Multi-objective Optimization Control Strategy of Traction Inverter Based on Particle Swarm Algorithm

Abstract:

In order to solve the problem that the unbalance of neutral-point voltage and output current harmonics cannot be effectively controlled at the same time, a multi-objective optimal control strategy for three-level traction inverter based on particle swarm optimization was proposed in this paper. Firstly, a mathematical model of harmonic suppression and neutral-point voltage balance control was established. Then the multi-objective optimization model was built with the idea of penalty function. The object function of the optimum problem was to minimize the total harmonic distortion rate of the output currents. And the key constraint was to make the neutral-point voltage fluctuation as small as possible. Finally, the PSO algorithm was applied to solve the optimum problem, and the goal of suppressing the output current harmonics and reducing the neutral-point voltage fluctuation was achieved. Simulation and experimental results verify the effectiveness of the proposed multi-objective optimal control strategy.