Optimum geometry to improve torque of a doubly salient variable reluctance machine

The growing interest in Variable Reluctance Machines (VRMs) in the field of electromechanical energy conversion is due to their robustness, simplicity, and cost of construction, where their numerous applications as well as high-speed operating motor (electric drive) that generator operating at low speeds ("direct drive" in wind generators). To improve their performance, the research is directed towards optimizing the geometry, the control, and a judicious choice of materials. In this context, the aim of this paper is to optimize various geometrical parameters such as the angles of the stator and rotor teeth, and yoke thickness, using Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) methods. The results obtained under MATLAB and FEMM environment have discussed and improved the average torque of a 6/4 VRM prototype.