Based On The Opening Turn-off Angle Optimization Of Switched Reluctance Motor Control Strategy

Switched Reluctance Motor (SRM for short) features simple and strong structure, high reliability and high efficiency, and thus has great application potential. But at the same time, due to its doubly salient structure and seriously nonlinear magnetic circuit, it is difficult to establish an accurate mathematical model for it, and accordingly, the improvement of the performance of SRM is restricted. Under this background, this paper aims to explore a control strategic to optimize the performance of SRM by changing the turn-on and turn-off angle of switches in power circuit.This paper introduces and analyzes three different control methods of angle optimization:online-optimization-based method, fuzzy-logic-based method and neural-network-based method, in terms of their principles and application examples. These methods are applied for simulation on the same SRM, the result of the simulation is used for the comparison of their pros and cons comprehensively. According to the comparision, it is determined that neural-network-based control strategic of angle optimization for performance of SRM will be adopted in the paper. This paper considers the maximization of ampere/torque ratio as the optimum objective, chooses the Radial Base Function (RBF) neural network as the tool of optimizing the ampere/torque ratio of SRM based-on angle control. A heuristic searching algorithm is proposed to obtain the sample data for training the RBF neural network. By utilizing the neural network toolbox of Matlab software, the RBF network is designed using the sampled data. The Matlab/Simulink simulation model of the RBF-network-based control system is established and run to testify the feasibility of the proposed angle optimization method based on RBF network.Finally, based on the DSP chip TMS320F2812, the hardware system for SRM angle optimization is designed, respectively in two aspects: power circuit and controller circuit. The framework of the systematic software is proposed, and the implementation of several important program modules is analyzed in detail. By taking advantage of the integrated developing environment CCS 3.1 of TI Company, the system program is developed, and then several related experiments are taken, the result of the experiments demonstrates that:the proposed control strategic in this paper based on RBF neural network is of superiority, the objective of the maximization of torque/ampere ratio is realized.