Optimized Passivity-based Control of a Hybrid Electric Vehicle Source using a Novel Equilibrium Optimizer

Abstract

Passivity-based control is a well-known strategy for synthesizing stable controllers because it models and manages systems based on their global state space equations. It also permits proving the system's stability by making it passive, which is an undeniable advantage over traditional controllers that have limitations in terms of applications, saturation, and the inability to verify stability. Previous research used nonlinear control based on passivity method to control the energy distribution between the embedded sources, they did not investigate the impact of the dumping matrix parameter, which was typically considered to be a positive random value. In contrast, the results of this investigation show that it significantly affects system behaviour, especially in the transient-state domain. The primary objective of this study is to develop and evaluate an energy management strategy for hybrid electric vehicles powered by Fuel Cells as the primary source and Supercapacitors as the secondary source. The fast response with less overshoot is ensured by optimizing the damping matrix parameter using a well-known optimization technique named Novel Equilibrium Optimizer. The proposed technique is successfully demonstrated in a Matlab® simulation environment, and the control system exhibits robust dynamic behaviour. Finally, despite the complexity of this technique's mathematical proof, it provides a simple, efficient feedback control law for a real electrical vehicle application.