Cited by 1,758Battery Modeling and ManagementAdvancements in Battery MaterialsExtraction and Separation Processes

The DOI matches its Crossref record; 139 of the 142 references it cites were found in a registry or an index.

A review on lithium-ion battery ageing mechanisms and estimations for automotive applications

Open access

Barré, Anthony, Deguilhem, Benjamin, Grolleau, Sébastien, Gérard, Mathias, Suard, Frédéric, Riu, Delphine·2013·Journal of Power Sources

DOI 10.1016/j.jpowsour.2013.05.040

Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1016/j.jpowsour.2013.05.040

Cites

139 of 139 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Book Review: Pattern Recognition and Machine Learning
Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 22,066
Book Review: Time Series Analysis: Forecasting and Control
Geurts, M. D., Box, G. E. P., & Jenkins, G. M. (1977) · Journal of Marketing Research · doi:10.2307/3150485 · Cited by 19,410
A Statistical Distribution Function of Wide Applicability
Weibull, W. (1951) · Journal of Applied Mechanics · doi:10.1115/1.4010337 · Cited by 11,646
Pattern Recognition and Machine Learning
(2007) · Kybernetes · doi:10.1108/03684920710743466 · Cited by 8,545
Time Series Analysis: Forecasting and Control.
Anderson, O. D., Box, G. E. P., & Jenkins, G. M. (1978) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.2307/2988198 · Cited by 5,398
Lithium Batteries: Status, Prospects and Future
Scrosati, B., & Garche, J. (2010) · Journal of Power Sources · doi:10.1016/j.jpowsour.2009.11.048 · Cited by 5,153
Modeling of Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell
Doyle, M., Fuller, T. F., & Newman, J. (1993) · Journal of The Electrochemical Society · doi:10.1149/1.2221597 · Cited by 4,328 · cited 1×
“On the other side, it is possible to identify the prominent occurring physico-chemical processes depending on the employed materials, and evaluate with atomistic calculations, their e ect on the battery [78, 79].”
Background
Ageing mechanisms in lithium-ion batteries
Vetter, J., Novák, P., Wagner, M. R., Veit, C., Möller, K.-C., Besenhard, J. O., Winter, M., Wohlfahrt-Mehrens, M., Vogler, C., & Hammouche, A. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2005.01.006 · Cited by 3,987
Thermal runaway caused fire and explosion of lithium ion battery
Wang, Q., Ping, P., Zhao, X., Chu, G., Sun, J., & Chen, C. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.02.038 · Cited by 3,218
Time Series Analysis, Forecasting and Control.
Kendall, M. G., Box, G. E. P., & Jenkins, G. M. (1971) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344246 · Cited by 2,784

Flagged first, then by citations

Show all 142 references

3 of the 142 references couldn’t be matched to a known paper.

Research works printed but not linked: 8

Nagaura, 1990, Progress in Batteries and Solar Cells, 209, 9
Neubauer, 2012, Journal of Power Sources
Kerlau, 2007, Electrochimica Acta, 52, 5422, 10.1016/j.electacta.2007.02.085 · DOI
Hu, 2011, Applied Energy
Ecker, 2012, Journal of Power Sources
Safari, 2011, vol. 158
Tipping, 2001, Journal of Machine Learning Research, 1, 211
Smith, 2009, vol. 25–29

