Output Voltage Optimization Of Switched Reluctance Generator Based On Iterative Learning Control

As a new type of generator,Switch Reluctance Generator attracts the attention of scholars in recent years with its features such as simple structure,low-cost,strong fault-tolerant,high reliability and output is DC,which is convenient to be as the DC source and can be grid-connected through the inverter.But due to the special doubly salient structure and special way of power supply,when used as a DC voltage source,the output voltage ripple is large,the quality of power generation is reduced,and the application of SRG in the field of power generation is limited.So how to reduce the fluctuation of output voltage effectively and improve the quality of power generation has become the focus of domestic and international scholars.Firstly the paper introduces the development situation and the research status of SRG,aiming at the problem of large output voltage fluctuation,the reason is analyzed and the current distribution strategy is put forward to reduce the output voltage fluctuation in the commutation interval.Secondly this paper introduces the traditional current control method and analyses the principle and characteristics of ILC,according to the characteristics of SRG the current control strategy is proposed based on PWM cycle,after the current distribution function of each phase of the specified current through the iterative learning algorithm to learn and adjust in order to achieve accurate tracking of the desired current,then achieve the purpose of reducing the output voltage fluctuation.Finally the simulation model and system test platform of SRG voltage control system are set up,simulation and experimental research based on current distribution strategy and ILC algorithm are carried out.The current tracking effect and the output voltage effect are given under different current,speed,voltage and load.The correctness and effectiveness of the proposed scheme are demonstrated by simulation and experiment.