Hierarchical Fuel-Cell Airpath Control: an Efficiency-Aware MIMO Control Approach Combined with a Novel Constraint-Enforcing Reference Governor

TL;DR

This paper introduces a hierarchical MIMO control strategy with a novel constraint-enforcing reference governor for PEMFC air supply systems, improving efficiency and power tracking accuracy.

Contribution

It develops a new MIMO control scheme combined with a cascade and cross-section reference governor to enhance efficiency and constraint management in fuel cell air supply control.

Findings

Up to 7.36% reduction in hydrogen fuel consumption.

Up to 3.68% improvement in power tracking accuracy.

Significant enhancement in OER constraint enforcement.

Abstract

This paper presents a hierarchical multivariable control and constraint management approach for an air supply system for a proton exchange membrane fuel cell (PEMFC) system. The control objectives are to track desired compressor mass airflow and cathode inlet pressure, maintain a minimum oxygen excess ratio (OER), and run the system at maximum net efficiency. A multi-input multi-output (MIMO) internal model controller (IMC) is designed and simulated to track flow and pressure set-points, which showed high performance despite strongly coupled plant dynamics. A new set-point map is generated to compute the most efficient cathode inlet pressure from the stack current load. To enforce OER constraints, a novel reference governor (RG) with the ability to govern multiple references (the cascade RG) and the ability to speed up as well as slow down a reference signal (the cross-section RG) is developed and tested. Compared with a single-input single-output (SISO) air-flow control approach, the proposed MIMO control approach shows up to 7.36 percent lower hydrogen fuel consumption. Compared to a traditional load governor, the novel cascaded cross-section RG (CC-RG) shows up to 3.68 percent less mean absolute percent error (MAPE) on net power tracking and greatly improved worst-case OER on realistic drive-cycle simulations. Control development and validations were conducted on two fuel cell system (FCS) models, a nonlinear open-source model and a proprietary Ford high-fidelity model