Implementation of an on-line multi-objective particle swarm optimization controllers gains self-adjusted of FC/UC system devoted for electrical vehicle

摘要

In the context of ameliorating the electrical vehicle dynamic, this paper suggests an on-line control based on multi-objective Particle-Swarm-Optimization (MOPSO). This control is applied to Fuel Cell (FC)/Ultra-Capacitor (UC) vehicle in order to enhance the dynamic system and to reduce fuel consumption. The traction system, comprising a permanent magnet synchronous motor (PMSM) as well as the main power source and the auxiliary energy device, is controlled using PI controllers. The regulators' gains are adjusted by an energy management system based on off-line PSO, in the first step and on-line MOPSO in the second one. In order to demonstrate the effectiveness of the two proposed approaches, a New York City cycle profile is implemented as the reference speed of the vehicle model. Theoretical analysis and outcomes display that the on-line self-adjusted PI regulators by MOPSO established on the Integral Absolute Error (IAE) index contributes better to the power management system than conventional regulators based on the same index. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.