Sorted by citations

Items 101–200 of 1,000

Cost modeling of lithium‐ion battery cells for automotive applications
Patry, G., Romagny, A., Martinet, S., & Frœlich, D. (2014) · Energy Science & Engineering · doi:10.1002/ese3.47 · Cited by 202
Enabling Future Closed‐Loop Recycling of Spent Lithium‐Ion Batteries: Direct Cathode Regeneration
Yang, T., Luo, D., Yu, A., & Chen, Z. (2023) · Advanced Materials · doi:10.1002/adma.202203218 · Cited by 202
Progress and prospect on failure mechanisms of solid-state lithium batteries
Ma, J., Chen, B., Wang, L., & Cui, G. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.04.055 · Cited by 194
Natural biomass-derived carbons for electrochemical energy storage
Tang, W., Zhang, Y., Zhong, Y., Shen, T., Wang, X., Xia, X., & Tu, J. (2016) · Materials Research Bulletin · doi:10.1016/j.materresbull.2016.12.025 · Cited by 192
Porous Electrode Modeling and its Applications to Li‐Ion Batteries
Chen, Z., Danilov, D. L., Eichel, R., & Notten, P. H. L. (2022) · Advanced Energy Materials · doi:10.1002/aenm.202201506 · Cited by 198
A Data-Driven Method for Extracting Aging Features to Accurately Predict the Battery Health
Xiong, R., Sun, Y., Wang, C., Tian, J., Chen, X., Li, H., & Zhang, Q. (2023) · Energy storage materials · doi:10.1016/j.ensm.2023.02.034 · Cited by 190
A Framework for Simplification of PDE-Based Lithium-Ion Battery Models
Zou, C., Manzie, C., & Nesic, D. (2016) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2015.2502899 · Cited by 196
Smart households: Dispatch strategies and economic analysis of distributed energy storage for residential peak shaving
Zheng, M., Meinrenken, C. J., & Lackner, K. S. (2015) · Applied Energy · doi:10.1016/j.apenergy.2015.02.039 · Cited by 189
Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation
Yang, F., Xie, Y., Deng, Y., & Yuan, C. Y. (2018) · Nature Communications · doi:10.1038/s41467-018-04826-0 · Cited by 204
Accelerated cycle life testing and capacity degradation modeling of LiCoO2-graphite cells
Diao, W., Saxena, S., & PECHT, M. G. (2019) · Journal of Power Sources · doi:10.1016/j.jpowsour.2019.226830 · Cited by 188
Review—Use of Impedance Spectroscopy for the Estimation of Li-ion Battery State of Charge, State of Health and Internal Temperature
Carthy, K. M., Gullapalli, H., Ryan, K. M., & Kennedy, T. (2021) · Journal of The Electrochemical Society · doi:10.1149/1945-7111/ac1a85 · Cited by 189
Characterising Lithium-Ion Battery Degradation through the Identification and Tracking of Electrochemical Battery Model Parameters
Uddin, K., Perera, S., Widanage, W. D., Somerville, L., & Marco, J. (2016) · Batteries · doi:10.3390/batteries2020013 · Cited by 193
Delamination behavior of lithium-ion battery anodes: Influence of drying temperature during electrode processing
Baunach, M., Jaiser, S., Schmelzle, S., Nirschl, H., Scharfer, P., & Schabel, W. (2015) · Drying Technology · doi:10.1080/07373937.2015.1060497 · Cited by 186
Safe and Durable High-Temperature Lithium–Sulfur Batteries via Molecular Layer Deposited Coating
Li, X., Lushington, A., Sun, Q., Xiao, W., Liu, J., Wang, B., Ye, Y., Nie, K., Hu, Y., Xiao, Q., et al. (2016) · Nano Letters · doi:10.1021/acs.nanolett.6b00577 · Cited by 185
Temperature, Ageing and Thermal Management of Lithium-Ion Batteries
Spitthoff, L., Shearing, P. R., & Burheim, O. S. (2021) · Energies · doi:10.3390/en14051248 · Cited by 186
Connecting battery technologies for electric vehicles from battery materials to management
Zhao, G., Wang, X., & Negnevitsky, M. (2022) · iScience · doi:10.1016/j.isci.2022.103744 · Cited by 198
Corrosion of aluminium current collector in lithium-ion batteries: A review
Gabryelczyk, A., Ivanov, S., Bund, A., & Lota, G. (2021) · Journal of Energy Storage · doi:10.1016/j.est.2021.103226 · Cited by 150
State-of-health estimation of lithium-ion batteries for electrified vehicles using a reduced-order electrochemical model
Hosseininasab, S., Lin, C., Pischinger, S., Stapelbroek, M., & Vagnoni, G. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.104684 · Cited by 182
