Based on the characteristics of the nonlinear and the large range of structures and parameters of switched reluctance motor drive system used in electric vehicles, a new method that the combination of mixed genetic algorithms and neural network is put forward to achieve the identification of switched reluctance motor drive system. The principle is expounded and corresponding algorithm and formulas are presented as well. The method combines the advantages of the optimum genetic algorithms and neural networks which overcomes the shortcomings of traditional BP networks such as the slow learning rate and liable to converge to the local minima, The simulation results demonstrate that this method is quite practicable for its fast and exact closing to its real system.