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Critical review of state of health estimation methods of Li-ion batteries for real applications

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  1. Phattara Khumprom & Nita Yodo, 2019. "A Data-Driven Predictive Prognostic Model for Lithium-ion Batteries based on a Deep Learning Algorithm," Energies, MDPI, vol. 12(4), pages 1-21, February.
  2. Yang, Bo & Qian, Yucun & Li, Qiang & Chen, Qian & Wu, Jiyang & Luo, Enbo & Xie, Rui & Zheng, Ruyi & Yan, Yunfeng & Su, Shi & Wang, Jingbo, 2024. "Critical summary and perspectives on state-of-health of lithium-ion battery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
  3. Li, Alan G. & West, Alan C. & Preindl, Matthias, 2022. "Towards unified machine learning characterization of lithium-ion battery degradation across multiple levels: A critical review," Applied Energy, Elsevier, vol. 316(C).
  4. Xiaoyu Li & Xing Shu & Jiangwei Shen & Renxin Xiao & Wensheng Yan & Zheng Chen, 2017. "An On-Board Remaining Useful Life Estimation Algorithm for Lithium-Ion Batteries of Electric Vehicles," Energies, MDPI, vol. 10(5), pages 1-15, May.
  5. Fujin Wang & Zhi Zhai & Zhibin Zhao & Yi Di & Xuefeng Chen, 2024. "Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  6. Pan, Haihong & Lü, Zhiqiang & Wang, Huimin & Wei, Haiyan & Chen, Lin, 2018. "Novel battery state-of-health online estimation method using multiple health indicators and an extreme learning machine," Energy, Elsevier, vol. 160(C), pages 466-477.
  7. Fan, Guodong & Zhang, Xi, 2023. "Battery capacity estimation using 10-second relaxation voltage and a convolutional neural network," Applied Energy, Elsevier, vol. 330(PA).
  8. Li, J. & Adewuyi, K. & Lotfi, N. & Landers, R.G. & Park, J., 2018. "A single particle model with chemical/mechanical degradation physics for lithium ion battery State of Health (SOH) estimation," Applied Energy, Elsevier, vol. 212(C), pages 1178-1190.
  9. Lee, Meng Hong & Chang, Dong-Shang, 2016. "Allocative efficiency of high-power Li-ion batteries from automotive mode (AM) to storage mode (SM)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 60-67.
  10. Xinwei Sun & Yang Zhang & Yongcheng Zhang & Licheng Wang & Kai Wang, 2023. "Summary of Health-State Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy," Energies, MDPI, vol. 16(15), pages 1-19, July.
  11. Jiang, Bo & Dai, Haifeng & Wei, Xuezhe & Xu, Tianjiao, 2019. "Joint estimation of lithium-ion battery state of charge and capacity within an adaptive variable multi-timescale framework considering current measurement offset," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
  12. Martin Henke & Getu Hailu, 2020. "Thermal Management of Stationary Battery Systems: A Literature Review," Energies, MDPI, vol. 13(16), pages 1-16, August.
  13. Yunlong Han & Conghui Li & Linfeng Zheng & Gang Lei & Li Li, 2023. "Remaining Useful Life Prediction of Lithium-Ion Batteries by Using a Denoising Transformer-Based Neural Network," Energies, MDPI, vol. 16(17), pages 1-16, August.
  14. Bing Jiang & Zeqi Chen & Feifan Chen, 2019. "Influence of Sampling Delay on the Estimation of Lithium-Ion Battery Parameters and an Optimized Estimation Method," Energies, MDPI, vol. 12(10), pages 1-16, May.
  15. Zhang, Jianyu & Lu, Wei, 2022. "Sparse data machine learning for battery health estimation and optimal design incorporating material characteristics," Applied Energy, Elsevier, vol. 307(C).
  16. Cadini, F. & Sbarufatti, C. & Cancelliere, F. & Giglio, M., 2019. "State-of-life prognosis and diagnosis of lithium-ion batteries by data-driven particle filters," Applied Energy, Elsevier, vol. 235(C), pages 661-672.
