Comparison of efficiencies of in situ induction motor in unbalanced field conditions

G. S. Grewal, B. Rajpurohit
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引用次数: 3

Abstract

There has been a tremendous pressure to assess the in situ efficiency of Induction Machine (IM) with bounded level of intrusion and restricted measurements so as to enhance IMs enforcement. Very few researchers have carried out work to make IM efficiency evaluation methods compatible to unbalanced supply and varying load conditions. This paper recommends a novel approach using cuckoo algorithm to obtain efficiency assessment of an IM operating as a motor working with unbalanced supply having different phase voltages and different currents respectively. The cuckoo algorithm improves the searching ability and has competence to accommodate to complex optimization obstacles. Here, cuckoo algorithm optimizes the IM positive sequence parameters at various loading levels. The parameters optimization is done with the use of positive sequence input currents and electrical powers which have been obtained earlier at various load points of operation. Using the optimized parameters, the evaluation of negative sequence parameters can be made. So, the efficiency of IM can be estimated at different loading levels. Comparison of efficiencies at varying load points with unbalanced power supplies is carried out. The proposed approach is materialized on the MATLAB/SIMULINK platform. The effectiveness, validation and accuracy of the proposed strategy are established by comparing the results obtained with genetic algorithm.
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不平衡磁场条件下原位感应电动机效率的比较
在有限侵入水平和受限测量条件下,评估感应电机的原位效率,以加强感应电机的执行,已成为一个巨大的压力。很少有研究人员开展工作,使IM效率评估方法与不平衡供应和变负荷条件相适应。本文提出了一种新的方法,利用布谷鸟算法来评估在不同相电压和不同电流的不平衡电源下,IM作为电动机运行时的效率。布谷鸟算法提高了搜索能力,具有适应复杂优化障碍的能力。其中,布谷鸟算法对不同加载水平下的IM正序列参数进行了优化。参数优化是利用在运行的各个负载点上已获得的正序输入电流和电功率来完成的。利用优化后的参数,可以对负序参数进行评价。因此,可以估计不同负载水平下IM的效率。在不同负载点与不平衡电源的效率比较进行了。该方法在MATLAB/SIMULINK平台上实现。通过与遗传算法的比较,验证了所提策略的有效性、有效性和准确性。
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