The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries
Open accessAbstract
For reliable lifetime predictions of lithium-ion batteries, models for cell degradation are required. A comprehensive semi-empirical model based on a reduced set of internal cell parameters and physically justified degradation functions for the capacity loss is developed and presented for a commercial lithium iron phosphate/graphite cell. One calendar and several cycle aging effects are modeled separately. Emphasis is placed on the varying degradation at different temperatures. Degradation mechanisms for cycle aging at high and low temperatures as well as the increased cycling degradation at high state of charge are calculated separately. For parameterization, a lifetime test study is conducted including storage and cycle tests. Additionally, the model is validated through a dynamic current profile based on real-world application in a stationary energy storage system revealing the accuracy. Tests for validation are continued for up to 114 days after the longest parametrization tests. The model error for the cell capacity loss in the application-based tests is at the end of testing below 1% of the original cell capacity and the maximum relative model error is below 21%.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Most of the existing studies model the battery cyclic and calendar aging independently, and combine the two to make predictions under a dynamic load profile [6,94,95].”
From Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019) · cites this paper as [95]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The current rate and DOD dependence on cyclic ageing can be modelled with exponential [95,102] or polynomial [102] functions.”
From Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019) · cites this paper as [95]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“In contrast, the SOC dependence on calendar ageing lifetime is typically fitted by linear functions [100], exponential functions [99] or by the Tafel equation [95].”
From Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019) · cites this paper as [95]
The cited source says what the claim attributes to it.
In the citing paper
“The capacity loss due to calendar ageing is usually proportional to a power law relation with time 𝑡, weighted by the influences of temperature 𝑇 and storage SOC, what can be represented by some stress factor 𝑘 [95]:”
From Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019) · cites this paper as [95]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Cycle-life model for graphite-LiFePO4 cells
Wang, J. J., Liu, P., Hicks-Garner, J., Sherman, E., Soukiazian, S., Verbrugge, M. W., Tataria, H., Musser, J., & Finamore, P. (2010) · Journal of Power Sources · doi:10.1016/j.jpowsour.2010.11.134 · Cited by 1,785
A review on lithium-ion battery ageing mechanisms and estimations for automotive applications
Barré, A., Deguilhem, B., Grolleau, S., Gérard, M., Suard, F., & Riu, D. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.05.040 · Cited by 1,758
Temperature dependent ageing mechanisms in Lithium-ion batteries – A Post-Mortem study
Waldmann, T., Wilka, M. D., Kasper, M., Fleischhammer, M., & Wohlfahrt‐Mehrens, M. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.03.112 · Cited by 1,269
Main aging mechanisms in Li ion batteries
Broussely, M., Biensan, P., Bonhomme, F., Blanchard, P., Herreyre, S., Nechev, K., & Staniewicz, R. J. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2005.03.172 · Cited by 1,162
Calendar and cycle life study of Li(NiMnCo)O2-based 18650 lithium-ion batteries
Ecker, M., Nieto, N., Käbitz, S., Schmalstieg, J., Blanke, H., Warnecke, A., & Sauer, D. U. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.09.143 · Cited by 809
A holistic aging model for Li(NiMnCo)O2 based 18650 lithium-ion batteries
Schmalstieg, J., Käbitz, S., Ecker, M., & Sauer, D. U. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.02.012 · Cited by 755
Lithium plating in a commercial lithium-ion battery – A low-temperature aging study
Petzl, M., Kasper, M., & Danzer, M. A. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.11.065 · Cited by 731
Calendar Aging of Lithium-Ion Batteries: I. Impact of the Graphite Anode on Capacity Fade
Keil, P., Schuster, S. F., Wilhelm, J., Travi, J., Hauser, A., Karl, R. C., & Jossen, A. (2016) · Journal of The Electrochemical Society · doi:10.1149/2.0411609jes · Cited by 669
Self-citationEcker, M., Gerschler, J. B., Vogel, J., Käbitz, S., Hust, F., Dechent, P., & Sauer, D. U. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.05.012 · Cited by 647
Flagged first, then by citations
Research works printed but not linked: 1
- Yasuda Masayuki , in OREBA 1.0 - International Conference on Olivines for Rechargeable Batteries, (2014).