A Comprehensive Review on Lithium-Ion Battery Lifetime Prediction and Aging Mechanism Analysis
Madani, S. S., Shabeer, Y., Allard, F., Fowler, M. W., Ziebert, C., Wang, Z., Panchal, S., Chaoui, H., Mekhilef, S., Dou, S. X., et al. (2025) · Batteries · doi:10.3390/batteries11040127 · Cited by 208
Plug-in electric vehicle batteries degradation modeling for smart grid studies: Review, assessment and conceptual framework
Ahmadian, A., Sedghi, M., Elkamel, A., Fowler, M. W., & Golkar, M. A. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.06.067 · Cited by 193
Economic implications of lithium ion battery degradation for Vehicle-to-Grid (V2X) services
Thompson, A. W. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.06.053 · Cited by 179
A Rising 2D Star: Novel MBenes with Excellent Performance in Energy Conversion and Storage
Xu, T., Wang, Y., Xiong, Z., Wang, Y., Zhou, Y., & Li, X. (2022) · Nano-Micro Letters · doi:10.1007/s40820-022-00976-5 · Cited by 186
Electric Vehicle Battery Cycle Aging Evaluation in Real-World Daily Driving and Vehicle-to-Grid Services
Jafari, M., Gauchia, A., Zhao, S., Zhang, K., & Gauchia, L. (2018) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2017.2764320 · Cited by 177
A Mechanical Aging Mechanism in Lithium-Ion Batteries
Waldmann, T., Gorse, S., Samtleben, T., Schneider, G. A., Knoblauch, V., & Wohlfahrt‐Mehrens, M. (2014) · Journal of The Electrochemical Society · doi:10.1149/2.1001410jes · Cited by 178
Optimized charging of lithium-ion battery for electric vehicles: Adaptive multistage constant current–constant voltage charging strategy
Li, Y., Li, K., Xie, Y., Liu, J., Fu, C., & Liu, B. (2019) · Renewable Energy · doi:10.1016/j.renene.2019.08.077 · Cited by 181
Capacity Fade Estimation in Electric Vehicle Li-Ion Batteries Using Artificial Neural Networks
Hussein, A. A.-H. (2014) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2014.2365152 · Cited by 176
Electrothermal dynamics-conscious lithium-ion battery cell-level charging management via state-monitored predictive control
Zou, C., Hu, X., Wei, Z., & Tang, X. (2017) · Energy · doi:10.1016/j.energy.2017.09.048 · Cited by 176
Single-perturbation-cycle online battery impedance spectrum measurement method with closed-loop control of power converter
Qahouq, J. A. A., & Xia, Z. (2017) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2686324 · Cited by 174
A Review of SOH Estimation Methods in Lithium-ion Batteries for Electric Vehicle Applications
Cheng, L., Tang, A., & Wang, W. (2015) · Energy Procedia · doi:10.1016/j.egypro.2015.07.199 · Cited by 174
Aging mechanisms under different state-of-charge ranges and the multi-indicators system of state-of-health for lithium-ion battery with Li(NiMnCo)O2 cathode
Gao, Y., Jiang, J., Zhang, C., Zhang, W., & Jiang, Y. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.07.018 · Cited by 174
Thermal Behavior of Lithium- and Sodium-Ion Batteries: A Review on Heat Generation, Battery Degradation, Thermal Runway – Perspective and Future Directions
Velumani, D., & Bansal, A. (2022) · Energy & Fuels · doi:10.1021/acs.energyfuels.2c02889 · Cited by 179
Next-generation battery management systems: dynamic reconfiguration
Han, W., Wik, T., Kersten, A., Dong, G., & Zou, C. (2020) · IEEE Industrial Electronics Magazine · doi:10.1109/mie.2020.3002486 · Cited by 173
An Integrated Probabilistic Approach to Lithium-Ion Battery Remaining Useful Life Estimation
Liu, D., Xie, W. H., Liao, H., & Peng, Y. (2014) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2014.2348613 · Cited by 171
State-of-Health Estimation of Lithium-ion Batteries by Fusing an Open-Circuit-Voltage Model and Incremental Capacity Analysis
Bian, X., Wei, Z., Li, W., Pou, J., Sauer, D. U., & Liu, L. (2021) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2021.3104723 · Cited by 171
Energy Management Strategies for Fuel Cell Vehicles: A Comprehensive Review of the Latest Progress in Modeling, Strategies, and Future Prospects
Khalatbarisoltani, A., Zhou, H., Tang, X., Kandidayeni, M., Boulon, L., & Hu, X. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3309052 · Cited by 171
