Hot Resistance Estimation for 8/6 Switched Reluctance Machine Using Artificial Intelligence


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Abstract


To design energy saving electrical machines, a new trend has come out to determine the temperature rise of rotating electrical machine. Rise in the winding temperature was determined from the estimated values of winding resistance, both cold and hot. The estimation of hot resistance was modeled using soft computing techniques such as ANFIS which stands for Adaptive Neuro Fuzzy Inference system. This technique estimates hot resistance of the winding using the input variables as cold resistance, ambient temperature and temperature rise. Heat run test was conducted on 8/6 Switched Reluctance Machine of 2 H.P at various Ambient temperature .The estimated values of hot resistance show a good agreement between the measured and computed values obtained using ANFIS. Hence this model proves to be well suited for the estimation of hot resistance.
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Keywords


Adaptive Neuro Fuzzy Inference System (ANFIS); Hot Resistance; Temperature Rise; Switched Reluctance Machine

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References


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