Cited by
Sorted by citations
Items 101–200 of 238
He, Y., & Zhang, Y. (2025) · Energy Conversion and Management · doi:10.1016/j.enconman.2025.120156 · Cited by 24
Schimpe, M., Truong, C. N., Naumann, M., Jossen, A., Hesse, H. C., Reniers, J. M., & Howey, D. A. (2018) · IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) · doi:10.1109/eeeic.2018.8493717 · Cited by 24
Self-citationAssessment of residential battery storage systems and operation strategies considering battery aging
Förstl, M., Azuatalam, D., Chapman, A. C., Verbič, G., Jossen, A., & Hesse, H. C. (2019) · International Journal of Energy Research · doi:10.1002/er.4770 · Cited by 25
Self-citationAdhikari, P. R., Pach, G. F., Quinn, J., Wang, C., Singh, A., Prakash, N., Verma, A., Colclasure, A. M., Kliegle, G. A., Veith, G. M., et al. (2025) · Advanced Energy Materials · doi:10.1002/aenm.202501074 · Cited by 23
Wang, J., & Xiang, Y. (2021) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2021.3128018 · Cited by 23
Parlikar, A., Tepe, B., Möller, M., Hesse, H. C., & Jossen, A. (2024) · Energy Conversion and Management · doi:10.1016/j.enconman.2024.118208 · Cited by 23
Self-citationSemmelmann, L., Konermann, M., Dietze, D., & Staudt, P. (2024) · Energy Policy · doi:10.1016/j.enpol.2024.114343 · Cited by 23
Routh, B., Guha, A., Mukhopadhyay, S., & Patra, A. (2024) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2024.3521316 · Cited by 22
Cloud-based model-predictive-control of a battery storage system at a commercial site
Goldsworthy, M., Moore, T., Peristy, M., & Grimeland, M. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.120038 · Cited by 22
State-of-health estimation using a neural network trained on vehicle data
Hamar, J. C., Erhard, S. V., Canesso, A., Kohlschmidt, J., Olivain, N., & Jossen, A. (2021) · Journal of Power Sources · doi:10.1016/j.jpowsour.2021.230493 · Cited by 21
Self-citationRodríguez-Iturriaga, P., Anseán, D., López-Villanueva, J. A., Gonzalez, M., & Rodríguez-Bolívar, S. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.106260 · Cited by 21
Ewert, R., Grahle, A., Martins-Turner, K., Syré, A. M., Nagel, K., & Göhlich, D. (2021) · World Electric Vehicle Journal · doi:10.3390/wevj12030122 · Cited by 19
Aryai, V., & Goldsworthy, M. (2022) · Energy Informatics · doi:10.1186/s42162-022-00216-5 · Cited by 19
Park, S.-W., Yu, J.-U., Lee, J.-W., & Son, S.-Y. (2024) · Applied Energy · doi:10.1016/j.apenergy.2024.123879 · Cited by 23
Khange, S., & Sharma, A. K. (2024) · International Journal of Thermal Sciences · doi:10.1016/j.ijthermalsci.2024.109564 · Cited by 19
Impact of the User Charging Practice on the Battery Aging in an Electric Vehicle
Ndiaye, A., German, R., Bouscayrol, A., Gaetani-Liseo, M., Venet, P., & Castex, É. (2024) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2024.3356116 · Cited by 18
Xiao, B., Walker, P. D., Zhou, S., Yang, W., & Zhang, N. (2021) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2021.3084196 · Cited by 18
Analysis of vehicle-integrated photovoltaics and vehicle-to-grid on electric vehicle battery life
Kouzelis, A., Linders, K., Bandyopadhyay, S., & Mouli, G. R. C. (2025) · Journal of Power Sources · doi:10.1016/j.jpowsour.2024.236117 · Cited by 17
