| Switched Reluctance Motor(SRM)has many advantages,such as simple structure,ruggedness,high starting torque,etc.At present,it has been widely used in petroleum,mineral and other industrial fields.However,due to the double salient structure of SRM,the torque ripple of SRM is too large during operation,which affects its development in more fields.Torque Sharing Function is the most common method to suppress SRM torque ripple.In this paper,an improved torque sharing function is proposed.And the optimization of improved TSF parameters based on genetic algorithm is carried out.The torque ripple can be reduced,and the motor performance can be improved during SRM operation.Combining with the structure and principle of SRM and the mathematical model of motor,this paper analyses the main methods of restraining SRM torque ripple at present.And their advantages and disadvantages are also analysed.The commonly used linear TSF function curve is introduced.The structure of SRM control system based on TSF control strategy is also discussed.The traditional linear TSF is analyzed,aiming at the problems of poor current tracking effect and high current peak value in overlapping area,which lead to high torque ripple and copper loss.A quadratic compensation curve is proposed based on the linear TSF,which reduces the difficulty of current tracking.The parameters of the compensation curve are tuned.The performance of the improved TSF based on the compensation curve is compared with the traditional linear TSF.The results show that the improved TSF based on the compensation curve can effectively suppress the torque ripple and reduce the copper loss.Based on the improved TSF,the influence of opening angle and overlap angle on SRM torque ripple and copper loss is analyzed.An improved TSF optimization method based on genetic algorithm is proposed.Copper loss and torque ripple rate are selected as optimization objectives.Opening angle,overlap angle and quadratic compensation curve parameters are optimized offline.In order to solve the problem that traditional genetic algorithm is easy to fall into local optimal solution,adaptive crossover and mutation operators are adopted.Genetic algorithm combined with online simulation obtains the improved TSF curve with optimal torque ripple and copper loss at different speed.The SRM control system based on TSF strategy is built by using MATLAB/Simulink simulation software.The optimal improved TSF obtained at different rotating speeds is applied to the system and compared with the improved TSF after parameter tuning.The experiment proves that the optimized result based on genetic algorithm can improve the current tracking effect,and effectively suppress the torque ripple and reduce the copper loss produced during commutation.Finally,the hardware and software design of SRM control system based on DSP is introduced,and the test platform of SRM drive system is built.Experiments are carried out on this platform to further verify the effectiveness and feasibility of TSF optimization method. |
