Abstract：Hysteresis is the property of magnetic materials, which exists in electromagnetic equipment such as electrical machines and transformers. It is necessary to create mathematic model of hysteresis. The model used in the paper is a Preisach hysteresis model, whose distribution function is supposed to be a Lorentzian function. Both the analytical and neural network(NN) methods are taken to identify the parameters of the distribution function, then the two methods are compared and experimental results testify the effectiveness of identification. The model can be used to predict the current of transformer without DC bias, and an Epstein frame is adopted to testify the model by simulating the current of primary winding with the input of the voltage of secondary winding, the consistency of the simulation results with the experimental results indicates the feasibility of the model.
李富华, 刘德志, 陈俊全, 王东, 郭云. 基于Lorentzian函数的Preisach磁滞模型辨识与验证[J]. 电工技术学报, 2011, 26(2): 1-7.
Li Fuhua, Liu Dezhi, Chen Junquan, Wang Dong, Guo Yunjun. Identification of a Preisach Hysteresis Model WithLorentzian Function and Its Verification. Transactions of China Electrotechnical Society, 2011, 26(2): 1-7.
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2011, Vol. 26 
