Research On Sensorless Control Of Switched Reluctance Motor

In recent years the switched reluctance motor (SRM) has received considerable attention due to its simple structure, high efficiency, strong fault-tolerance and flexibility in control. Its application fields have been involved in aerospace, oil development, electric vehicles and so on. The information of rotor position is essential for driving SRM, however, the direct position sensors not only increase the overall cost, but also deteriorate the system reliability in harsh environment. Hence, the sensorless technique has important theoretical significance and project value. This paper studies the injected voltage pulse method at low speed and the current-flux method at high speed respectively.Firstly, this paper summarizes basic equations and mathematical models of SRM, discusses the principle of light-electric sensor. Then the online detection method of sensors'fault conditions is studied. If all the three sensors go wrong, the motor can operate under sensorless condition. Secondly, the method of determining initial position accurately based on the injected voltage pulse method is discussed, the robustness analysis and experimental verification is carried out also.Subsequently, a new method for sensorless control of SRM at low speed is presented in this paper. This new method is appropriate for chopping model. Via injecting voltage pulse into the idle phases and detecting current slope difference, the rotor position can be estimated. The control strategy is suitable for regulating speed with variable voltage, which can eliminate the impact of EMF and adjust the on-off angle. Simulation and experimental results show that the proposed method is effective.Thirdly, the current-flux method which is suitable for high speed operation is studied. The motor's flux characteristic curve based on DSP is measured, which is the working base of the current-flux method. In order to reduce time delay and memory space, the principle of simplified flux method is described and verified by experiments. Subsequently, simulation results show the feasibility of sensorless technology using BP neural network.Finally, this paper introduces the system hardware platform and software program. The hardware platform includes current detection and protection circuit, voltage detection and protection circuit, LCD circuit and so on. The software program includes DSP program and CPLD program.