  17. Sun, Li & Sun, Wen & You, Fengqi, 2020. "Core temperature modelling and monitoring of lithium-ion battery in the presence of sensor bias," Applied Energy, Elsevier, vol. 271(C).
  18. Shida Jiang & Zhengxiang Song, 2021. "Estimating the State of Health of Lithium-Ion Batteries with a High Discharge Rate through Impedance," Energies, MDPI, vol. 14(16), pages 1-20, August.
  19. Wenxian Duan & Chuanxue Song & Silun Peng & Feng Xiao & Yulong Shao & Shixin Song, 2020. "An Improved Gated Recurrent Unit Network Model for State-of-Charge Estimation of Lithium-Ion Battery," Energies, MDPI, vol. 13(23), pages 1-19, December.
  20. Xu, Zhicheng & Wang, Jun & Lund, Peter D. & Zhang, Yaoming, 2021. "Estimation and prediction of state of health of electric vehicle batteries using discrete incremental capacity analysis based on real driving data," Energy, Elsevier, vol. 225(C).
  21. Li, Renzheng & Hong, Jichao & Zhang, Huaqin & Chen, Xinbo, 2022. "Data-driven battery state of health estimation based on interval capacity for real-world electric vehicles," Energy, Elsevier, vol. 257(C).
  22. Taichun Qin & Shengkui Zeng & Jianbin Guo & Zakwan Skaf, 2016. "A Rest Time-Based Prognostic Framework for State of Health Estimation of Lithium-Ion Batteries with Regeneration Phenomena," Energies, MDPI, vol. 9(11), pages 1-18, November.
  23. Lai, Xin & Yi, Wei & Cui, Yifan & Qin, Chao & Han, Xuebing & Sun, Tao & Zhou, Long & Zheng, Yuejiu, 2021. "Capacity estimation of lithium-ion cells by combining model-based and data-driven methods based on a sequential extended Kalman filter," Energy, Elsevier, vol. 216(C).
  24. Das, Kaushik & Kumar, Roushan & Krishna, Anurup, 2024. "Analyzing electric vehicle battery health performance using supervised machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
  25. Yang, Jufeng & Xia, Bing & Huang, Wenxin & Fu, Yuhong & Mi, Chris, 2018. "Online state-of-health estimation for lithium-ion batteries using constant-voltage charging current analysis," Applied Energy, Elsevier, vol. 212(C), pages 1589-1600.
  26. Ashleigh Townsend & Rupert Gouws, 2023. "A Comparative Review of Capacity Measurement in Energy Storage Devices," Energies, MDPI, vol. 16(10), pages 1-26, May.
  27. Goh, Taedong & Park, Minjun & Seo, Minhwan & Kim, Jun Gu & Kim, Sang Woo, 2017. "Capacity estimation algorithm with a second-order differential voltage curve for Li-ion batteries with NMC cathodes," Energy, Elsevier, vol. 135(C), pages 257-268.
  28. Singh, Karanjot & Tjahjowidodo, Tegoeh & Boulon, Loïc & Feroskhan, Mir, 2022. "Framework for measurement of battery state-of-health (resistance) integrating overpotential effects and entropy changes using energy equilibrium," Energy, Elsevier, vol. 239(PA).
  29. Li, Yi & Liu, Kailong & Foley, Aoife M. & Zülke, Alana & Berecibar, Maitane & Nanini-Maury, Elise & Van Mierlo, Joeri & Hoster, Harry E., 2019. "Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
  30. Cheng, Ming & Zhang, Xuan & Ran, Aihua & Wei, Guodan & Sun, Hongbin, 2023. "Optimal dispatch approach for second-life batteries considering degradation with online SoH estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
  31. Zhang, Kai & Bai, Dongxin & Li, Yong & Song, Ke & Zheng, Bailin & Yang, Fuqian, 2024. "Robust state-of-charge estimator for lithium-ion batteries enabled by a physics-driven dual-stage attention mechanism," Applied Energy, Elsevier, vol. 359(C).
