Volume 45: Energy Transitions toward Carbon Neutrality: Part VIII

Particle swarm optimization Fuzzy algorithm applied to temperature control in PEM fuel cell systems Zhanglin Ruan, Handong Wu, Ruilin Wang, ZhenYu Tian, Wenjia Li

Abstract

Working temperature is a key issue that affects the performance of proton exchange membrane fuel cells (PEMFCs). Proper thermal management can improve the PEMFC output performance and longevity. To deal with the problems of poor robustness and slow
response time of traditional temperature control curves, this paper establishes a dynamic temperature model of PEMFC. It proposes a particle swarm optimized fuzzy proportional-integral-derivative (PSO-Fuzzy-PID)-based temperature control strategy to achieve dynamic control of the electric reactor temperature. The performance of PSO-Fuzzy-PID temperature control is verified for step load, dynamic load, and variable target conditions, and its effectiveness is compared with that of an ordinary PID controller. The results show that the proposed method has the advantages of fast convergence speed, good dynamic performance, and strong disturbance immunity.
The PSO-Fuzzy-PID temperature controller ensures temperature fluctuations within 0.5°C of dynamic perturbations and is capable of strong tracking control of variable targets.

Keywords PEMFC, Temperature management, Thermal model, Particle Swarm Optimization Fuzzy Control