Dorronsoro, X., de Castro, R. P., Barreras, J. V., Garayalde, E., & Iraola, U. (2025) · Applied Energy · doi:10.1016/j.apenergy.2025.126494 · Cited by 17
Sowe, J., Barreras, J. V., Schimpe, M., Wu, B., Candelise, C., Nelson, J., & Few, S. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.104524 · Cited by 17
Self-citationFeng, X., Zhang, Y., Xiong, R., & Tang, A. (2023) · iEnergy · doi:10.23919/ien.2023.0034 · Cited by 19
Li, J.-F., Lin, C.-H., & Chen, K.-C. (2018) · Journal of The Electrochemical Society · doi:10.1149/2.0211816jes · Cited by 17
Aging matrix visualizes complexity of battery aging across hundreds of cycling protocols
van Vlijmen, B., Lam, V., Asinger, P. A., Cui, X., Schaeffer, J., Geslin, A., Ganapathi, D., Sun, S., Herring, P. K., Gopal, C. B., et al. (2025) · Energy & Environmental Science · doi:10.1039/d4ee05609d · Cited by 17
Valuing distributed energy resources for non-wires alternatives
Laws, N. D., Webber, M. E., & Chen, D. (2024) · Electric Power Systems Research · doi:10.1016/j.epsr.2024.110521 · Cited by 15
Yagci, M. C., Richter, O., Behmann, R., & Bessler, W. G. (2025) · Journal of Energy Storage · doi:10.1016/j.est.2025.116774 · Cited by 15
Saleem, A., Shaw, L. L., Chen, Z., & Lai, W. (2025) · Advanced Energy Materials · doi:10.1002/aenm.202405300 · Cited by 15
Technological improvements in EV batteries offset climate-induced durability challenges
Wu, H.-C., Chen, J., Vaishnav, P., Sun, M., & Craig, M. (2026) · Nature Climate Change · doi:10.1038/s41558-026-02579-z · Cited by 15
A Review on Aging-Aware System Simulation for Plug-In Hybrids
Frambach, T., Liedtke, R., Dechent, P., Sauer, D. U., & Figgemeier, E. (2021) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2021.3104105 · Cited by 15
Suitability of late-life lithium-ion cells for battery energy storage systems
Collath, N., Winner, H., Frank, A., Durdel, A., & Jossen, A. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2024.111508 · Cited by 16
Self-citationA fractional-order model for calendar aging with dynamic storage conditions
López-Villanueva, J. A., Rodríguez-Iturriaga, P., & Rodríguez-Bolívar, S. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.104537 · Cited by 15
Degradation-Aware Derating of Lithium-Ion Battery Energy Storage Systems in the UK Power Market
Rajah, I., Sowe, J., Schimpe, M., & Barreras, J. V. (2024) · Electronics · doi:10.3390/electronics13193817 · Cited by 14
Self-citationGwayi, I., Ayeng’o, S. P., & Kimambo, C. Z. M. (2025) · Engineering Reports · doi:10.1002/eng2.70169 · Cited by 15
Electrothermal Characterization and Modeling of Lithium-Ion Pouch Cells in Thermal Runaway
Yan, H., Gajjar, P. D., & Ezekoye, O. (2022) · Fire technology · doi:10.1007/s10694-022-01349-5 · Cited by 12
Chen, L., Ding, S., Wang, L., Zhu, F., Zhu, X., Zhang, S., Dai, H., He, X., Cao, G., Qiu, J., et al. (2024) · Applied Energy · doi:10.1016/j.apenergy.2024.124175 · Cited by 14
Jia, R., Gao, K., Cui, S., Chen, J., & Andrić, J. M. (2024) · Transportation Research Part E Logistics and Transportation Review · doi:10.1016/j.tre.2024.103885 · Cited by 14
Battery Early Prognostics Based on Pseudo Meta-Learning