  32. Vichard, L. & Ravey, A. & Venet, P. & Harel, F. & Pelissier, S. & Hissel, D., 2021. "A method to estimate battery SOH indicators based on vehicle operating data only," Energy, Elsevier, vol. 225(C).
  33. Zhang, Yajun & Liu, Yajie & Wang, Jia & Zhang, Tao, 2022. "State-of-health estimation for lithium-ion batteries by combining model-based incremental capacity analysis with support vector regression," Energy, Elsevier, vol. 239(PB).
  34. Omid Rahbari & Noshin Omar & Joeri Van Mierlo & Marc A. Rosen & Thierry Coosemans & Maitane Berecibar, 2019. "Electric Vehicle Battery Lifetime Extension through an Intelligent Double-Layer Control Scheme," Energies, MDPI, vol. 12(8), pages 1-24, April.
  35. Ma’d El-Dalahmeh & Maher Al-Greer & Mo’ath El-Dalahmeh & Michael Short, 2020. "Time-Frequency Image Analysis and Transfer Learning for Capacity Prediction of Lithium-Ion Batteries," Energies, MDPI, vol. 13(20), pages 1-19, October.
  36. Deng, Yuanwang & Ying, Hejie & E, Jiaqiang & Zhu, Hao & Wei, Kexiang & Chen, Jingwei & Zhang, Feng & Liao, Gaoliang, 2019. "Feature parameter extraction and intelligent estimation of the State-of-Health of lithium-ion batteries," Energy, Elsevier, vol. 176(C), pages 91-102.
  37. Bahloul, Mohamed & Daoud, Mohamed & Khadem, Shafi K., 2024. "Optimal dispatch of battery energy storage for multi-service provision in a collocated PV power plant considering battery ageing," Energy, Elsevier, vol. 293(C).
  38. Kai-Rong Lin & Chien-Chung Huang & Kin-Cheong Sou, 2023. "Lithium-Ion Battery State of Health Estimation Using Simple Regression Model Based on Incremental Capacity Analysis Features," Energies, MDPI, vol. 16(20), pages 1-20, October.
  39. Yang, Lin & Cai, Yishan & Yang, Yixin & Deng, Zhongwei, 2020. "Supervisory long-term prediction of state of available power for lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 257(C).
  40. Miquel Martí-Florences & Andreu Cecilia & Ramon Costa-Castelló, 2023. "Modelling and Estimation in Lithium-Ion Batteries: A Literature Review," Energies, MDPI, vol. 16(19), pages 1-36, September.
  41. Ummartyotin, S. & Bunnak, N. & Manuspiya, H., 2016. "A comprehensive review on modified clay based composite for energy based materials," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 466-472.
  42. Liu, Sijia & Winter, Michaela & Lewerenz, Meinert & Becker, Jan & Sauer, Dirk Uwe & Ma, Zeyu & Jiang, Jiuchun, 2019. "Analysis of cyclic aging performance of commercial Li4Ti5O12-based batteries at room temperature," Energy, Elsevier, vol. 173(C), pages 1041-1053.
  43. Lisa Calearo & Charalampos Ziras & Andreas Thingvad & Mattia Marinelli, 2022. "Agnostic Battery Management System Capacity Estimation for Electric Vehicles," Energies, MDPI, vol. 15(24), pages 1-17, December.
  44. Bian, Chong & He, Huoliang & Yang, Shunkun, 2020. "Stacked bidirectional long short-term memory networks for state-of-charge estimation of lithium-ion batteries," Energy, Elsevier, vol. 191(C).
  45. Liu, Gengfeng & Zhang, Xiangwen & Liu, Zhiming, 2022. "State of health estimation of power batteries based on multi-feature fusion models using stacking algorithm," Energy, Elsevier, vol. 259(C).
  46. Theodoros Kalogiannis & Md Sazzad Hosen & Mohsen Akbarzadeh Sokkeh & Shovon Goutam & Joris Jaguemont & Lu Jin & Geng Qiao & Maitane Berecibar & Joeri Van Mierlo, 2019. "Comparative Study on Parameter Identification Methods for Dual-Polarization Lithium-Ion Equivalent Circuit Model," Energies, MDPI, vol. 12(21), pages 1-35, October.
  47. Zhang, Shuzhi & Zhang, Qiang & Liu, Dayong & Dai, Xian & Zhang, Xiongwen, 2022. "State-of-charge estimation for lithium-ion battery during constant current charging process based on model parameters updated periodically," Energy, Elsevier, vol. 257(C).
  48. Harper, Gavin D.J. & Kendrick, Emma & Anderson, Paul A. & Mrozik, Wojciech & Christensen, Paul & Lambert, Simon & Greenwood, David & Das, Prodip K. & Ahmeid, Mohamed & Milojevic, Zoran & Du, Wenjia & , 2023. "Roadmap for a sustainable circular economy in lithium-ion and future battery technologies," LSE Research Online Documents on Economics 118420, London School of Economics and Political Science, LSE Library.
  49. Bian, Xiaolei & Liu, Longcheng & Yan, Jinying, 2019. "A model for state-of-health estimation of lithium ion batteries based on charging profiles," Energy, Elsevier, vol. 177(C), pages 57-65.
  50. Ko, Chi-Jyun & Chen, Kuo-Ching & Su, Ting-Wei, 2024. "Differential current in constant-voltage charging mode: A novel tool for state-of-health and state-of-charge estimation of lithium-ion batteries," Energy, Elsevier, vol. 288(C).
  51. Nicolas T. D. Fernandes & Anderson Rocha & Danilo Brandao & Braz C. Filho, 2021. "Comparison of Advanced Charge Strategies for Modular Cascaded Battery Chargers," Energies, MDPI, vol. 14(12), pages 1-28, June.
  52. Khaleghi, Sahar & Hosen, Md Sazzad & Karimi, Danial & Behi, Hamidreza & Beheshti, S. Hamidreza & Van Mierlo, Joeri & Berecibar, Maitane, 2022. "Developing an online data-driven approach for prognostics and health management of lithium-ion batteries," Applied Energy, Elsevier, vol. 308(C).
  53. Hector Beltran & Sam Harrison & Agustí Egea-Àlvarez & Lie Xu, 2020. "Techno-Economic Assessment of Energy Storage Technologies for Inertia Response and Frequency Support from Wind Farms," Energies, MDPI, vol. 13(13), pages 1-21, July.
  54. Jussi Sihvo & Tomi Roinila & Daniel-Ioan Stroe, 2020. "Broadband Impedance Measurement of Lithium-Ion Battery in the Presence of Nonlinear Distortions," Energies, MDPI, vol. 13(10), pages 1-15, May.
  55. Ayuso, Pablo & Beltran, Hector & Segarra-Tamarit, Jorge & Pérez, Emilio, 2021. "Optimized profitability of LFP and NMC Li-ion batteries in residential PV applications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 183(C), pages 97-115.
  56. Yi Wu & Saurabh Saxena & Yinjiao Xing & Youren Wang & Chuan Li & Winco K. C. Yung & Michael Pecht, 2018. "Analysis of Manufacturing-Induced Defects and Structural Deformations in Lithium-Ion Batteries Using Computed Tomography," Energies, MDPI, vol. 11(4), pages 1-22, April.
  57. Chi Zhang & Fuwu Yan & Changqing Du & Jianqiang Kang & Richard Fiifi Turkson, 2017. "Evaluating the Degradation Mechanism and State of Health of LiFePO 4 Lithium-Ion Batteries in Real-World Plug-in Hybrid Electric Vehicles Application for Different Ageing Paths," Energies, MDPI, vol. 10(1), pages 1-13, January.
  58. Braco, Elisa & San Martín, Idoia & Sanchis, Pablo & Ursúa, Alfredo & Stroe, Daniel-Ioan, 2022. "State of health estimation of second-life lithium-ion batteries under real profile operation," Applied Energy, Elsevier, vol. 326(C).
