Developing a Hydrogen Fuel Cell Vehicle (HFCV) Energy Consumption Model for Transportation Applications

• Published in: Energies (Basel) Vol. 15; no. 2; p. 529
• Main Authors: Ahn, Kyoungho, Rakha, Hesham A.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2022
• Subjects: Acceleration; Advisors; Algorithms; Automobile industry; Automotive engineering; Braking systems; Electric vehicles; Energy consumption; energy consumption model; Energy efficiency; Energy management; Engineers; Environmental engineering; Fuel cell vehicles; Fuel cells; Fuel consumption; Fuel technology; Global positioning systems; GPS; Hydrogen; hydrogen fuel cell vehicle (HFCV); Hydrogen fuels; Infrastructure; Internal combustion engines; microscopic energy model; Optimization; Renewable resources; Simulation; Smartphones; Traffic models; Traffic speed; Transportation; Transportation applications; Velocity; United States > US
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en15020529

This paper presents a simple hydrogen fuel cell vehicle (HFCV) energy consumption model. Simple fuel/energy consumption models have been developed and employed to estimate the energy and environmental impacts of various transportation projects for internal combustion engine vehicles (ICEVs), battery electric vehicles (BEVs), and hybrid electric vehicles (HEVs). However, there are few published results on HFCV energy models that can be simply implemented in transportation applications. The proposed HFCV energy model computes instantaneous energy consumption utilizing instantaneous vehicle speed, acceleration, and roadway grade as input variables. The mode accurately estimates energy consumption, generating errors of 0.86% and 2.17% relative to laboratory data for the fuel cell estimation and the total energy estimation, respectively. Furthermore, this work validated the proposed model against independent data and found that the new model accurately estimated the energy consumption, producing an error of 1.9% and 1.0% relative to empirical data for the fuel cell and the total energy estimation, respectively. The results demonstrate that transportation engineers, policy makers, automakers, and environmental engineers can use the proposed model to evaluate the energy consumption effects of transportation projects and connected and automated vehicle (CAV) transportation applications within microscopic traffic simulation models.