IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v134y2020ics1364032120305165.html
   My bibliography  Save this article

Advancement of lithium-ion battery cells voltage equalization techniques: A review

Author

Listed:
  • Das, Utpal Kumar
  • Shrivastava, Prashant
  • Tey, Kok Soon
  • Bin Idris, Mohd Yamani Idna
  • Mekhilef, Saad
  • Jamei, Elmira
  • Seyedmahmoudian, Mehdi
  • Stojcevski, Alex

Abstract

Recently, the use of electric batteries has reached great heights due to the invention of electric vehicles (EVs). Many lithium-ion battery cells are usually connected in series to meet the voltage requirements. The voltages of the entire series-connected battery cells in a battery pack should be equal. However, such result is impossible due to some unavoidable reasons in real life. Unbalanced battery cell voltages can reduce storage capacities and may cause explosions or fires in the worst case which is a major obstacle for safe and optimum operations of battery-driven appliances, such as EVs. Therefore, battery cell voltage equalizations have become an important research topic. Many studies have been conducted to develop and improve techniques to equalize battery cell voltages by incorporating various remarkable features. This study makes a comprehensive and systematic review of these cell equalization techniques. The importance and research prospect of battery cell voltage equalizers are discussed. A critical analysis of recent techniques, particularly on construction, operation, and control strategy of equalization circuits, is also presented. Moreover, recent studies are compared based on circuit designs, sizes, costs, complexities, system efficiencies, applications, control strategies, balancing speeds, and voltage/current stresses of different equalizers. Commonly used two different types of control strategies/algorithms in software system of battery cell equalizers are briefly described. The recent research trend of different equalizers is also discussed in detail. Simulation results of few equalization approaches and performance evaluation techniques are analyzed.

