Optimum performance of switched reluctance motors (SRMs) over a wide range of speed control is an essential approach for many industrial applications. However, the doubly salient structure and deep magnetic saturation make magnetization characteristics of SRMs a highly nonlinear function of rotor position and current magnitude. This, in turn, makes the control of SRM drives a challenging task. As the control of SRMs depends on the inductance profile, it requires an adaptive control technique for optimum operation over a wide range of operating speeds. This paper presents an adaptive control technique for optimum excitation of SRM drives. The proposed control technique accurately considers the effect of back-emf voltage for high-and even low-speed operation. It determines the most efficient switch-on angle as a function of motor speed and current magnitude. Moreover, the optimum switch-off angle is defined to enhance motor output torque/power without negative torque production. The proposed technique simplifies the SRM control in order to cut down the complexity and cost; it offers easy implementation and can be used for sensor and sensorless operation of SRM drives. It also provides an eligible candidate for industrial applications as the optimization strategy uses an analytical solution. For adequate modeling, the nonlinear magnetization characteristics of the SRM are obtained using finite element analysis. The SRM, converter, and control algorithm are modeled using the MATLAB/Simulink environment. The simulation results are compared with a closed-loop switch-on angle controller in order to show the feasibility of the proposed control technique. In addition, experimental results are obtained to prove the promising performance and simplicity of the proposed controller.
High performance control and analysis of switched reluctance machines (SRMs) require accurate modeling of their magnetic characteristics. However, the doubly salient structure and deep magnetic saturation make it very complicated to accurately model SRMs. This paper presents a high fidelity model development for SRMs. The model is developed based on the experimental measurement of flux-linkage and torque characteristics. The introduced measurement noises / errors are investigated carefully. Then several post-processes are achieved to reduce these noises. The measurement accuracy is verified by three methods: finite element method (FEM), search coil comparison, and LCR meter. The measured data are employed after proper rearrangement to build a dynamic MATLAB simulation model for the tested 8/6 machine. The model accuracy and dependability is achieved experimentally.
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