Recent advances in metal organic framework and cellulose nanomaterial composites
Lu, Y., Liu, C., Mei, C., Sun, J., Lee, J., Wu, Q., Hubbe, M. A., & Li, M. (2022) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2022.214496 · Cited by 172
A Neural Network Based State-of-Health Estimation of Lithium-ion Battery in Electric Vehicles
Yang, D., Wang, Y., Pan, R. N., Chen, R., & Chen, Z. (2017) · Energy Procedia · doi:10.1016/j.egypro.2017.03.583 · Cited by 169
Hexagonal Ti 2 B 2 monolayer: a promising anode material offering high rate capability for Li-ion and Na-ion batteries
Bo, T., Liu, P., Xu, J., Zhang, J., Chen, Y., Eriksson, O., Wang, F., & Wang, B. (2018) · Physical Chemistry Chemical Physics · doi:10.1039/c8cp03362e · Cited by 169
Enhanced Adsorptions to Polysulfides on Graphene-Supported BN Nanosheets with Excellent Li–S Battery Performance in a Wide Temperature Range
Deng, D., Xue, F., Bai, C.-D., Lei, J. H., Yuan, R., Zheng, M. S., & Dong, Q. (2018) · ACS Nano · doi:10.1021/acsnano.8b05534 · Cited by 169
Lithium-Ion Battery Operation, Degradation, and Aging Mechanism in Electric Vehicles: An Overview
Guo, J., Li, Y., Pedersen, K., & Stroe, D. (2021) · Energies · doi:10.3390/en14175220 · Cited by 172
Online available capacity prediction and state of charge estimation based on advanced data-driven algorithms for lithium iron phosphate battery
Deng, Z., Yang, L., Cai, Y., Deng, H., & Sun, L. (2016) · Energy · doi:10.1016/j.energy.2016.06.130 · Cited by 168
Carbon nanofiber-based nanostructures for lithium-ion and sodium-ion batteries
Li, W., Li, M., Adair, K. R., Sun, X. A., & Yu, Y. M. (2017) · Journal of Materials Chemistry A · doi:10.1039/c7ta02153d · Cited by 173
Charge scheduling for electric freight vehicles
Pelletier, S., Jabali, O., & Gilbert Laporte, A. (2018) · Transportation Research Part B Methodological · doi:10.1016/j.trb.2018.07.010 · Cited by 165
Online Health Diagnosis of Lithium-Ion Batteries Based on Nonlinear Autoregressive Neural Network
Khaleghi, S., Karimi, D., Beheshti, S. H., Hosen, M. S., Behi, H., Berecibar, M., & Van Mierlo, J. (2021) · Applied Energy · doi:10.1016/j.apenergy.2020.116159 · Cited by 161
An evaluation study of different modelling techniques for calendar ageing prediction of lithium-ion batteries
Liu, K., Ashwin, T. R., Hu, X., Lucu, M., & Widanage, W. D. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.110017 · Cited by 172
Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives
Thelen, A., Huan, X., Paulson, N. H., Onori, S., Hu, Z., & Hu, C. K. (2024) · npj Materials Sustainability · doi:10.1038/s44296-024-00011-1 · Cited by 170
Impact of Tab Location on Large Format Lithium-Ion Pouch Cell Based on Fully Coupled Tree-Dimensional Electrochemical-Thermal Modeling
Samba, A., Omar, N., Gualous, H., Capron, O., den Bossche, P. V., & Mierlo, J. V. (2014) · Electrochimica Acta · doi:10.1016/j.electacta.2014.08.115 · Cited by 161
State of Health Estimation for Lithium-Ion Batteries Based on Healthy Features and Long Short-Term Memory
Wu, Y., Xue, Q., Shen, J., Lei, Z., Chen, Z., & Liu, Y. (2020) · IEEE Access · doi:10.1109/access.2020.2972344 · Cited by 160
Energy Storage Structural Composites with Integrated Lithium‐Ion Batteries: A Review
Galos, J., Pattarakunnan, K., Best, A. S., Kyratzis, I. L., Wang, C., & Mouritz, A. P. (2021) · Advanced Materials Technologies · doi:10.1002/admt.202001059 · Cited by 158
Understanding aging mechanisms in lithium-ion battery packs: From cell capacity loss to pack capacity evolution
Zheng, Y., Ouyang, M., Lu, L., & Li, J. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.12.105 · Cited by 157
Risk-Averse Coordinated Operation of a Multi-Energy Microgrid Considering Voltage/Var Control and Thermal Flow: An Adaptive Stochastic Approach
Li, Z., Wu, L., & Xu, Y. H. (2021) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2021.3080312 · Cited by 157
The capacity estimation and cycle life prediction of lithium-ion batteries using a new broad extreme learning machine approach