  59. Rauf, Huzaifa & Khalid, Muhammad & Arshad, Naveed, 2022. "Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
  60. Neha Bhushan & Saad Mekhilef & Kok Soon Tey & Mohamed Shaaban & Mehdi Seyedmahmoudian & Alex Stojcevski, 2022. "Overview of Model- and Non-Model-Based Online Battery Management Systems for Electric Vehicle Applications: A Comprehensive Review of Experimental and Simulation Studies," Sustainability, MDPI, vol. 14(23), pages 1-31, November.
  61. Ly, Sel & Xie, Jiahang & Wolter, Franz-Erich & Nguyen, Hung D. & Weng, Yu, 2023. "T-shape data and probabilistic remaining useful life prediction for Li-ion batteries using multiple non-crossing quantile long short-term memory," Applied Energy, Elsevier, vol. 349(C).
  62. Li, Xiaoyu & Wang, Zhenpo & Zhang, Lei, 2019. "Co-estimation of capacity and state-of-charge for lithium-ion batteries in electric vehicles," Energy, Elsevier, vol. 174(C), pages 33-44.
  63. Lin, Chun Pang & Ling, Man Ho & Cabrera, Javier & Yang, Fangfang & Yu, Denis Yau Wai & Tsui, Kwok Leung, 2021. "Prognostics for lithium-ion batteries using a two-phase gamma degradation process model," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
  64. Penelope K. Jones & Ulrich Stimming & Alpha A. Lee, 2022. "Impedance-based forecasting of lithium-ion battery performance amid uneven usage," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  65. Tarhan, Burak & Yetik, Ozge & Karakoc, Tahir Hikmet, 2021. "Hybrid battery management system design for electric aircraft," Energy, Elsevier, vol. 234(C).
  66. Liu, Yisheng & Fan, Guodong & Zhou, Boru & Chen, Shun & Sun, Ziqiang & Wang, Yansong & Zhang, Xi, 2023. "Rapid and flexible battery capacity estimation using random short-time charging segments based on residual convolutional networks," Applied Energy, Elsevier, vol. 351(C).
  67. Haifeng Dai & Bo Jiang & Xuezhe Wei, 2018. "Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient," Energies, MDPI, vol. 11(1), pages 1-18, January.
  68. Shun Xiang & Guangdi Hu & Ruisen Huang & Feng Guo & Pengkai Zhou, 2018. "Lithium-Ion Battery Online Rapid State-of-Power Estimation under Multiple Constraints," Energies, MDPI, vol. 11(2), pages 1-20, January.
  69. Qiaohua Fang & Xuezhe Wei & Tianyi Lu & Haifeng Dai & Jiangong Zhu, 2019. "A State of Health Estimation Method for Lithium-Ion Batteries Based on Voltage Relaxation Model," Energies, MDPI, vol. 12(7), pages 1-18, April.
  70. Shrivastava, Prashant & Soon, Tey Kok & Idris, Mohd Yamani Idna Bin & Mekhilef, Saad, 2019. "Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
  71. Zheng Chen & Xiaoyu Li & Jiangwei Shen & Wensheng Yan & Renxin Xiao, 2016. "A Novel State of Charge Estimation Algorithm for Lithium-Ion Battery Packs of Electric Vehicles," Energies, MDPI, vol. 9(9), pages 1-15, September.
  72. Khaleghi, Sahar & Hosen, Md Sazzad & Van Mierlo, Joeri & Berecibar, Maitane, 2024. "Towards machine-learning driven prognostics and health management of Li-ion batteries. A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
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  75. Hector Beltran & Pablo Ayuso & Emilio Pérez, 2020. "Lifetime Expectancy of Li-Ion Batteries used for Residential Solar Storage," Energies, MDPI, vol. 13(3), pages 1-18, January.
  76. Zheng, Yuejiu & Cui, Yifan & Han, Xuebing & Ouyang, Minggao, 2021. "A capacity prediction framework for lithium-ion batteries using fusion prediction of empirical model and data-driven method," Energy, Elsevier, vol. 237(C).
  77. Lin, Yan-Hui & Ruan, Sheng-Jia & Chen, Yun-Xia & Li, Yan-Fu, 2023. "Physics-informed deep learning for lithium-ion battery diagnostics using electrochemical impedance spectroscopy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
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