Research On Decoupled Control System Of Five-Phase Fault-Tolerant Permanent-Magnet Motor

To ease the global problems such as air pollution and energy depletion, developing new energy electric vehicles becomes an important initiative. And multi-phase permanent magnet motors have been increasingly applied to the drive system of electric vehicles because of their advantages such as high efficiency, high power density, and high torque to current ratio. Due to the fact that the five-phase in-wheel fault-tolerant permanent magnet(IW-FTPM) motor drive is a multivariable and strong coupling nonlinear system whose accurate mathematical model is difficult to acquire. A new decoupled control method for the motor is proposed, in which radial basis function neural network inverse(RBF-NNI) and internal model control(IMC) are engaged to realize the decoupling and strengthen the robustness of the system. The RBF-NNI system is introduced to construct a pseudo-linear system with original system, and internal model controller is utilized as a robust controller.Firstly, the development and the control strategies of the multi-phase motors are introduced and analyzed briefly. Then, the IMC of five-phase IW-FTPM motor by using RBF-NNI is proposed.Secondly, the basic theory of the inverse system and neural network is introduced. It is hard to get the precise mathematical model, internal parameters and the analytic expression by using implicit function theorem due to the nonlinearity and strong coupling of the multivariable system. As a result, a RBF-NNI system is built by combining the RBF-NN with the inverse system, in order to construct a pseudo-linear system with the original system, and internal model controller is utilized as a robust controller.Thirdly, the fundamental characteristics and the mathematical model of the five-phase IW-FTPM motor are proposed. According to the inverse system theory and Interactor algorithm,the existence of its inverse is proved. On this basis, RBF-NNI system of the motor is deduced, which cascades before the original system.Thus, a pseudo-linear composite system including a couple of pseudo-linear-subsystems is constructed.Finally, both simulation and experimental results prove the correctness of the proposed control strategy. First of all, the simulation model is built by using MATLAB/Simulink TOOLBOX to prove the correctness and feasibility of the the control method. Then, the wholeexperiment platform is introduced, which includes the dSPACE platform and the external hardware system. The simulation and experimental results demonstrate that the proposed strategy can successfully decouple the multivariable nonlinear system and has strong robustness to load torque disturbance and un-modeled dynamics.