FPGA Based Speed Control of SRM with Optimized Switching Angles by Self Tuning

The electromagnetic torque and speed in Switched Reluctance Motor (SRM) greatly depend on the excitation parametersi.e. turn-on angle, turn-off angle, dwell angle and magnitude of the phase currents of its phases. At lower speeds, a change in the current contributes the torque requirement which can be achieved either by voltage control (pulse width modulation) or instantaneous current control techniques. At high speeds, due to high back EMF, the regulation of current is crucial and achieved with the control of switching angles of phases. This type of control is referred as average torque control, where the torque is averaged over one stroke (2π/Nr). With constant dwell angle, advancing the phase angle influences the current into the phase winding at minimum inductance position. It has more time to get the current out of the phase winding before the rotor reaches the negative inductance slope. To maintain the speed of the motor at different load conditions, the turn-on and turn-off angles are adaptively varied. The change in dwell angle may be required where the turn-on and turn-off angle may not be sufficient to reach the required speed. In this paper, a new algorithm is proposed for self tuning of switching parameters of SRM. The proposed algorithm is simulated in MATLAB-Simulink and experimentally validated with Field Programmable Gated Array (FPGA) using MATLAB- system generator environment.

Performance prediction of switched reluctance generator with time average and small signal models

This paper presents the complete mathematical model and predicts the performance of switched reluctance generator with time average and small signal models. The complete mathematical model is developed in three stages. First, a switching model is developed based on quasi-linear inductance profile. Next, based on the switching behaviour, a time average model is obtained to measure the difference between the excitation and generation time in each switching cycle. Finally, to track control voltage and current wave shapes, a small signal model is designed. The effectiveness of the complete multilevel model combining electrical machine, power converter, load and control with programming language is demonstrated through simulations. A PI controller is used for controlling the voltage of the generator. The results presented show that the controller exhibits accurate tracking control of load voltage under different operating conditions. This demonstrates that the proposed model is able to perform an accurate control of the generated output voltage even in transient situations. The simulation is performed to choose the control parameters and study the performance of switched reluctance generator prior to its actual implementation. Initial experimental results are presented using NI-Data acquisition card to control the output power according to load requirements.