss model, and a thermal model. Then a layered optimisation design method suitable for the SRM is proposed in combination with the multi-physical field simulation model. Taguchi method is used to analyse the influence degree of the main geometric dimensions on the dynamic performance, and the parameters are divided into high-sensitivity parameters (HSPs) and low-sensitivity parameters. The non-dominated sorting genetic algorithm-II algorithm is used to optimise the HSP by the proposed model. The iron loss, average torque, average torque per unit mass, torque ripple and efficiency are taken as the objective functions. Finally, the prototype is manufactured and a testing platform is built. The flux linkage of several special positions of the machine is verified experimentally, and the accuracy of the electromagnetic model in the multi-physical field model is verified. The temperature experiments are carried out on the machine, and the accuracy of the equivalent heat circuit model in the multi-physical field model is verified.

Non‐linear analytical modelling and optimisation of a 12/8 rotor excited flux‐switching machine

“…The Taguchi optimisation method will be performed to find the optimum values for notch dimensions and other machine parameters. This method is one of the popular methods which is proven to be effective especially in the optimisation of electrical machines [36–38]. The Taguchi method is also a fast‐computing optimisation tool which is extensively used when a robust design and optimisation procedure is required [39–41].…”

Multi-objective optimization of high torque density segmented PM consequent pole flux switching machine with flux bridge

“…In order to further improve torque capability, the design is proceeded for optimization based on multi-variable techniques used for Multi-Objective Optimization (MOO). Various multi-objective optimization techniques have been formulated in different FSMs topologies [18][19][20][21][22][23][24][25][26] for enhancing electromagnetic performance, comparison of single-variable and multi-variable and design refinement to achieve global optimum parameters. Comparison of optimization techniques compel author for design refinement utilizing multi-objective optimization based on multi-variable geometric parameters.…”

Lumped thermal model for the multi‐layer switched reluctance motor

“…To evaluate the proposed method, a lumped thermal model is developed and the measurements are used to validate the suggested thermal model. A multi‐physical model consisting of electromagnetic model, an electrical model, a loss model, and a thermal model is introduced for the SRM in [27]. In order to evaluate the equivalent heat circuit model developed in the multi‐physical model, temperature experiments are carried out.…”

“…In comparison to the research done on electromagnetic modelling and design of the conventional type of the SRM (onelayer), less attention has been paid to thermal modelling of the onelayer SRM [22][23][24][25][26][27][28][29][30][31][32] and no work has been reported on thermal modelling of the multi-layer SRM. Therefore, it is valuable to develop an accurate lumped thermal model for the multi-layer SRM which is the main objective of the present study.…”