Ma, Y., Wu, L., Guan, Y., & Peng, Z. (2020) · Journal of Power Sources · doi:10.1016/j.jpowsour.2020.228581 · Cited by 154
Novel application of differential thermal voltammetry as an in-depth state-of-health diagnosis method for lithium-ion batteries
Merla, Y., Wu, B., Yufit, V., Brandon, N. P., Martinez-Botas, R. F., & Offer, G. J. (2016) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.12.122 · Cited by 156
Primary and secondary use of electric mobility batteries from a life cycle perspective
Faria, R., Marques, P., Garcia, R., Moura, P., Freire, F. M. C. S., Delgado, J., & de Almeida, A. T. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.03.092 · Cited by 173
An online SOC and capacity estimation method for aged lithium-ion battery pack considering cell inconsistency
Yang, C., Wang, X., Fang, Q., Dai, H., Cao, Y., & Wei, X. (2020) · Journal of Energy Storage · doi:10.1016/j.est.2020.101250 · Cited by 154
A coupled electrochemical-thermal-mechanical degradation modelling approach for lifetime assessment of lithium-ion batteries
Yang, S.-C., Hua, Y., Qiao, D., Lian, Y.-B., Pan, Y.-W., & He, Y.-L. (2019) · Electrochimica Acta · doi:10.1016/j.electacta.2019.134928 · Cited by 152
Research gaps in environmental life cycle assessments of lithium ion batteries for grid-scale stationary energy storage systems: End-of-life options and other issues
Pellow, M. A., Ambrose, H., Mulvaney, D., Betita, R., & Shaw, S. (2020) · Sustainable Materials and Technologies · doi:10.1016/j.susmat.2019.e00120 · Cited by 152
A review on state of health estimation for lithium ion batteries in photovoltaic systems
Tian, J., Xiong, R., & Shen, W. (2019) · eTransportation · doi:10.1016/j.etran.2019.100028 · Cited by 153
A method to estimate battery SOH indicators based on vehicle operating data only
Vichard, L., Ravey, A., Venet, P., Harel, F., Pélissier, S., & Hissel, D. (2021) · Energy · doi:10.1016/j.energy.2021.120235 · Cited by 151
A novel bi-functional double-layer rGO–PVDF/PVDF composite nanofiber membrane separator with enhanced thermal stability and effective polysulfide inhibition for high-performance lithium–sulfur batteries
Zhu, P., Zhu, J., Zang, J., Chen, C., Lu, Y., Jiang, M., Yan, C., Dirican, M., Selvan, R. K., & Zhang, X. (2017) · Journal of Materials Chemistry A · doi:10.1039/c7ta03301j · Cited by 151
Lithium Ion Battery Models and Parameter Identification Techniques
Barcellona, S., & Piegari, L. (2017) · Energies · doi:10.3390/en10122007 · Cited by 149
High precision strain monitoring for lithium ion batteries based on fiber Bragg grating sensors
Peng, J., Zhou, X., Jia, S., Jin, Y., Xu, S., & Chen, J. (2019) · Journal of Power Sources · doi:10.1016/j.jpowsour.2019.226692 · Cited by 150
On the influence of second use, future battery technologies, and battery lifetime on the maximum recycled content of future electric vehicle batteries in Europe
Abdelbaky, M., Peeters, J. R., & Dewulf, W. (2021) · Waste Management · doi:10.1016/j.wasman.2021.02.032 · Cited by 147
Aging Mechanisms of Electrode Materials in Lithium‐Ion Batteries for Electric Vehicles
Lin, C. W., Tang, A., Mu, H., Wang, W., & Wang, C. (2015) · Journal of Chemistry · doi:10.1155/2015/104673 · Cited by 158
U.S. end-of-life electric vehicle batteries: Dynamic inventory modeling and spatial analysis for regional solutions
Ai, N., Zheng, J., & Chen, W. (2019) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2019.01.021 · Cited by 149
Integrating Physics-Based Modeling and Machine Learning for Degradation Diagnostics of Lithium-Ion Batteries
Thelen, A., Lui, Y. H., Shen, S., Laflamme, S., Hu, S., Ye, H., & Hu, C. (2022) · Energy storage materials · doi:10.1016/j.ensm.2022.05.047 · Cited by 148
Reused second life batteries for aggregated demand response services
Casals, L. C., Barbero, M., & Corchero, C. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.12.005 · Cited by 155
The effect of fluoroethylene carbonate additive content on the formation of the solid-electrolyte interphase and capacity fade of Li-ion full-cell employing nano Si–graphene composite anodes
