Optimization of Passivity-Based Controller for a Hybrid Vehicle Power Source using the Gray Wolf Algorithm

This paper introduces an enhanced approach for the control of hybrid sources, specifically fuel cells and batteries, within a hybrid electric vehicle. The proposed enhancement involves integrating the Gray Wolf Optimization algorithm with the passive-based control technique. The primary aim of this research is to enhance the operational characteristics of the studied system that is governed by the passivity-based control approach. This enhancement is achieved by optimizing the damping matrix parameter using the Gray Wolf Optimization algorithm. It is noteworthy that prior studies utilizing this technique did not address its impact, considering it a stochastic value ranging from 0 to 1. The central focus remains on proficiently and effectively managing the energy exchange between the two sources. Through Simulink-Matlab simulations, the outcomes underscore the influence of the damping matrix parameter on the overall dynamic performance of the system. Moreover, these results emphasize its pivotal role in achieving tracking precision and system robustness. This research constitutes a significant advancement in the realm of sophisticated control methodologies for hybrid power sources. Furthermore, it lays the groundwork for future investigations and the potential implementation of supplementary energy management strategies based on this innovative technique.