Neural Network-Based Co-Simulation Technology for Intelligent Contactors

Abstract

A simulation method of an intelligent contactor is presented by using a neural network to fit the proven relationship among the flux linkage, the electrical current, and the moving core displacement of a contactor in this article. First, the neural network algorithm is trained by the operational data of a contactor driven by a basic training circuit to solve the coil current. Then, a dynamic simulation program of the contactor model is constructed via combining the algorithm and dynamic differential equations. On this basis, by means of the co-simulation technology, the point-by-point closed-loop simulation between the control module and the contactor model is carried out. Accordingly, the co-simulation of an intelligent contactor based on a neural network is completed. The simulation method can avoid the complex finite-element modeling of a contactor and realize the model extraction of an arbitrary contactor. The extracted model can be combined with a drive circuit and any control strategy to perform the co-simulation, which is convenient for the flexible design of hardware control circuits and software control strategies of various intelligent contactors.