Suggested Citation

  • Das, Utpal Kumar & Shrivastava, Prashant & Tey, Kok Soon & Bin Idris, Mohd Yamani Idna & Mekhilef, Saad & Jamei, Elmira & Seyedmahmoudian, Mehdi & Stojcevski, Alex, 2020. "Advancement of lithium-ion battery cells voltage equalization techniques: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:rensus:v:134:y:2020:i:c:s1364032120305165
    DOI: 10.1016/j.rser.2020.110227
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032120305165
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2020.110227?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shubiao Wang & Longyun Kang & Xiangwei Guo & Zefeng Wang & Ming Liu, 2017. "A Novel Layered Bidirectional Equalizer Based on a Buck-Boost Converter for Series-Connected Battery Strings," Energies, MDPI, vol. 10(7), pages 1-15, July.
    2. Manzetti, Sergio & Mariasiu, Florin, 2015. "Electric vehicle battery technologies: From present state to future systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1004-1012.
    3. Das, Utpal Kumar & Tey, Kok Soon & Seyedmahmoudian, Mehdi & Mekhilef, Saad & Idris, Moh Yamani Idna & Van Deventer, Willem & Horan, Bend & Stojcevski, Alex, 2018. "Forecasting of photovoltaic power generation and model optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 912-928.
    4. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    5. Tong, Shi Jie & Same, Adam & Kootstra, Mark A. & Park, Jae Wan, 2013. "Off-grid photovoltaic vehicle charge using second life lithium batteries: An experimental and numerical investigation," Applied Energy, Elsevier, vol. 104(C), pages 740-750.
    6. Hoque, M.M. & Hannan, M.A. & Mohamed, A. & Ayob, A., 2017. "Battery charge equalization controller in electric vehicle applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1363-1385.
    7. 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.
    8. Ashique, Ratil H. & Salam, Zainal & Bin Abdul Aziz, Mohd Junaidi & Bhatti, Abdul Rauf, 2017. "Integrated photovoltaic-grid dc fast charging system for electric vehicle: A review of the architecture and control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1243-1257.
    9. Dong-Hua Zhang & Guo-Rong Zhu & Shao-Jia He & Shi Qiu & Yan Ma & Qin-Mu Wu & Wei Chen, 2015. "Balancing Control Strategy for Li-Ion Batteries String Based on Dynamic Balanced Point," Energies, MDPI, vol. 8(3), pages 1-18, March.
    10. Utpal Kumar Das & Kok Soon Tey & Mehdi Seyedmahmoudian & Mohd Yamani Idna Idris & Saad Mekhilef & Ben Horan & Alex Stojcevski, 2017. "SVR-Based Model to Forecast PV Power Generation under Different Weather Conditions," Energies, MDPI, vol. 10(7), pages 1-17, June.
    11. Yuanmao Ye & Ka Wai Eric Cheng, 2016. "An Automatic Switched-Capacitor Cell Balancing Circuit for Series-Connected Battery Strings," Energies, MDPI, vol. 9(3), pages 1-15, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mohammed, Abubakar Gambo & Elfeky, Karem Elsayed & Wang, Qiuwang, 2022. "Recent advancement and enhanced battery performance using phase change materials based hybrid battery thermal management for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    2. Konara Mudiyanselage Sandun Y. Konara & Mohan Lal Kolhe & Nils Ulltveit-Moe & Indika A. M. Balapuwaduge, 2023. "Reliability Enhancement of Fast Charging Station under Electric Vehicle Supply Equipment Failures and Repairs," Energies, MDPI, vol. 16(6), pages 1-13, March.
    3. Xu, Cheng & Zhang, E & Jiang, Kai & Wang, Kangli, 2022. "Dual fuzzy-based adaptive extended Kalman filter for state of charge estimation of liquid metal battery," Applied Energy, Elsevier, vol. 327(C).
    4. Foad H. Gandoman & Emad M. Ahmed & Ziad M. Ali & Maitane Berecibar & Ahmed F. Zobaa & Shady H. E. Abdel Aleem, 2021. "Reliability Evaluation of Lithium-Ion Batteries for E-Mobility Applications from Practical and Technical Perspectives: A Case Study," Sustainability, MDPI, vol. 13(21), pages 1-24, October.
    5. Wan Chen & Zujun Ding & Jun Liu & Jiarong Kan & Muhammad Shahzad Nazir & Yeqin Wang, 2023. "Half-Bridge Lithium-Ion Battery Equalizer Based on Phase-Shift Strategy," Sustainability, MDPI, vol. 15(2), pages 1-13, January.
    6. Shengyi Luo & Dongchen Qin & Hongxia Wu & Tingting Wang & Jiangyi Chen, 2022. "Multi-Cell-to-Multi-Cell Battery Equalization in Series Battery Packs Based on Variable Duty Cycle," Energies, MDPI, vol. 15(9), pages 1-21, April.
    7. Tian, Jiaqiang & Fan, Yuan & Pan, Tianhong & Zhang, Xu & Yin, Jianning & Zhang, Qingping, 2024. "A critical review on inconsistency mechanism, evaluation methods and improvement measures for lithium-ion battery energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    8. Shu, Xing & Shen, Jiangwei & Chen, Zheng & Zhang, Yuanjian & Liu, Yonggang & Lin, Yan, 2022. "Remaining capacity estimation for lithium-ion batteries via co-operation of multi-machine learning algorithms," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. 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.
    10. Olabi, A.G. & Abdelkareem, Mohammad Ali, 2022. "Renewable energy and climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    11. Rodríguez-Iturriaga, Pablo & Anseán, David & Rodríguez-Bolívar, Salvador & García, Víctor Manuel & González, Manuela & López-Villanueva, Juan Antonio, 2024. "Modeling current-rate effects in lithium-ion batteries based on a distributed, multi-particle equivalent circuit model," Applied Energy, Elsevier, vol. 353(PA).
