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Energy Management of Heavy-Duty Fuel Cell Electric Vehicles: Model Predictive Control for Fuel Consumption and Lifetime Optimization

Alessandro Ferrara, Michael Okoli, Stefan Jakubek, Christoph Hametner

2020IFAC-PapersOnLine26 citationsDOIOpen Access PDF

Abstract

This paper investigates the application of a simple but effective model predictive control concept for the fuel consumption and system lifetime optimization of a heavy-duty fuel cell electric vehicle. Energy management strategies primarily help extend the fuel cell lifetime by limiting shutdowns, transients and high-power operations to avoid detrimental conditions. In this framework, the proposed online control scheme determines a significant reduction of the average fuel cell power change rate and a small fuel consumption increment with respect to the control law that minimizes the fuel consumption, computed offline through the Pontryagin’s minimum principle. These results refer to the real-world driving mission of a road freight vehicle, including the elevation gradient of the road, which highly affects the load request in downhill and uphill sections. However, this preliminary study does not include a speed prediction model, but it assumes that the speed is known without uncertainties over a relatively short time horizon.

Topics & Concepts

Automotive engineeringModel predictive controlHeavy dutyFuel efficiencyEnergy managementFuel cellsConsumption (sociology)Energy consumptionEnvironmental scienceControl (management)Energy (signal processing)Waste managementComputer scienceEngineeringElectrical engineeringMathematicsStatisticsChemical engineeringSociologyArtificial intelligenceSocial scienceFuel Cells and Related MaterialsElectric and Hybrid Vehicle TechnologiesAdvanced Battery Technologies Research
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