TY - GEN
T1 - Self-starting analysis of a novel 12/14 type bearingless switched reluctance motor
AU - Bao, Junfang
AU - Wang, Huijun
AU - Liu, Jianfeng
AU - Xue, Bingkun
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/9
Y1 - 2014/9/9
N2 - In this paper, a novel 12/14 bearingless switched reluctance motor (BLSRM) is investigated. For the conventional 12/14 BLSRM, there is only a small conduction range for positive torque generation. In order to solve this problem, shifting stator pole technology is applied in the proposed structure. It is good for increasing the output torque and simplifying the control circuit. However, the proposed motor becomes a two-phase motor. As a result, the motor can't realize self-starting at some rotor positions due to torque dead point or dead zone. Therefore, in this paper, self-starting analysis of the proposed motor is firstly analyzed. A step-airgap starting method is applied to implement self-starting at all rotor positions. Furthermore, the effect of starting method on the motor performance such as torque and suspending force is also investigated by means of finite element analysis (FEA). Finally, surface response method and genetic algorithm are employed to optimize structure parameter to improve the motor performance.
AB - In this paper, a novel 12/14 bearingless switched reluctance motor (BLSRM) is investigated. For the conventional 12/14 BLSRM, there is only a small conduction range for positive torque generation. In order to solve this problem, shifting stator pole technology is applied in the proposed structure. It is good for increasing the output torque and simplifying the control circuit. However, the proposed motor becomes a two-phase motor. As a result, the motor can't realize self-starting at some rotor positions due to torque dead point or dead zone. Therefore, in this paper, self-starting analysis of the proposed motor is firstly analyzed. A step-airgap starting method is applied to implement self-starting at all rotor positions. Furthermore, the effect of starting method on the motor performance such as torque and suspending force is also investigated by means of finite element analysis (FEA). Finally, surface response method and genetic algorithm are employed to optimize structure parameter to improve the motor performance.
UR - https://www.scopus.com/pages/publications/84907805259
U2 - 10.1109/ICIT.2014.6895013
DO - 10.1109/ICIT.2014.6895013
M3 - 会议稿件
AN - SCOPUS:84907805259
T3 - Proceedings of the IEEE International Conference on Industrial Technology
SP - 866
EP - 871
BT - Proceedings of the IEEE International Conference on Industrial Technology
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Industrial Technology, ICIT 2014
Y2 - 26 February 2014 through 1 March 2014
ER -