|Title:||Design and optimisation of the performance of switched reluctance motor drives|
|Subject:||Hong Kong Polytechnic University -- Dissertations.|
Sliding mode control.
|Department:||Department of Electrical Engineering|
|Pages:||xx, 154 leaves : ill. ; 30 cm.|
|Abstract:||Switched reluctance machine (SRM) has been gaining increasing attentions from researchers and industries decades ago. Because of its simple mechanical structure, low moment of inertia, high power density, low manufacturing cost, and high reliability, it is considered as a strong competitor to induction motor. Because SRM usually operates in regions of high magnetic saturation in order to realise high power density, there are inevitable nonlinearities among flux-linkage, phase current, electromagnetic torque and rotor position. Nonlinearities complicate SRM drive system simulation studies, which are now becoming indispensable tools for performance evaluation and controller design. SRM also suffers from having a relatively high torque ripple using simple current control. Hence, the use of SRM in applications demanding high performance becomes challenging. This thesis concentrates on studies of SRM in respect to non-linear computer simulation model, online torque estimation, instantaneous torque control and position control. A computer simulation model with nonlinear magnetic and torque characteristics is presented. Since the model is developed under MATLAB/ SimPowerSystems, it can be used to simulate SRM, power drive and its associated control algorithm simultaneously. User defines the magnetic data and considers both self and mutual coupling as well as the necessary mechanical parameters which are acquired from experiments. The configuration of the power drive and control algorithm can be altered using appropriate graphical user interface. Simulation results show that the model is accurate and effective, as all the simulation results obtained from the developed model have been fully validated experimentally. To estimate the electromagnetic torque online, a torque estimator for SRM under hysteresis current control is proposed. The co-energy of the phase is estimated based on a few pre-measured machine parameters. The co-energy, rotor position and phase current are stored in the memory. In the next switching cycle that follows, the newly estimated co-energy and the stored value are used to estimate the instantaneous torque using the principle of co-energy. Simulation and experiment results demonstrate that the outputs of the proposed estimator are similar to those based on cubic spline model. In regard to torque ripple reduction, a torque controller based on co-energy control is developed. For this controller a co-energy profile is firstly deduced from pre-measured low-current magnetic characteristics of the SRM. Since co-energy is proportional to the electromagnetic torque in both linear and nonlinear regions, the required co-energy can be calculated from the co-energy profile and torque command. With the use of an online co-energy estimator, the controller can regulate the co-energy to follow the command. Computer simulation and experiment confirm that under co-energy control, the torque contribution of each phase can be controlled to reduce output torque ripple significantly. In addition, the controller requires less memory and less pre-measured machine data, in contrast to traditional current control schemes. The torque controller is then extended from one-quadrant to four-quadrant operation, to achieve torque ripple reduction in both motoring and generating modes at both directions. An algorithm for rotor position control is developed on top of the torque control scheme. The position control loop and torque control system are connected in cascade. The position controller and co-energy controller are designed utilising the principles of two-degree of freedom internal model control, which is a model-based controller with improved disturbance rejection. The parameters of the controllers are expressed in terms of basic machine parameters and user-selected system response time constants. The simulation and laboratory outputs of the systems ascertain the robustness of the proposed algorithm against parameter mismatch.|
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