Bordes, A., Eom, K., & Fuller, T. F. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.12.144 · Cited by 146
Battery energy storage system for primary control reserve and energy arbitrage
Brivio, C., Mandelli, S., & Merlo, M. (2016) · Sustainable Energy Grids and Networks · doi:10.1016/j.segan.2016.03.004 · Cited by 146
Effect of current on cycle aging of lithium ion batteries
Barcellona, S., & Piegari, L. (2020) · Journal of Energy Storage · doi:10.1016/j.est.2020.101310 · Cited by 125
A survey on lithium-ion battery internal and external degradation modeling and state of health estimation
Vennam, G., Sahoo, A., & Ahmed, S. M. F. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.104720 · Cited by 146
Current trends, challenges, and prospects in material advances for improving the overall safety of lithium-ion battery pack
Rana, S., Kumar, R., & Bharj, R. S. (2023) · Chemical Engineering Journal · doi:10.1016/j.cej.2023.142336 · Cited by 143
Toward a Mechanistic Model of Solid–Electrolyte Interphase Formation and Evolution in Lithium-Ion Batteries
Spotte-Smith, E., Kam, R. L., Barter, D., Xie, X., Hou, T., Dwaraknath, S., Blau, S. M., & Persson, K. (2022) · ACS Energy Letters · doi:10.1021/acsenergylett.2c00517 · Cited by 120
In situ TEM visualization of LiF nanosheet formation on the cathode-electrolyte interphase (CEI) in liquid-electrolyte lithium-ion batteries
Zhang, Q.-Y., Ma, J.-L., Mei, L., Liu, J., Li, Z.-Y., Li, J., & Zeng, Z. (2022) · Matter · doi:10.1016/j.matt.2022.01.015 · Cited by 121
A study on thermal management system of lithium-ion batteries for electrical vehicles: A critical review
Kumar, R., & Goel, V. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.108025 · Cited by 141
Energy and climate effects of second-life use of electric vehicle batteries in California through 2050
Sathre, R., Scown, C. D., Kavvada, O., & Hendrickson, T. P. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.04.097 · Cited by 146
A pseudo 3D electrochemical-thermal modeling and analysis of a lithium-ion battery for electric vehicle thermal management applications
Bahiraei, F., Ghalkhani, M., Fartaj, A., & Nazri, G. (2017) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2017.07.060 · Cited by 136
Advances in battery state estimation of battery management system in electric vehicles
Jiang, M., Li, D., Li, Z., Chen, Z., Yan, Q., Fu, L., Yu, C., Jiang, B., Wei, X., Yan, W., et al. (2024) · Journal of Power Sources · doi:10.1016/j.jpowsour.2024.234781 · Cited by 142
Review of state-of-the-art battery state estimation technologies for battery management systems of stationary energy storage systems
Park, S., Ahn, J., Kang, T., Park, S., Kim, Y., Cho, I., & Kim, J. (2020) · Journal of Power Electronics · doi:10.1007/s43236-020-00122-7 · Cited by 137
A novel method on estimating the degradation and state of charge of lithium-ion batteries used for electrical vehicles
Yang, R., Xiong, R., He, H., Mu, H., & Wang, C. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.05.183 · Cited by 132
A comprehensive review of the lithium-ion battery state of health prognosis methods combining aging mechanism analysis
Xiao, Y., Wen, J., Yao, L. Y., Zheng, J., Fang, Z., & Shen, Y. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.107347 · Cited by 132
Understanding the crack formation of graphite particles in cycled commercial lithium-ion batteries by focused ion beam - scanning electron microscopy
Lin, N., Jia, Z., Wang, Z., Zhao, H., Ai, G., Song, X., Bai, Y., Battaglia, V., Sun, C., Qiao, J., et al. (2017) · Journal of Power Sources · doi:10.1016/j.jpowsour.2017.08.045 · Cited by 139
Mechanical methods for state determination of Lithium-Ion secondary batteries: A review
Popp, H., Koller, M., Jahn, M., & Bergmann, A. (2020) · Journal of Energy Storage · doi:10.1016/j.est.2020.101859 · Cited by 130
Comparative Study of Surface Temperature Behavior of Commercial Li-Ion Pouch Cells of Different Chemistries and Capacities by Infrared Thermography
Goutam, S., Timmermans, J.-M., Omar, N., den Bossche, P. V., & Mierlo, J. V. (2015) · Energies · doi:10.3390/en8088175 · Cited by 135
