Research on control strategy of bidirectional DC-DC converter based on improved genetic algorithm

Abstract

The bidirectional DC-DC converter was selected as the research object. Based on the connection topology of energy storage and consumption components in the hybrid energy storage system, power demand indicators were determined for different energy flow directions, and the parameters of the main converter components and appropriate circuit components were established. A circuit model of buck/boost was constructed, and an adaptive fast terminal sliding mode control strategy was designed. The controller parameters were optimized using an improved genetic algorithm. Different control parameters have different control effects. In order to obtain better voltage output characteristics,the parameters of the adaptive fast terminal sliding mode control strategy were optimized.The proposed method can be verified to exhibit good control performance through simulation.

Keywords

• genetic algorithm;BP neural network;self disturbance rejection;Cuk converter;DC-DC