期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Parameter estimation and reliable fault detection of electric motors 被引量:1
1
作者 dusan progovac Le Yi WANG George YIN 《Control Theory and Technology》 EI CSCD 2014年第2期110-121,共12页
Accurate model identification and fault detection are necessary for reliable motor control. Motor-characterizing parameters experience substantial changes due to aging, motor operating conditions, and faults. Conseque... Accurate model identification and fault detection are necessary for reliable motor control. Motor-characterizing parameters experience substantial changes due to aging, motor operating conditions, and faults. Consequently, motor parameters must be estimated accurately and reliably during operation. Based on enhanced model structures of electric motors that accommodate both normal and faulty modes, this paper introduces bias-corrected least-squares (LS) estimation algorithms that incorporate functions for correcting estimation bias, forgetting factors for capturing sudden faults, and recursive structures for efficient real-time implementation. Permanent magnet motors are used as a benchmark type for concrete algorithm development and evaluation. Algorithms are presented, their properties are established, and their accuracy and robustness are evaluated by simulation case studies under both normal operations and inter-turn winding faults. Implementation issues from different motor control schemes are also discussed. 展开更多
关键词 Electric machine Parameter estimation Fault detection Brushless direct current (BLDC) motor Bias correction Forgetting factor
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部