Electrochemical-thermal modeling of lithium plating/stripping of Li(Ni0.6Mn0.2Co0.2)O2/Carbon lithium-ion batteries at subzero ambient temperatures
Zhao, X., Yin, Y., Hu, Y., & Choe, S.-Y. (2019) · Journal of Power Sources · doi:10.1016/j.jpowsour.2019.02.001 · Cited by 129
Correlation between capacity and impedance of lithium-ion cells during calendar and cycle life
Schuster, S. F., Brand, M. J., Campestrini, C., Gleissenberger, M., & Jossen, A. (2016) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.11.096 · Cited by 128
A comparative study and review of different Kalman filters by applying an enhanced validation method
Campestrini, C., Heil, T., Kosch, S., & Jossen, A. (2016) · Journal of Energy Storage · doi:10.1016/j.est.2016.10.004 · Cited by 128
A review of atomic layer deposition providing high performance lithium sulfur batteries
Yan, B., Li, X., Bai, Z., Song, X., Xiong, D., Zhao, M., Li, D., & Lu, S. (2016) · Journal of Power Sources · doi:10.1016/j.jpowsour.2016.10.097 · Cited by 128
Hybrid fuel cell system degradation modeling methods: A comprehensive review
Vichard, L., Steiner, N. Y., Noureddine Zerhouni, A., & Hissel, D. (2021) · Journal of Power Sources · doi:10.1016/j.jpowsour.2021.230071 · Cited by 130
Detection of Lithium‐Ion Cells’ Degradation through Deconvolution of Electrochemical Impedance Spectroscopy with Distribution of Relaxation Time
Iurilli, P., Brivio, C., & Wood, V. C. (2022) · Energy Technology · doi:10.1002/ente.202200547 · Cited by 128
Computationally efficient thermal network model and its application in optimization of battery thermal management system with phase change materials and long-term performance assessment
Ling, Z., Lin, W., Zhang, Z., & Fang, X. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.114120 · Cited by 125
A hybrid model based on support vector regression and differential evolution for remaining useful lifetime prediction of lithium-ion batteries
Wang, F., & Mamo, T. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.08.073 · Cited by 127
Developments in X-ray tomography characterization for electrochemical devices
Heenan, T. M. M., Tan, C., Hack, J., Brett, D. J. L., & Shearing, P. R. (2019) · Materials Today · doi:10.1016/j.mattod.2019.05.019 · Cited by 126
Design criteria for the optimal sizing of a hybrid energy storage system in PV household-prosumers to maximize self-consumption and self-sufficiency
Hernández, J. C., Sánchez-Sutil, F., & Muñoz-Rodríguez, F. J. (2019) · Energy · doi:10.1016/j.energy.2019.07.157 · Cited by 126
Prognostics of battery cycle life in the early-cycle stage based on hybrid model
Zhang, Y., Peng, Z., Guan, Y., & Wu, L. (2021) · Energy · doi:10.1016/j.energy.2021.119901 · Cited by 123
Multi-stress factor model for cycle lifetime prediction of lithium ion batteries with shallow-depth discharge
Cui, Y., Du, C., Yin, G., Gao, Y., Zhang, L., Guan, T., Yang, L., & Wang, F. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.01.003 · Cited by 124
Accelerated aging of lithium-ion batteries: bridging battery aging analysis and operational lifetime prediction.
Li, R., Bao, L., Chen, L., Zha, C., Dong, J., Qi, N., Tang, R., Lu, Y., Wang, M., Huang, R., et al. (2023) · Science Bulletin · doi:10.1016/j.scib.2023.10.029 · Cited by 113
Effects of battery chemistry and performance on the life cycle greenhouse gas intensity of electric mobility
Ambrose, H., & Kendall, A. M. (2016) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2016.05.009 · Cited by 131
Lifetime Estimation of the Nanophosphate $\hbox{LiFePO}_{4}\hbox{/C}$ Battery Chemistry Used in Fully Electric Vehicles
Swierczynski, M. J., Stroe, D., Stan, A.-I., Teodorescu, R., & Kær, S. K. (2015) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2015.2405500 · Cited by 122
State of Health Estimation for Lithium-ion Batteries Based on Fusion of Autoregressive Moving Average Model and Elman Neural Network
Chen, Z., Xue, Q., Xiao, R., Liu, Y., & Shen, J. (2019) · IEEE Access · doi:10.1109/access.2019.2930680 · Cited by 120

