Real-time optimal hierarchical energy and power management system for fuel cell-battery hybrid electric vehicles

Abstract

The transportation sector is a major contributor to global greenhouse gas emissions, with heavy-duty vehicles (HDVs) accounting for a significant share. Hydrogen fuel cell technology, particularly Proton Exchange Membrane Fuel Cells (PEMFCs), offers a promising zero-emission solution for HDVs due to their high efficiency and environmental benefits. However, standalone PEMFC systems face challenges in dynamic response and energy recovery. To overcome these limitations, Fuel Cell Hybrid Electric Vehicles (FCHEVs) integrate PEMFCs with batteries. This hybridization requires a robust Energy Management System (EMS) for optimal power distribution. The main objective is to minimize the hydrogen consumption while satisfying the power demand and the battery state-of-charge (SOC) constraints in the presence of fuel cell and battery degradation over time. This study presents a hierarchical optimal energy and power management system for FCHEVs with multiple PEMFC stacks and a battery. The upper layer of the hierarchy consists of a dual-rate economic model predictive controller which optimally splits the total power demand between the 'slow' fuel cell system and the 'fast' battery considering total hydrogen consumption. The second-layer controller then distributes the power demand allocated to the fuel cell among the individual stacks, taking into account the hydrogen consumption and degradation of individual stacks. The fast transient power demands which cannot be met by the fuel cell stacks are identified and allocated to the battery control system. A mechanistic dynamic PEMFC model is combined with a battery model to support the proposed hierarchical control strategy. Simulation results show that the proposed method consistently achieves lower hydrogen consumption than two benchmark strategies-rule-based control and SOC trajectory control.