Zhang, S., Liu, Z., & Su, H. (2024) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2024.3412128 · Cited by 13
Jang, S., & Yang, H. (2021) · Electronics · doi:10.3390/electronics10010086 · Cited by 13
The impact of V2X on battery degradation: A quantitative review
Linders, K., Jenu, S., Hentunen, A., & Mouli, G. R. C. (2025) · Journal of Power Sources · doi:10.1016/j.jpowsour.2025.238482 · Cited by 13
Planden, B., Lukow, K., Henshall, P., Collier, G., & Morrey, D. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.105637 · Cited by 12
Performance metrics for the comparison of lithium ion cell aging experiments
Heyer, G., D’Arpino, M., & Rizzoni, G. (2023) · Energy Reviews · doi:10.1016/j.enrev.2023.100025 · Cited by 12
Li, L., Chen, X., Hu, R., Wang, T., Ji, H., Yuan, Q., Ji, Y., Jiang, Z., Liu, W., & Zheng, W. (2020) · Journal of Electrochemical Energy Conversion and Storage · doi:10.1115/1.4048703 · Cited by 13
Jung, J., Bassole, Y. C. F., & Sung, Y. (2025) · Complex & Intelligent Systems · doi:10.1007/s40747-025-02194-z · Cited by 11
Raj, P., Richter, E., Herb, F., Kempf, J., Michel, F., & Birke, K. P. (2024) · e-Prime - Advances in Electrical Engineering Electronics and Energy · doi:10.1016/j.prime.2024.100712 · Cited by 10
López-Villanueva, J. A., Rodríguez-Iturriaga, P., Parrilla, L., & Rodríguez-Bolívar, S. (2023) · Energies · doi:10.3390/en16052484 · Cited by 10
Chen, P., Mao, Z., Lu, C., Li, B., Ding, W., & Li, J. (2024) · Journal of Power Sources · doi:10.1016/j.jpowsour.2023.234046 · Cited by 9
Environmental Analysis of Integrating Photovoltaics and Energy Storage in Building
Zhao, G., Searle, J. R., Clarke, J., Roberts, M., Allen, S. R., & Baker, J. (2022) · Procedia CIRP · doi:10.1016/j.procir.2022.02.102 · Cited by 9
Kröger, T., Maisel, S., Jank, G., Gamra, K. A., Brehler, T., & Lienkamp, M. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2024.114702 · Cited by 8
Schreiber, M., Köning, L. L., Balke, G., Gamra, K. A., Kayl, J., Dietermann, B., Urban, R., Grosu, C., & Lienkamp, M. (2025) · eTransportation · doi:10.1016/j.etran.2025.100518 · Cited by 8
Terkeş, M., Demirci, A., & Gökalp, E. (2024) · Energy Storage · doi:10.1002/est2.661 · Cited by 7
Brehm, J., Altmann, M., Mehlsam, L., Kotter, P., & Jossen, A. (2025) · Journal of The Electrochemical Society · doi:10.1149/1945-7111/ade345 · Cited by 7
Self-citationOrbit maintenance strategy integrated with power management for ultra low Earth orbit satellites
Ding, J., Bai, X. L., Wenchi, Z., & Xu, M. (2026) · Advances in Space Research · doi:10.1016/j.asr.2026.03.031 · Cited by 7
Ketjoy, N., Chamsa-ard, W., Suriwong, T., Mensin, Y., Prasatsap, U., Kumar, S., Sahoo, S. K., & Chantarapongphan, C. (2025) · Journal of Energy Storage · doi:10.1016/j.est.2025.115851 · Cited by 7
Aitio, A., & Howey, D. A. (2020) · ASME Dynamic Systems and Control Conference (DSCC) · doi:10.1115/dscc2020-3180 · Cited by 6
Jiang, X., Zhao, Z., Zhou, W., Meng, L., Hu, D., Shangguan, Z., Liu, M., Zuo, J., Zhang, J., & Jin, L. J. (2026) · Applied Energy · doi:10.1016/j.apenergy.2025.127303 · Cited by 5
Choi, M., Du, X., Choe, S.-Y., & Garrick, T. R. (2026) · Journal of Power Sources · doi:10.1016/j.jpowsour.2026.240007 · Cited by 6