Authors: Barré, A., Deguilhem, B., Grolleau, S., Gérard, M., Suard, F., & Riu, D.
Affiliations: Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
Laboratoire de Génie Électrique de Grenoble (FR)
Corresponding author: Barré, Anthony
ORCID: Barré, Anthony
Gérard, Mathias
Venue: Journal of Power Sources
Publisher: Elsevier BV
Published: 2013-11
Volume: 241
Pages: 680-689
ISSN: 0378-7753 (ISSN-L)
DOI: 10.1016/j.jpowsour.2013.05.040
OpenAlex: W2017136542
Cited by: 1,758
References: 142
Citations by year: 2026: 159 · 2025: 172 · 2024: 152 · 2023: 154 · 2022: 189 · 2021: 183 · 2020: 163 · 2019: 148 · 2018: 113 · 2017: 123 · 2016: 71 · 2015: 73 · 2014: 55 · 2013: 3
FWCI: 104.87
Type: journal article
Language: en
Open access: green
cea.hal.science
Licence: other-oa
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Journal of Power Sources (publishedVersion)
HAL (submittedVersion, other-oa)
Topics: Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
Physical Sciences › Materials Science › Metals and Alloys › Extraction and Separation Processes
Keywords: lithium-ion batteries, state of health estimation, remaining useful life prediction, automotive batteries, battery degradation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

A review on lithium-ion battery ageing mechanisms and estimations for automotive applications

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks