Study of a control strategy simulation based on genetic algorithm optimization for DC-DC converter of fuel cell vehicle

Buck-Boost circuit is a kind of non-isolated DC-DC converter for fuel cell vehicles. In this paper, a PID control strategy with genetic algorithm to optimize the BP neural network is proposed for the problem of mismatch between DC-DC power battery and vehicle bus voltage in fuel cell vehicles. With simulation, compared with BP-PID and PID, the GA-BP-PID is verified that, the control strategy can achieve a more stable output voltage, faster response speed and stronger disturbance resistance of the Buck-Boost converter. The novel GA-BP-PID scheme proposed in this study was proven efficient in reducing the oscillation time and overshoot.