Gonzalez-Saenz, J., & Becerra, V. M. (2024) · Energies · doi:10.3390/en17061470 · Cited by 5
Cui, X., Stroebl, F., Uppaluri, M., Lam, V., Chueh, W. C., & Onori, S. (2025) · Journal of The Electrochemical Society · doi:10.1149/1945-7111/adde16 · Cited by 5
Guarino, A., Zamboni, W., & Monmasson, É. (2020) · IEEE International Symposium on Industrial Electronics (ISIE) · doi:10.1109/isie45063.2020.9152535 · Cited by 5
Ahn, H., Wang, Z., Shen, H., Zhou, X., & Wang, J. (2022) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2022.11.160 · Cited by 5
Mendez-Navarro, A., Álvarez-Salgado, F. Á., & Villalobos-Guerra, A. U. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.121014 · Cited by 4
Measuring the degradation of a power grid-connected BESS using a new data-driven indicator
Alvarez-Monteserin, I., & Sanz-Bobi, M. A. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2024.110958 · Cited by 4
Ye, W., Chen, X., Xu, H., Xie, Y., Gong, F., He, L., Han, X., Wang, H., & Ouyang, M. (2025) · Journal of Energy Chemistry · doi:10.1016/j.jechem.2025.09.006 · Cited by 4
Galatro, D., & Amon, C. H. (2025) · Journal of Energy Storage · doi:10.1016/j.est.2025.116657 · Cited by 4
Azzam, M., Sauer, D. U., Endisch, C., & Lewerenz, M. (2025) · Batteries & Supercaps · doi:10.1002/batt.202500349 · Cited by 4
Hybrid Renewable Power System for Radio Networks in Mission Critical Applications
Rozzi, M., Mascherpa, M., Grimaccia, F., & Leva, S. (2020) · IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) · doi:10.1109/eeeic/icpseurope49358.2020.9160572 · Cited by 4
Accelerated Degradation of Li-Ion Batteries for High Rate Discharge Applications
Thampan, T. M., Ding, Y., & Toomey, L. (2020) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2020-01-0452 · Cited by 4
Petrin, G. K., Arens, S., Schoenfeld, P., Klement, P., & Schlüters, S. (2025) · Applied Energy · doi:10.1016/j.apenergy.2025.126492 · Cited by 5
Raj, P., Richter, E., Schofer, K., Kempf, J., Michel, F., Fill, A., & Birke, K. P. (2025) · e-Prime - Advances in Electrical Engineering Electronics and Energy · doi:10.1016/j.prime.2025.101103 · Cited by 5
Deep eutectic electrolytes for fast charging and wide temperature lithium metal batteries
Lertthanaphol, N., San, M. T., Hossain, M. A., Tulaphol, S., Maihom, T., Wang, M., Jasinski, J. B., Syzdek, J., Cheng, Y., Jaeger, V. W., et al. (2026) · Journal of Power Sources · doi:10.1016/j.jpowsour.2025.238884 · Cited by 3
Long, Z., Chen, K., Tang, M., Zheng, X., Wang, H., Luo, Y., Li, Y., Nie, G., Zhang, X., Gao, G., et al. (2026) · International Journal of Green Energy · doi:10.1080/15435075.2026.2619449 · Cited by 3
Sonthalia, A., Femilda Josepin, J. S., Varuvel, E. G., & Anka, F. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.120879 · Cited by 3
Energy production, storage and management for sustainable VTOL aircraft and advanced air mobility
Elmeligy, A., Safwat, N. E., Moursi, M. S. E., & Sabatini, R. (2026) · Energy Reports · doi:10.1016/j.egyr.2026.109137 · Cited by 3
Degradation-Aware Learning-Based Control for Residential PV–Battery Systems