    12. Chein-Chung Sun & Chun-Hung Chou & Yu-Liang Lin & Yu-Hua Huang, 2022. "A Cost-Effective Passive/Active Hybrid Equalizer Circuit Design," Energies, MDPI, vol. 15(6), pages 1-20, March.
    13. Daniels, Rojo Kurian & Langeh, Harsh & Kumar, Vikas & Chouhan, Satyendra Singh & Prabhakar, Aneesh, 2024. "Faulty cell prediction accuracy comparison of machine learning algorithms using temperature sensor placement optimization approach in immersion cooled Li-ion battery modules," Applied Energy, Elsevier, vol. 367(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Turksoy, Arzu & Teke, Ahmet & Alkaya, Alkan, 2020. "A comprehensive overview of the dc-dc converter-based battery charge balancing methods in electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    2. Wen, Jianping & Zhao, Dan & Zhang, Chuanwei, 2020. "An overview of electricity powered vehicles: Lithium-ion battery energy storage density and energy conversion efficiency," Renewable Energy, Elsevier, vol. 162(C), pages 1629-1648.
    3. Shun-Chung Wang & Chun-Yu Liu & Yi-Hua Liu, 2018. "A Fast Equalizer with Adaptive Balancing Current Control," Energies, MDPI, vol. 11(5), pages 1-15, April.
    4. Chen, Zheng & Zhao, Hongqian & Shu, Xing & Zhang, Yuanjian & Shen, Jiangwei & Liu, Yonggang, 2021. "Synthetic state of charge estimation for lithium-ion batteries based on long short-term memory network modeling and adaptive H-Infinity filter," Energy, Elsevier, vol. 228(C).
    5. Shahjalal, Mohammad & Roy, Probir Kumar & Shams, Tamanna & Fly, Ashley & Chowdhury, Jahedul Islam & Ahmed, Md. Rishad & Liu, Kailong, 2022. "A review on second-life of Li-ion batteries: prospects, challenges, and issues," Energy, Elsevier, vol. 241(C).
    6. Xiao, Zenan & Huang, Xiaoqiao & Liu, Jun & Li, Chengli & Tai, Yonghang, 2023. "A novel method based on time series ensemble model for hourly photovoltaic power prediction," Energy, Elsevier, vol. 276(C).
    7. Bizhong Xia & Zizhou Lao & Ruifeng Zhang & Yong Tian & Guanghao Chen & Zhen Sun & Wei Wang & Wei Sun & Yongzhi Lai & Mingwang Wang & Huawen Wang, 2017. "Online Parameter Identification and State of Charge Estimation of Lithium-Ion Batteries Based on Forgetting Factor Recursive Least Squares and Nonlinear Kalman Filter," Energies, MDPI, vol. 11(1), pages 1-23, December.
    8. Sun, Li & Li, Guanru & You, Fengqi, 2020. "Combined internal resistance and state-of-charge estimation of lithium-ion battery based on extended state observer," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    9. Muhammad Umair Ali & Amad Zafar & Sarvar Hussain Nengroo & Sadam Hussain & Muhammad Junaid Alvi & Hee-Je Kim, 2019. "Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation," Energies, MDPI, vol. 12(3), pages 1-33, January.
    10. Woo-Yong Kim & Pyeong-Yeon Lee & Jonghoon Kim & Kyung-Soo Kim, 2019. "A Nonlinear-Model-Based Observer for a State-of-Charge Estimation of a Lithium-Ion Battery in Electric Vehicles," Energies, MDPI, vol. 12(17), pages 1-20, September.
    11. Eltoumi, Fouad M. & Becherif, Mohamed & Djerdir, Abdesslem & Ramadan, Haitham.S., 2021. "The key issues of electric vehicle charging via hybrid power sources: Techno-economic viability, analysis, and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    12. Korkmaz, Deniz, 2021. "SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting," Applied Energy, Elsevier, vol. 300(C).
    13. Shungang Xu & Kai Gao & Xiaobing Zhang & Kangle Li, 2019. "Double-Layer E-Structure Equalization Circuit for Series Connected Battery Strings," Energies, MDPI, vol. 12(22), pages 1-16, November.
    14. Md. Sazal Miah & Molla Shahadat Hossain Lipu & Sheikh Tanzim Meraj & Kamrul Hasan & Shaheer Ansari & Taskin Jamal & Hasan Masrur & Rajvikram Madurai Elavarasan & Aini Hussain, 2021. "Optimized Energy Management Schemes for Electric Vehicle Applications: A Bibliometric Analysis towards Future Trends," Sustainability, MDPI, vol. 13(22), pages 1-38, November.
    15. Bhatti, Ghanishtha & Mohan, Harshit & Raja Singh, R., 2021. "Towards the future of smart electric vehicles: Digital twin technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    16. Hassan, Muhammed A. & Bailek, Nadjem & Bouchouicha, Kada & Nwokolo, Samuel Chukwujindu, 2021. "Ultra-short-term exogenous forecasting of photovoltaic power production using genetically optimized non-linear auto-regressive recurrent neural networks," Renewable Energy, Elsevier, vol. 171(C), pages 191-209.
    17. Martina Radicioni & Valentina Lucaferri & Francesco De Lia & Antonino Laudani & Roberto Lo Presti & Gabriele Maria Lozito & Francesco Riganti Fulginei & Riccardo Schioppo & Mario Tucci, 2021. "Power Forecasting of a Photovoltaic Plant Located in ENEA Casaccia Research Center," Energies, MDPI, vol. 14(3), pages 1-22, January.
    18. Alfredo Alvarez-Diazcomas & Adyr A. Estévez-Bén & Juvenal Rodríguez-Reséndiz & Miguel-Angel Martínez-Prado & Jorge D. Mendiola-Santíbañez, 2020. "A Novel RC-Based Architecture for Cell Equalization in Electric Vehicles," Energies, MDPI, vol. 13(9), pages 1-16, May.
    19. Xiaoli Sun & Zhengguo Li & Xiaolin Wang & Chengjiang Li, 2019. "Technology Development of Electric Vehicles: A Review," Energies, MDPI, vol. 13(1), pages 1-29, December.
    20. Nguyen, Thi Ngoc & Müsgens, Felix, 2022. "What drives the accuracy of PV output forecasts?," Applied Energy, Elsevier, vol. 323(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:134:y:2020:i:c:s1364032120305165. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.