Optimal Study Of Buck-Boost Matrix Converter Based On Particle Swarm Optimization

Matrix converter has simple topology structure and a series of idealelectrical characteristics, and has become a hotspot in research of powerelectronics. The reason that low voltage transfer ratio to make it has notbeen popularized up to now. In this paper, the Buck-Boost matrix converter(BBMC) of the voltage transfer ratio can be greater than1, can also be lessthan1, and has good output waveform, small harmonic content. Studiesfound that BBMC output harmonic distortion is directly related to its maincircuit parameters and its control parameters. The research on optimaldesign of BBMC to improve the quality of power has theoretical andpractical significance.The basic structure and working principle of BBMC is expoundedfirstly, its inverter using sliding mode control, discrete sliding mode control,double-loop control strategy is analyzed and simulated respectively. Theprinciple of PSO is analyzed, aiming at the defects of PSO is easy to fallinto local optimum, the PSO is improved by combining genetic algorithmand immune algorithm with dynamic inertia weight factor and learningfactor is adopted. BBMC parameters as the location information of PSO, themodel of BBMC based on double-loop control strategy and testing model ofharmonic distortion degree of output waveforms is built in Matlab， BBMCoutput harmonic distortion degree As a fitness using sim() to obtain for themodel， Write program of PSO optimize BBMC main circuit parameters andits PI control parameters of the double-loop control strategy, and optimizingabove parameters respectively，the parameters obtained by PSO is analyzed.A prototype of BBMC has been manufactured, in which DSP is acted ascontroller and MOSFET as power switch in main circuit, and correspondingapplication software has been developed. This prototype has been debuggedand tested combined with application software.