Ammari, A. C. (2026) · Energies · doi:10.3390/en19061434 · Cited by 3
Evaluating isothermal degradation error in lithium-ion batteries under WLTP drive cycles
Ahmed, N., Shiblee, M. F. H., & Manfo, T. A. (2026) · Applied Energy · doi:10.1016/j.apenergy.2026.128623 · Cited by 5
An Improved Gaussian Process Regression Based Aging Prediction Method for Lithium-Ion Battery
Qu, W., Deng, H., Pang, Y., & Li, Z. (2023) · World Electric Vehicle Journal · doi:10.3390/wevj14060153 · Cited by 3
Gonzalez-Saenz, J., & Becerra, V. M. (2023) · Batteries · doi:10.3390/batteries10010002 · Cited by 3
Vanem, E., Alnes, Ø. Å., & Lam, J. (2021) · Annual Conference of the PHM Society · doi:10.36001/phmconf.2021.v13i1.2972 · Cited by 3
Optimal mobile energy transportation: A co-optimization approach
Singh, P. P., Mamun, S. A., Mishra, S., Bordin, C., Øyvang, T., & Palu, I. (2025) · Journal of Energy Storage · doi:10.1016/j.est.2025.119568 · Cited by 2
Sordi, G., Trippetta, G. M., Luder, D., Berg, S., Li, W., Figgemeier, E., Sauer, D. U., Casalegno, A., & Rabissi, C. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.120653 · Cited by 2
Yan, Y., Meng, J., Song, Z., zhang, S., Pan, Y., Peng, Q., & Peng, J. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.121305 · Cited by 5
Qazi, S. H., Bozalakov, D. V., & Vandevelde, L. (2026) · Results in Engineering · doi:10.1016/j.rineng.2026.109769 · Cited by 3
Warmerdam, S. B., Damianakis, N., & Mouli, G. R. C. (2026) · Sustainable Energy Grids and Networks · doi:10.1016/j.segan.2026.102228 · Cited by 2
Lingzhao, K., & Lee, R. (2021) · SAE International Journal of Advances and Current Practices in Mobility · doi:10.4271/2021-01-0756 · Cited by 2
Rosen, M. A., & Farsi, A. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-18862-6.00005-7 · Cited by 2
Model Predictive Control for EV Chargers Coupling Electro-Thermal and Degradation Battery Models
Dorronsoro, X., de Castro, R. P., Barreras, J. V., Garayalde, E., & Iraola, U. (2023) · IEEE Vehicle Power and Propulsion Conference (VPPC) · doi:10.1109/vppc60535.2023.10403342 · Cited by 2
An Interpretable Semi-Supervised Learning Approach for Battery Lifespan Early Prognostic
Zhang, S., Liu, Z., An, T., Guo, J., & Su, H. (2024) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc62350.2024.10588123 · Cited by 2
An Investigation into the Viability of Cell-Level Temperature Control in Lithium-Ion Battery Packs
Abadie, P. T., & Docimo, D. J. (2024) · ASME Letters in Dynamic Systems and Control · doi:10.1115/1.4066514 · Cited by 2
Hybrid Power System Optimization in Mission-Critical Communication
Leva, S., Grimaccia, F., Rozzi, M., & Mascherpa, M. (2020) · Electronics · doi:10.3390/electronics9111971 · Cited by 2
Precise Model Extraction for Li-Ion Batteries Using Segmented Columb Counting and Kalman Filtering
FatokKiani, A., Ghanbarian, A., Esteghamat, A., Fotowat‐Ahmady, A., & Tahami, F. (2022) · Iranian Conference on Electrical Engineering · doi:10.1109/icee55646.2022.9827098 · Cited by 2
Gao, Z., Xie, H., Zhang, L., Yu, H., Ma, B., Liu, X., & Chen, S. (2022) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2022-01-7035 · Cited by 2
