A method for determining the optimal delivered hydrogen pressure for fuel cell electric vehicles

Lin, Zhenhong; Ou, Shiqi; Elgowainy, Amgad; Reddi, Krishna; Veenstra, Mike; Verduzco, Laura

doi:10.1016/j.apenergy.2018.02.041

Cited by 61 publications

(14 citation statements)

References 23 publications

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“…Lin and Greene were the first to use the gamma distribution for daily driving distance in the analysis of plug-in electric vehicle energy consumption due to its non-negativity, skewness flexibility, and specification ease [25]. The gamma method was later validated by Lin et al, using GPS-tracked driving data [26], and it has been commonly adopted in plug-in electric vehicle energy studies [27][28][29]. The gamma distribution is described as follows [27,28]:…”

Section: Methods 231 Travel and Charging Patternmentioning

confidence: 99%

“…The gamma method was later validated by Lin et al, using GPS-tracked driving data [26], and it has been commonly adopted in plug-in electric vehicle energy studies [27][28][29]. The gamma distribution is described as follows [27,28]:…”

Section: Methods 231 Travel and Charging Patternmentioning

confidence: 99%

“…The mode of the gamma distribution is (α − 1) β and can be approximated by the daily round-trip distance to work or the most frequent destination. As a result, the gamma distribution can be specified by knowing the annual distance and the commuting distance, as described in Lin et al [28].…”

Section: Methods 231 Travel and Charging Patternmentioning

confidence: 99%

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Actual Electricity Utility Factor of Plug-In Hybrid Electric Vehicles in Typical Chinese Cities Considering Charging Pattern Heterogeneity

Hao

Yuan

Wang

et al. 2021

WEVJ

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The actual energy saving effect of plug-in hybrid vehicles (PHEVs) is usually evaluated by the electricity utility factor (UF) in a standardized charging pattern. To further evaluate the impacts of the charging pattern heterogeneity of PHEV, actual vehicle travel data are adopted to classify the charging pattern in seven typical Chinese cities and derive its impacts on actual UF. Additionally, UF curves are fitted as power exponential functions. The result shows that during daily usage, UF can reach over 0.8 for 50 km all-electric-range PHEVs for the 77% frequently charging adopters, while it is as low as 0.1 for the 3% rarely charging adopters. Comprehensive UF values at an actual charging pattern are 0.53 and 0.68 for the 50 km and 80 km all-electric-range PHEVs, and the values are 0.03 and 0.04 smaller than the standard UF, respectively.

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Section: Methods 231 Travel and Charging Patternmentioning

confidence: 99%

Section: Methods 231 Travel and Charging Patternmentioning

confidence: 99%

See 1 more Smart Citation

Actual Electricity Utility Factor of Plug-In Hybrid Electric Vehicles in Typical Chinese Cities Considering Charging Pattern Heterogeneity

Hao

Yuan

Wang

et al. 2021

WEVJ

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“… 𝑀 𝑀 > 1: Normal shock wave in the mixing section. Use of Equation (9) and Equation (10) to calculate the flow condition at section 3, just as for the critical mode,  𝑀 𝑀 < 1: No normal shock wave in the mixing section.…”

Section: Breakdown Pressure Of the Ejectormentioning

confidence: 99%

“…Lin et al [10] proposed a method to determine the optimal delivered hydrogen pressure, based on the economic analysis of the delivery of hydrogen, refuelling and inconvenience cost. They found out that the optimal pressure is highly dependent on the number of stations, adoption rate or driving habits.…”

Section: Introductionmentioning

confidence: 99%

Numerical optimization of a novel gas-gas ejector for fuelling of hydrogen vehicles

Rogié

Kærn

Wen

et al. 2020

International Journal of Hydrogen Energy

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Technoeconomic Optimization of a Photovoltaic Wind Energy‐Based Hydrogen Refueling Station: A Case Study

2023

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Increased use of renewable energy sources is expected to contribute to long‐term sustainability and robust economic growth. A better global economy and lower greenhouse gas emissions are possible due to intensive research into more effective energy production, storage, and utilization technologies. The exciting solution for advancing the development of green hydrogen production and the clean transportation sector is the conversion of electrical energy generated from wind parks into green hydrogen. Therefore, herein, a technoeconomic optimization of hydrogen production for refueling fuel cell vehicles by comparing two different renewable energy sources is presented. Results obtained in this article demonstrate that Riyadh possesses sufficient wind speed and sunlight, which can be used to produce renewable hydrogen. It is evident from the evaluated and optimized results that the selected wind‐based hybrid energy system has the lowest net present cost, levelized cost of energy, and levelized cost of hydrogen of $247,654.00, $/kWh 0.1720, and $/kg 4.23, respectively, as compared to the other system counterpart, making the selected optimized hybrid energy system the preferred choice to fulfill the electricity and hydrogen production demand of the refueling fuel cell vehicles. It is expected that the stakeholders through this study can encourage the production of hydrogen in Saudi Arabia.

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A method for determining the optimal delivered hydrogen pressure for fuel cell electric vehicles

Cited by 61 publications

References 23 publications

Actual Electricity Utility Factor of Plug-In Hybrid Electric Vehicles in Typical Chinese Cities Considering Charging Pattern Heterogeneity

Actual Electricity Utility Factor of Plug-In Hybrid Electric Vehicles in Typical Chinese Cities Considering Charging Pattern Heterogeneity

Numerical optimization of a novel gas-gas ejector for fuelling of hydrogen vehicles

Technoeconomic Optimization of a Photovoltaic Wind Energy‐Based Hydrogen Refueling Station: A Case Study

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