Title :
Optimization research of turn-on angle and turn-off angle based on switched reluctance starter/generator system
Author :
Xiaoshu Zan ; Yingjie Huo ; Gu, Jason
Author_Institution :
Sch. of Electr. Power Eng., China Univ. of Min. & Technol., Xuzhou, China
Abstract :
Switched reluctance starter/generator has stronger competition ability in the hybrid system by reason of the large starting torque, easy to switch from electric to power, high power density, wide speed range, high efficiency, high reliability, low cost, etc. In order to improve the performance of switched reluctance starter/generator system, the master switch angle is needed to optimize. In this paper, according to the serious nonlinear characteristic of switched reluctance motor, the nonlinear simulation model is built by wavelet neural network method. The system starting opening turn-on and turn-off angle has been optimized with the purpose of maximizing the torque and the system power opening turn-on and turn-off angle has been optimized with the purpose of both biggest power output and optimal efficiency. The optimum switch angles are obtained under the two states. Experiments verification has finished on the prototype system of SRM/G system experimental platform.
Keywords :
neural nets; optimisation; power engineering computing; reluctance generators; nonlinear simulation model; optimization research; switched reluctance motor; switched reluctance starter-generator system; turn-off angle; turn-on angle; wavelet neural network method; Generators; Optimization; Power generation; Simulation; Switched reluctance motors; Torque;
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2015 IEEE 28th Canadian Conference on
Conference_Location :
Halifax, NS
Print_ISBN :
978-1-4799-5827-6
DOI :
10.1109/CCECE.2015.7129388