An Enhanced Axial-flux Magnetic-geared Machine with Dual-winding Design for Electric Vehicle Applications

Axial-flux magnetic-geared machine(MGM) is a promising solution for electric vehicle applications for combining the virtues of both axial-flux electric machine and magnetic gear. However, generalized MGMs are limited by the torque density issue, accordingly inapplicable to industrial applications. To solve the abovementioned issue, an improved axial-flux magnetic-geared machine with a dual-winding design is proposed. The key merit of the proposed design is to achieve enhanced torque performance and space utilization with the proposed design, which installs a set of auxiliary winding between modulation rings. With the proposed design, overload protection capability, and fault-tolerant capability can be also achieved, for the proposed machine can work with either the excitation of armature windings or auxiliary windings. The pole-pair, slot combination, and parametric design is studied and optimized by the 3d finite-element method and designed C++ optimization software. Electromagnetic analysis and performance comparison indicate that the proposed machine can achieve a torque enhancement of 68.6% compared to the comparison machine.

Sensorless Control on a Dual-Fed Flux Modulated Electric Motor

This paper proposes the operation principle and a new flux estimation method for sensorless control strategy for the dual-fed flux modulated electric motor(DFFM).The DFFM is designed based on the flux modulation theory,it includes two stator windings and one rotor which simplify the mechanical structure.The rotor has only modulation iron and no permanent magnets on it,so there is no cogging torque problem in this motor.With adjustment of the outer and inner stator flux rotating frequency and amplitude,different rotation speed and torque of the sandwiched rotor can be gained for the DFFM.Furthermore,an improved flux estimation based sensorless control strategy is performed on the proposed machine to fit the two winding set control situation.The startup and performance of the proposed control strategy is verified by the simulation and experiments.

Sub-region Alopex Optimization Method with RSM for Design of Permanent Magnet Machines

Based on an Alopex optimization algorithm and a response surface model(RSM),a hybrid sub-region methodology is presented to solve the optimal design problems of permanent magnet(PM)machines.The Alopex optimization method is processed both in subspace and in global solution space.In order to decrease the computing time,a multi quadric radial basis function(MQRBF)is embedded in the optimization.The proposed method speeds up the convergence rate while keeps the accuracy of the solution.A numerical experiment is given to validate the efficiency and effectiveness of the method.

Design and Comparison of Electrically Excited Double Rotor Flux Switching Motor Drive Systems for Automotive Applications

This paper presents a cost-effective driving system for automotive applications based on a double rotor electrically excited flux switching machine(FSM).Benefiting from a double rotor topology,this FSM can realize a drum winding design and thus winding ends are effectively shorten and the copper loss is mitigated.The machine structure,operation principle and design consideration are studied and further verified by time-stepping finite element method.Moreover,three topologies of drive circuit for the proposed FSM are introduced.By using electromagnetic-circuit coupling simulation,a comparison between three different three drive systems are performed,with focus on the system cost and overall electromagnetic performance,especially the effect of current control and torque ripple.A prototype is established and tested.Relevant experimental results verify the effectiveness of the proposed new FSM drive system.

Message from Editors

ELECTRICAL machines are the hearts of many modern appliances and industrial systems.Their analysis and design optimization processes become more and more complex as more disciplines/domains and constraints are involved,such as electromagnetics,structural mechanics,heat transfer,and control strategies.To achieve multi-objective optimal performance of electrical machines and systems for applications of challenging specifications,such as electric vehicles and wind power generation,it is of great significance to conduct a multi-physics analysis and take a systematic design optimization approach.On the other hand,the performance and quality of batch produced electrical machines depend highly on the material diversities and manufacturing tolerances.