Analysis of refueling behavior of hydrogen fuel vehicles through a stochastic model using Markov Chain Process

N. Isaac and A.K. Saha

Renewable and Sustainable Energy Reviews, 2021, vol. 141, issue C

Abstract: Fueling of hydrogen vehicles is an important factor that needs to be analyzed and optimized for hydrogen fuel vehicles to attain significant market penetration and relevance. This paper presents and applies a stochastic model that integrates the Markov Chain Process to trend the refueling patterns of hydrogen fuel vehicles and driver behavior within the South African transport sector. The aim is to understand the stochastic nature of the daily refueling behavior of hydrogen fuel vehicles. The key contribution of this paper includes the development of data on refueling behavior of hydrogen fuel vehicles such as fueling times, fueling capacity, and time spent at refueling stations using the algorithm which are important factors that needs to be analyzed and optimized for hydrogen fuel vehicles to attain significant market penetration and relevant issues such as infrastructure development. This accounts for the lack of data within the South African context on refueling patterns of hydrogen fuel vehicle users and aids in understanding the expected hydrogen fuel consumption (demand) a typical station would experience. Another significant contribution is the daily and weekly refueling patterns (profiles) of hydrogen fuel vehicles generated by the model. This provides useful insights and trends on refueling patterns, specifically in South Africa, where there is little hydrogen fuel vehicles present. The accuracy of the refueling patterns was ascertained by verifying the model against real-life hydrogen fuel vehicle data and through sensitivity analysis. Also, the model can be applied to quantify the effects of different parameters on refueling patterns.

Keywords: Hydrogen fuel vehicles; Markov chain; Stochastic; Refueling; Modeling; Driver behavior; Analysis; Data (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.rser.2021.110761

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