摘要
基于损耗模型的效率优化控制方法因其物理意义明确、寻优速度快等优点而得到广泛应用,然而该方法对损耗模型中的电机参数较为敏感,要提高优化效果,需要准确实时获取损耗模型中相关参数。对基于损耗模型的效率优化算法中关键参数辨识进行研究,设计考虑铁耗的牵引电机状态观测器,为了提高观测速度和系统的鲁棒性,进行基于反馈矩阵的极点配置,设计基于稳定性定律的关键参数自适应辨识算法,并进行实验验证。
Loss model control strategy(LMC) has been widely used in motor control for its visual physical meaning and high optimization speed. While the LMC strategy is highly sensitive to the motor parameters in the loss model, it is necessary to obtain accuracy parameters in the loss model in real time in order to improve the optimization effect. In this paper, the identification of key parameters in efficiency optimization algorithm based on loss model was studied and a state observer of traction motor considering iron loss was designed. In order to improve the observation speed and robustness of the system, a closed-loop pole configuration and an improved discrete method under low sampling frequency were carried out. Parameters sensitivity problem was solved through the adaptive estimation of key parameters. The algorithm was verified by simulation and experiment.
作者
董侃
刘伟志
马颖涛
宋永丰
安泊晨
DONG Kan;LIU Weizhi;MA Yingtao;SONG Yongfeng;AN Bochen(Locomotive & Car Research Institute, China Academy of Railway Sciences, Beijing 100081, China)
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2019年第4期64-72,共9页
Journal of the China Railway Society
基金
中国铁路总公司科技研究开发计划(2017J008-Ⅰ)
关键词
效率优化
损耗模型
状态观测器
参数辨识
efficiency optimization
loss model
state observer
parameter estimation