Lifecycle assessment of diesel, diesel-electric and hydrogen fuel cell transit buses with fuel cell degradation and battery aging using machine learning techniques

Ahmadi, Pouria; Raeesi, Mehrdad; Changizian, Sina; Teimouri, Aidin; Khoshnevisan, Alireza

doi:10.1016/j.energy.2022.125003

Cited by 40 publications

(5 citation statements)

References 33 publications

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“…Through the optimized use of resources and enhanced production efficiency, ML is contributing to the reduction of the environmental impact of fuel production. It aids in the development of cleaner, more sustainable fuels by analyzing and predicting the environmental impact of various fuel types, thereby guiding the industry toward more ecofriendly alternatives. , This commitment to sustainability is crucial in addressing the urgent global environmental challenges faced today. In conclusion, the incorporation of ML within the realm of fuel development is bringing forth substantial advancements in efficiency, sustainability, and innovation.…”

Section: Energy and Fuelsmentioning

confidence: 99%

Advances, Synergy, and Perspectives of Machine Learning and Biobased Polymers for Energy, Fuels, and Biochemicals for a Sustainable Future

Bin Abu Sofian,

Sun,

Gupta

et al. 2024

Energy Fuels

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This review illuminates the pivotal synergy between machine learning (ML) and biopolymers, spotlighting their combined potential to reshape sustainable energy, fuels, and biochemicals. Biobased polymers, derived from renewable sources, have garnered attention for their roles in sustainable energy and fuel sectors. These polymers, when integrated with ML techniques, exhibit enhanced functionalities, optimizing renewable energy systems, storage, and conversion. Detailed case studies reveal the potential of biobased polymers in energy applications and the fuel industry, further showcasing how ML bolsters fuel efficiency and innovation. The intersection of biobased polymers and ML also marks advancements in biochemical production, emphasizing innovations in drug delivery and medical device development. This review underscores the imperative of harnessing the convergence of ML and biobased polymers for future global sustainability endeavors in energy, fuels, and biochemicals. The collective evidence presented asserts the immense promise this union holds for steering a sustainable and innovative trajectory.

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Section: Energy and Fuelsmentioning

confidence: 99%

Advances, Synergy, and Perspectives of Machine Learning and Biobased Polymers for Energy, Fuels, and Biochemicals for a Sustainable Future

Bin Abu Sofian,

Sun,

Gupta

et al. 2024

Energy Fuels

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“…The environmental emissions during the power battery recycling stage primarily come from the emissions generated during the disassembly process due to the consumption of electricity and heat, the environmental emissions during the production of chemical agents used in battery material recycling, and the environmental impact and benefits resulting from battery material recycling. The environmental emission matrix for this stage is represented by Equation (8).…”

Section: Mathematical Evaluation Model For Environmental Emissionsmentioning

confidence: 99%

“…Significant research has been conducted both domestically and internationally regarding the life cycle assessment of power batteries, focusing on their resource and environmental impacts. There have been many studies on the life cycle assessment of power batteries for pure electric vehicles [3,4], plug-in hybrid vehicles [5,6], and fuel cell vehicles [7,8], in order to obtain the energy consumption and emissions of power batteries during the production, manufacturing, assembly, and use stages. Majeau [9], Oliveira [10], and Marques [11] conducted a life cycle assessment on nickel hydrogen batteries, nickel cobalt manganese lithium ion batteries (Lithium ion NCM), and iron phosphate lithium ion batteries (LiFePO 4 LFP) for plug-in hybrid vehicles, and compiled a transparent life cycle inventory in a component manner.…”

Section: Introductionmentioning

confidence: 99%

Study on the Life Cycle Assessment of Automotive Power Batteries Considering Multi-Cycle Utilization

