Design and Optimization of a Novel Delta-Type Consequent-Pole Hybrid Magnet Memory Machine

With the merits of high torque density, unintentional demagnetization (UD) withstand capability and satisfactory flux regulation range, series magnetic circuit variable flux memory machines (VFMMs) have been recently utilized in the new-generation household appliance, e.g., washing machine. However, the conventional series structure leads to the increase of cost and magnetization current amplitude due to a larger volume of permanent magnet (PM) material, which are unfavorable for the industrialization of this kind of machines in domestic appliance applications. In order to address the foregoing issues, a novel consequent-pole hybrid magnet VFMM (CPHM-VFMM) with dual-layer delta-type PMs is proposed and optimized for belt-drive washing machine application in this paper. The machine is geometrically characterized by a novel rotor-PM consequent-pole (CP) design, which replaces half of the magnetic poles with iron parts, thus increasing d-axis magnetic permeance to decrease the corresponding required magneto-motive-force (MMF) for flux regulation while maintaining satisfactory electromagnetic performance. The topology and operating principles of the proposed CPHM-VFMM are firstly introduced and analyzed. The air-gap flux density and flux regulation range of the machine are analytically identified with equivalent magnetic circuit method. Then the machine is optimized with multimode field-current coupled (MMFCC) solution considering the operation situation in the washing machine. Afterwards, the electromagnetic characteristics of the machine are evaluated and compared with those of a conventional VFMM by finite element (FE) method. It shows that the proposed CPHM-VFMM has the merits of smaller PM usage, higher torque density, lower flux regulation current, wider flux regulation range, as well as higher global efficiency compared with the conventional counterpart. A 36-slot/6-pole CPHM-VFMM prototype is manufactured and tested to validate the FE analyses.