), Hailong Lib()· A data-driven method is proposed to construct battery OCV-SOC curves using onboard data.
· A benchmark for calibrating battery SOC and SOH of data segments is built.
· The method is validated for different types of LIBs, including LFP and NCM.
Lithium-ion batteries (LiB) are widely used in electric vehicles (EVs) and battery energy storage systems, and accurate state estimation relying on the relationship between battery Open-Circuit-Voltage (OCV) and State-of-Charge (SOC) is the basis for their safe and efficient applications. To avoid the time-consuming lab test needed for obtaining OCV-SOC curves, this study proposes a data-driven universal method by using operation data collected onboard about the variation of OCV with ampere-hour (Ah). To guarantee high reliability, a series of constraints have been implemented. To verify the effectiveness of this method, the constructed OCV-SOC curves are used to estimate battery SOC and State-of-Health (SOH), which are compared with data from both lab tests and EV manufacturers. Results show that a higher accuracy can be achieved in the estimation of both SOC and SOH, for which the maximum deviations are less than 3.0% and 2.9% respectively.
Hannan MA, Hoque MM, Mohamed A, Ayob A. Review of energy storage systems for electric vehicle applications: issues and challenges. Renew Sustain Energy Rev 2017;69:771–89.
Lipu MSH, Hannan MA, Karim TF, Hussain A, Saad MHM, Ayob A, et al. Intelligent algorithms and control strategies for battery management system in electric vehicles: progress, challenges and future outlook. J Clean Prod 2021;292:126044.
Yang R, Xiong R, Shen W, Lin X. Extreme learning machine based thermal model for lithium-ion batteries of electric vehicles under external short circuit. Engineering 2021;7:395–405.
Martinez CM, Hu X, Cao D, Velenis E, Gao B, Wellers M. Energy management in plug-in hybrid electric vehicles: recent progress and a connected vehicles perspective. IEEE Trans Veh Technol 2017;66(6):4534–49.
Shrivastava P, Soon TK, Idris MYIB, Mekhilef S. Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries. Renew Sustain Energy Rev 2019;113:109233.
Meng J, Ricco M, Luo G, Swierczynski M, Stroe DI, Stroe AI, et al. An overview and comparison of online implementable SOC estimation methods for lithium-ion battery. IEEE Trans Ind Appl 2018;54(2):1583–91.
Pan B, Dong D, Wang J, Nie J, Liu S, Cao Y, et al. Aging mechanism diagnosis of lithium ion battery by open circuit voltage analysis. Electrochim Acta 2020;362:137101.
Wang Q, Wang J, Zhao P, Kang J, Yan F, Du C. Correlation between the model accuracy and model-based SOC estimation. Electrochim Acta 2017;228(20):146–59.
Shu X, Li G, Shen J, Yan W, Chen Z, Liu Y. An adaptive fusion estimation algorithm for state of charge of lithium-ion batteries considering wide onboard temperature and degradation. J Power Sources 2020;462(30):228132.
Lai X, Wang S, Ma S, Xie J, Zheng Y. Parameter sensitivity analysis and simplification of equivalent circuit model for the state of charge of lithium-ion batteries. Electrochim Acta 2020;330(10):135239.
Gismero A, Schaltz E, Stroe D. Recursive state of charge and state of health estimation method for lithium-ion batteries based on coulomb counting and open circuit voltage. Energies 2020;13(7):1811.
Bian X, Wei Z, Li W, Pou J, Sauer DU, Liu L. State-of-health estimation of lithium-ion batteries by fusing an open circuit voltage model and incremental capacity analysis. IEEE Trans Power Electron 2022;37(2):2226–36.
Meng J, Stroe D, Ricco M, Luo G, Swierczynski M, Teodorescu R. A novel multiple correction approach for fast open circuit voltage prediction of lithium-ion battery. IEEE Trans Energy Convers 2019;34(2):1115–23.
Han X, Lua L, Zheng Y, Feng X, Li Z, Li J, et al. A review on the key issues of the lithium ion battery degradation among the whole life cycle. eTransportation 2019;1:100005.
Zhang Q, Shang Y, Li Y, Cui N, Duan B, Zhang C. A novel fractional variable-order equivalent circuit model and parameter identification of electric vehicle Li-ion batteries. ISA (Instrum Soc Am) Trans 2020;97:448–57.
Cheng X, Yao L, Pecht M. Lithium-ion battery state-of-charge estimation based on deconstructed equivalent circuit at different open-circuit voltage relaxation times. J Zhejiang Univ - Sci 2017;18(4):256–67.
Chen Y, Yang G, Liu X, He Z. A time-efficient and accurate open circuit voltage estimation method for lithium-ion batteries. Energies 2019;12(9):1803.
Saxena S, Xing Y, Kwon D, Pecht M. Accelerated degradation model for C-rate loading of lithium-ion batteries. Electr. Power Energy Sys. 2019;107:438–45.
Diao W, Saxena S, Pecht M. Accelerated cycle life testing and capacity degradation modeling of LiCoO2-graphite cells. J Power Sources 2019;435(30):226830.
Tian J, Xiong R, Shen W, Sun F. Electrode aging estimation and open-circuit voltage reconstruction for lithium-ion batteries. Energy Storage Mater May 2021;37:283–95.
Gao W, Zheng Y, Ouyang M, Li J, Lai X, Hu X. Micro-short-circuit diagnosis for series-connected lithium-ion battery packs using mean-difference model. IEEE Trans Ind Electron 2019;66(3):2132–42.
Yang C, Wang X, Fang Q, Dai H, Cao Y, Wei X. An online SOC and capacity estimation method for aged lithium-ion battery pack considering cell inconsistency. J Energy Storage 2020;29:101250.
Huang D, Chen Z, Zheng C, Li H. A model-based state-of-charge estimation method for series connected lithium-ion battery pack considering fast-varying cell temperature. Energy 2019;185:847–61.
Chen X, Lei H, Xiong R, Shen W, Yang R. A novel approach to construct open circuit voltage for state of charge estimation of lithium ion batteries in electric vehicles. Appl Energy 2019;255:113758.
Li S, He H, Li J. Big data driven lithium-ion battery modeling method based on SDAE-ELM algorithm and data pre-processing technology. Appl Energy 2019;242:1259–73.
Li K, Zhou P, Lu Y, Han X, Li X, Zheng Y. Battery life estimation based on cloud data for electric vehicles. J Power Sources 2020;468:228192.
Hong J, Wang Z, Chen W, Wang L, Qu C. Online joint-prediction of multi-forward-step battery SOC using LSTM neural networks and multiple linear regression for real-world electric vehicles. J Energy Storage 2020;30:101459.
Pattipati B, Balasingam B, Avvari GV, Pattipati KR, Bar-Shalom Y. Open circuit voltage characterization of lithium-ion batteries. J Power Sources 2014;269:317–33.
Xiong R, Sun F, Gong X, Gao C. A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles. Appl Energy Jan 2014;113:1421–33.
Xiong R, Huang J, Duan Y, Shen W. Enhanced lithium-ion battery model considering critical surface charge behavior. Appl Energy May 2022;314:118915.
Journal Collaboration: Yao Meng (Ms.)✉️ +86-10-83470574
Technical Support: Kuo Zhao (Mr.)✉️ +86-10-83470507
Media Contact: Hao Jin (Mr.)✉️ +86-10-83470559
Address: Floor 6, Tower B, Xueyan Building, Shuangqing Road, Haidian District, Beijing 100084, China.
Copyright © 2025 Tsinghua University Press Ltd.
京公网安备11010802044758号