Liu,

Zhang,

Hao

et al. 2023

Energies

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This article utilizes the research method of the Life Cycle Assessment (LCA) to scrutinize Lithium Iron Phosphate (LFP) batteries and Ternary Lithium (NCM) batteries. It develops life cycle models representing the material, energy, and emission flows for power batteries, exploring the environmental impact and energy efficiency throughout the life cycles of these batteries. The life cycle assessment results of different power battery recycling process scenarios are compared and analyzed. This study focuses on retired LFP batteries to assess the environmental and energy efficiency during the cascade utilization stage, based on a 50% Single-Cell Conversion Rate (CCR). The findings of the research reveal that, in terms of resource depletion and environmental emission potential, LFP batteries exhibit lower impacts compared to NCM batteries. The use of hydrometallurgy in recovering LFP power batteries leads to minimal life cycle resource consumption and environmental emission potential. During the cascade utilization stage of LFP batteries, significant benefits are noted, including a 76% reduction in mineral resource depletion (ADP e) and an 83% reduction in fossil energy depletion (ADP f), alongside notable reductions in various environmental impact factors. Simultaneously, considering the sensitivity of life cycle assessment indicators and their benefit percentages to different CCRs, it is observed that ODP exhibits the highest sensitivity to CCR changes, while evaluation indicators such as HTP, AP, and GWP show relatively lower sensitivity. This study can provide an effective reference for the establishment of an energy saving and emission reduction evaluation system of power batteries.

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“…Proton exchange membrane fuel cells (PEMFCs) are, due to their high energy density, low-temperature operation, and lightweight, a suitable fuel cell for both light-and heavy-duty transportation. 2 However, the widespread commercialization of PEMFCs in automotive vehicles is currently impeded by their high cost and limited lifetime, which in turn is greatly attributed to the large amounts of platinum needed to catalyze the sluggish oxygen reduction reaction (ORR) kinetics in the cathode. 3 Thus, a large portion of PEMFC research has focused on lowering their cost by decreasing the amount of platinum in the cathode through alloying and microstructuring.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Moreover, they hold great potential to substitute fossil-powered internal combustion engines, which makes them suitable candidates for the decarbonization of transport systems. Proton exchange membrane fuel cells (PEMFCs) are, due to their high energy density, low-temperature operation, and lightweight, a suitable fuel cell for both light- and heavy-duty transportation . However, the widespread commercialization of PEMFCs in automotive vehicles is currently impeded by their high cost and limited lifetime, which in turn is greatly attributed to the large amounts of platinum needed to catalyze the sluggish oxygen reduction reaction (ORR) kinetics in the cathode .…”

Section: Introductionmentioning

confidence: 99%

Tuning the Activity of Silver Alloys for the Oxygen Reduction Reaction in Alkaline Media

Montserrat‐Sisó

Wickman

2023

ACS Appl. Energy Mater.

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Ag-based catalysts have recently attracted much attention as potential candidates to substitute costly Pt-based electrocatalysts for the oxygen reduction reaction (ORR) in alkaline media. Although the electrocatalytic activity of Pt-based alloys is known to exhibit a strong dependence on their electronic structures, a relationship between electronic structure and the ORR mechanism in Ag-based alloys still remains to be elucidated. Herein, by means of physical vapor deposition, we prepare Ag binary thin films (CoAg, CuAg, AuAg, and FeAg) with well-controlled compositions as a tool to investigate the ORR mechanism on Ag surfaces. The bimetallic thin films are evaluated for their ORR performance in alkaline media, and their specific activity at 0.8 VRHE is shown to correlate with the Ag electronic structure. Even though all thin films show different responses to potential cycling, all bimetallic samples exhibit a surface Ag enrichment after ORR. It is shown that the ORR occurs through different mechanisms on these Ag-rich surfaces, which in turn is potential-dependent. Tafel slopes reveal faster ORR kinetics at low overpotentials on all surfaces, whereas only CuAg surpasses pure Ag at higher overpotentials. Moreover, despite their incomplete O2 reduction, CuAg and AuAg exhibit an overall superior ORR activity over pure Ag, with a more than 2-fold increase in specific activity at 0.8 VRHE attributed to enhancements originating from electronic effects and surface defects, respectively. Since the potential-dependent improved ORR mechanism observed for Ag bimetallic samples makes a rational design of Ag-based electrocatalysts difficult, these results aim to provide insights for a more tailored design of electrocatalysts by shedding light on the mechanisms through which the ORR kinetics are improved on Ag surfaces in alkaline media.

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Lifecycle assessment of diesel, diesel-electric and hydrogen fuel cell transit buses with fuel cell degradation and battery aging using machine learning techniques

Cited by 40 publications

References 33 publications

Advances, Synergy, and Perspectives of Machine Learning and Biobased Polymers for Energy, Fuels, and Biochemicals for a Sustainable Future

Advances, Synergy, and Perspectives of Machine Learning and Biobased Polymers for Energy, Fuels, and Biochemicals for a Sustainable Future

Study on the Life Cycle Assessment of Automotive Power Batteries Considering Multi-Cycle Utilization

Tuning the Activity of Silver Alloys for the Oxygen Reduction Reaction in Alkaline Media

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