Vasile, A., Perişoară, L. A., & Bacîş, I. B. (2022) · Electronic System-Integration Technology Conference (ESTC) · doi:10.1109/estc55720.2022.9939543 · Cited by 2
A Comprehensive Solution for Ni-Rich Cathodes by Lithium Silicate Coating
Deng, X., Wu, K., Dang, R., Li, N., Zhang, H., Jiao, J., Lee, Y. L., Hu, Z., & Xiao, X. (2021) · Journal of The Electrochemical Society · doi:10.1149/1945-7111/abf4ed · Cited by 2
Batteriespeicherlösungen zur energiewirtschaftlichen Optimierung von Industriebetrieben
Philipp, M., Collath, N., Roth, S., Theumer, P., Will-Ehlers, G., Kellermann, M., & Hesse, H. C. (2022) · Zeitschrift für wirtschaftlichen Fabrikbetrieb · doi:10.1515/zwf-2022-1059 · Cited by 2
Self-citationData Science-Based Battery Operation Management II
Liu, K., Wang, Y., & Lai, X. (2022) · Green energy and technology · doi:10.1007/978-3-031-01340-9_5 · Cited by 1
Bayesian CNN-GRU with Attention Mechanism for Lithium-ion Battery State of Health Estimation
An, T., Liu, Z., Yan, C., Xu, K., Zhang, S., & Su, H. (2024) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc62350.2024.10587630 · Cited by 1
How long could EV batteries last if their thermal management is optimized?
Boutrouelle, M., Panariello, R., Reynier, Y., Mayousse, E., & Martinet, S. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2025.120262 · Cited by 1
Ma, C., Wang, L., Wu, J., Liu, C., Wang, L., & Liao, C. (2026) · Energies · doi:10.3390/en19061506 · Cited by 1
Degradation‐Informed Temperature Analysis for Cycle Life Prediction of LiFePO 4 Batteries
Kee, J., Lee, S., Hwang, J., Yoon, S., Han, S., & Kim, D. (2026) · Battery energy · doi:10.1002/bte2.70124 · Cited by 1
Fatmawati, U. D., Garniwa, I., & Husnayain, F. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.122906 · Cited by 1
Ezeoba, E., Grade, A., Stahl, G., & Sauer, D. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.123856 · Cited by 1
Metadata
- Authors
- Schimpe, M., von Kuepach, M. E., Naumann, M., Hesse, H. C., Smith, K., & Jossen, A.
- Affiliations
- Technical University of Munich (DE)
- National Laboratory of the Rockies (US)
- Venue
- Journal of The Electrochemical Society
- Publisher
- The Electrochemical Society
- Published
- 2018
- Volume
- 165
- Issue
- 2
- Pages
- A181-A193
- ISSN
- 0013-4651 (ISSN-L)
- 1945-7111
- OpenAlex
- W2782996909
- Cited by
- 238
- References
- 26
- Citations by year
- 2026: 40 · 2025: 30 · 2024: 38 · 2023: 28 · 2022: 34 · 2021: 37 · 2020: 17 · 2019: 9 · 2018: 5
- FWCI
- 9.04
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Journal of The Electrochemical Society (publishedVersion, cc-by)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion, other-oa)
- Funders
- Bundesministerium für Wirtschaft und Energie (Federal Ministry for Economic Affairs and Energy) (03ET1205G)
- Department of Energy | National Renewable Energy Laboratory, Office of Energy Efficiency and Renewable Energy (NREL) (AC36-08GO28308)
- 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 iron phosphate batteries, battery degradation modeling, temperature-dependent degradation, capacity fade, calendar aging, cycle aging, battery lifetime prediction, semi-empirical model, stationary energy storage
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
