High performance permanent magnet electrical machine for electrical vehicle applications

Abstract

For electrical vehicle system, torque density, power density, output performance, high-speed range, reliability and cost are of the most importance. This means that the designing and manufacturing of high-performance traction system must be employed, regarding electrical machine, drive and battery. In this work, the main target is to propose and investigate methods for improving the designing of the electrical machine on EVs traction system. Permanent Magnet Synchronous Machine (PMSM) with the advantage on high power density, high efficiency and excellent power factor has been widely used in EVs applications, especially the high saliency type motor called Interior Permanent Magnet Machine (IPM). The use of performance map is a valuable evaluation tool for EVs machines, in terms of torque-speed ability and efficiency presentation. A FEM based performance mapping tool is designed and presented to improve such evaluation abilities, with motor control method evolved, advanced losses evaluation and optimal running time. With the evaluation tool secured, the design of an IPM traction motor is employed with prototype and experimental test, to deliver high power density, good torque performance, low harmonic content and wide speed capability. To ensure the smooth running of EVs, novel skewing method for motor, called modular skewing, is then introduced to archive optimal torque ripple minimization on IPM, rather than optimizing the cogging torque. The technique has been developed through vector redistribution algorithm and testified by 2D FEM modelling. Basing on the new designed IPM motor, a novel motor structure, named End-winding Flux Motor (EWFM), is invented, whose structure can be embedded to most type of conventional PMSM end-winding side for the purpose of end-winding utilization, power density increases and thermal improvements. In the end, the 3D FEM and experimental tests validate the concept of EWFM.

Date of Award	11 Jun 2018
Original language	English
Awarding Institution	Univerisity of Nottingham
Supervisor	Christopher Gerada (Supervisor) & He Zhang (Supervisor)