Modeling the Performance and Cost of Lithium-Ion Batteries for Electric-Drive Vehicles, Third Edition

Nelson, P.A.; Ahmed, Shabbir; Gallagher, Kevin G.; Dees, Dennis W.

doi:10.2172/1503280

Cited by 80 publications

(49 citation statements)

References 30 publications

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“…We assumed a value of $185/kWh for Cnew in 2020, which we took as the current manufacturing price of BEV lithium-ion battery pack. This price is consistent with manufacturing costs estimated using Argonne BatPaC model for typical battery pack designs and current production volumes (Nelson et al 2019). For MY2025, we used Cnew from Autonomie modeling, starting at $150/kWh in 2025 (Islam et al 2020).…”

Section: Battery Pack Costs and Considerationsmentioning

confidence: 65%

“…Hamza et al (2020), MIT Energy Initiative ( 2019), Morrison et al (2018), Elgowainy et al (2018), Rousseau et al (2015), Burke et al (2015), NRC (2013), and Delucchi and Lipman (2001) all estimated vehicle costs using estimates of costs of vehicle components. Often cost models and projections are available for individual components, including PEV battery packs (e.g., Nelson et al 2019) and fuel cells and hydrogen tanks for FCEVs (James 2020;Kleen and Padgett 2021). Other LDV TCO studies have used more aggregate or top-down estimates derived from values reported in earlier literature or based on MSRPs of conventional or hybrid electric vehicles and modifying these to account for differences in prices of vehicles with other powertrains (e.g., Al-Alawi and Bradley 2013).…”

Section: Other Vehicle Cost Literaturementioning

confidence: 99%

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Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

Burnham

Gohlke

Rush

et al. 2021

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Erratum to accompany "Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains" (Argonne National Laboratory report ANL/ESD-21/4) July 2021After initial publication of this report, the authors were made aware of some minor typographical errors and omissions. As these mistakes can potentially confuse the results, they have been corrected in the present version. In the executive summary on page xxiii, "HEV" (hybrid electric vehicle) was once written as "BEV" (battery electric vehicle), contrary to the findings shown in the accompanying figure. Tables B.5 and B.6 previously stated the incorrect all-electric ranges for the battery electric vehicle and plug-in hybrid electric vehicle for the class 8 day cab tractor and class 4 delivery truck, respectively. These ranges have been corrected. Additionally, two sentences were added to Appendix B on page 143 to explicitly state the correctly modeled all-electric range for all medium-and heavy-duty vehicles.

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Section: Battery Pack Costs and Considerationsmentioning

confidence: 65%

Section: Other Vehicle Cost Literaturementioning

confidence: 99%

Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

Burnham

Gohlke

Rush

et al. 2021

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“…[14,23] Safety rating for each battery chemistry is qualitatively described, primarily dependent on battery stability, thermal behavior, and resiliency to abuse. [15] [14][15][16][17][18][19][20][21][22][23][25][26][27] Li-ion battery chemistry Cell-level specific energy [Wh kg −1 their relatively poor safety rating, with a far lower thermal runaway temperature than its competitors. [15,23] Other LIB chemistries, such as LCO were intentionally omitted due to their decreasing relevance in vehicle-and grid-scale energy storage systems.…”

Section: Lithium-ion Battery Technologiesmentioning

confidence: 99%

“…Li-ion cell production is generally divided into three phases: electrode manufacturing, cell assembly, and cell finishing (see Figure 2). Electrode manufacturing is largely independent of [26,82,90,92,93] cell type but may vary by battery chemistry. Cell assembly and cell finishing are typically independent of battery chemistry, but vary by cell configuration.…”

Section: Battery Manufacturingmentioning

confidence: 99%

Life‐Cycle Assessment Considerations for Batteries and Battery Materials

Porzio

Scown

2021

Advanced Energy Materials

142

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Rechargeable batteries are necessary for the decarbonization of the energy systems, but life‐cycle environmental impact assessments have not achieved consensus on the environmental impacts of producing these batteries. Nonetheless, life cycle assessment (LCA) is a powerful tool to inform the development of better‐performing batteries with reduced environmental burden. This review explores common practices in lithium‐ion battery LCAs and makes recommendations for how future studies can be more interpretable, representative, and impactful. First, LCAs should focus analyses of resource depletion on long‐term trends toward more energy and resource‐intensive material extraction and processing rather than treating known reserves as a fixed quantity being depleted. Second, future studies should account for extraction and processing operations that deviate from industry best‐practices and may be responsible for an outsized share of sector‐wide impacts, such as artisanal cobalt mining. Third, LCAs should explore at least 2–3 battery manufacturing facility scales to capture size‐ and throughput‐dependent impacts such as dry room conditioning and solvent recovery. Finally, future LCAs must transition away from kg of battery mass as a functional unit and instead make use of kWh of storage capacity and kWh of lifetime energy throughput.

