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作 者:毛帅 陶建峰[1,2] 余宏淦 刘成良 MAO Shuai;TAO Jianfeng;YU Honggan;LIU Chengliang(School of Mechanical and Power Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;State Key Laboratory of Mechanical System and Vibration,Shanghai Jiao Tong University,Shanghai 200240,China)
机构地区:[1]上海交通大学机械与动力工程学院,上海200240 [2]上海交通大学机械系统与振动国家重点实验室,上海200240
出 处:《西安交通大学学报》2020年第10期94-99,107,共7页Journal of Xi'an Jiaotong University
基 金:国家自然科学基金资助项目(51935007)。
摘 要:针对传统密集采样方法获得采用角度位置控制的开关磁阻电机最优开通角与关断角所需实验次数多、耗时长,效率低的问题,提出一种采用Kriging模型的最优开通角和关断角实验求取方法来减少实验采样次数,提高寻优效率。首先,通过少量的初始样本点建立开通角和关断角与电机振动加速度之间的预测模型;之后,根据得到的预测模型有针对性地在最优开通角和关断角可能出现的区域进行采样计算;最后,当区域缩小到满足精度要求的大小后,对该区域进行密集采样,从而快速准确发现最优开通角和关断角。实验结果表明,基于Kriging预测模型获取相同开关磁阻电机最优开通角和关断角(误差小于1%以内)所需样本数仅为传统的密集采样方法的12.4%,计算时间缩短了62.8%。因此,所提方法能显著提高开关磁阻电机的开通角和关断角寻优实验效率。An experimental method for turn-on and turn-off angles based on Kriging prediction model is proposed to solve the problem that the traditional intensive sampling method requires many experiments,long time and low efficiency to obtain optimal switching angles of switched reluctance motor controlled by angle position control strategy.First,a model to predict the relationship between the switching angles and the motor vibration is established via a small number of sample points.Then,prediction results from the model are used to the sampling and calculation in the area where the optimal switching angles probably exist.Finally,when the area is reduced to meet an accuracy requirement,intensive sampling is conducted in the area so as to rapidly and exactly obtain the optimal switching angles.Experimental results show that the number of samples used by the proposed method to obtain the optimal switching angle(error is less than 1%)of the same switched reluctance motor is only 12.4%of that of the traditional intensive sampling method,and the time-consumption of calculation reduces by 62.8%.Therefore,the proposed method significantly improves the optimization efficiency of the switching angles.
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