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“…For instance, in a typical Li-ion battery cell, the properties of electrode materials such as charge capacity and energy density are responsible for ∼50–70% of the cell energy density and cost, whereas materials stability strongly affects the cell lifetime. 1 − 6 NAtrium SuperIonic CONductor (NASICON)-type framework compounds, originally sought as suitable solid electrolytes for high-temperature liquid sodium–sulfur batteries, 7 are attracting increasing attention as potent materials for Na-ion insertion (“rocking chair”) battery (NIB) electrodes. 8 , 9 Presently, NASICON-structured phosphates with a general formula of Na 1–4 M′M″(PO 4 ) 3 are probably the most studied and applied polyanion electrode materials for NIBs.…”

Section: Introductionmentioning

confidence: 99%

Peculiarities of Phase Formation in Mn-Based Na SuperIonic Conductor (NaSICon) Systems: The Case of Na_1+2xMn_xTi_2–x(PO₄)₃ (0.0 ≤ x ≤ 1.5)

et al. 2021

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NAtrium SuperIonic CONductor (NASICON) structured phosphate framework compounds are attracting a great deal of interest as suitable electrode materials for “rocking chair” type batteries. Manganese-based electrode materials are among the most favored due to their superior stability, resource non-criticality, and high electrode potentials. Although a large share of research was devoted to Mn-based oxides for Li- and Na-ion batteries, the understanding of thermodynamics and phase formation in Mn-rich polyanions is still generally lacking. In this study, we investigate a bifunctional Na-ion battery electrode system based on NASICON-structured Na 1+2 x Mn x Ti 2– x (PO 4 ) 3 (0.0 ≤ x ≤ 1.5). In order to analyze the thermodynamic and phase formation properties, we construct a composition–temperature phase diagram using a computational sampling by density functional theory, cluster expansion, and semi-grand canonical Monte Carlo methods. The results indicate finite thermodynamic limits of possible Mn concentrations in this system, which are primarily determined by the phase separation into stoichiometric Na 3 MnTi(PO 4 ) 3 ( x = 1.0) and NaTi 2 (PO 4 ) 3 for x < 1.0 or NaMnPO 4 for x > 1.0. The theoretical predictions are corroborated by experiments obtained using X-ray diffraction and Raman spectroscopy on solid-state and sol–gel prepared samples. The results confirm that this system does not show a solid solution type behavior but phase-separates into thermodynamically more stable sodium ordered monoclinic α-Na 3 MnTi(PO 4 ) 3 (space group C 2) and other phases. In addition to sodium ordering, the anti-bonding character of the Mn–O bond as compared to Ti–O is suggested as another important factor governing the stability of Mn-based NASICONs. We believe that these results will not only clarify some important questions regarding the thermodynamic properties of NASICON frameworks but will also be helpful for a more general understanding of polyanionic systems.

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Modeling the Performance and Cost of Lithium-Ion Batteries for Electric-Drive Vehicles, Third Edition

Cited by 80 publications

References 30 publications

Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

Life‐Cycle Assessment Considerations for Batteries and Battery Materials

Peculiarities of Phase Formation in Mn-Based Na SuperIonic Conductor (NaSICon) Systems: The Case of Na_1+2xMn_xTi_2–x(PO₄)₃ (0.0 ≤ x ≤ 1.5)

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Modeling the Performance and Cost of Lithium-Ion Batteries for Electric-Drive Vehicles, Third Edition

Cited by 80 publications

References 30 publications

Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

Life‐Cycle Assessment Considerations for Batteries and Battery Materials

Peculiarities of Phase Formation in Mn-Based Na SuperIonic Conductor (NaSICon) Systems: The Case of Na1+2xMnxTi2–x(PO4)3 (0.0 ≤ x ≤ 1.5)

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Resources

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Peculiarities of Phase Formation in Mn-Based Na SuperIonic Conductor (NaSICon) Systems: The Case of Na_1+2xMn_xTi_2–x(PO₄)₃ (0.0 ≤ x ≤ 1.5)