A Cost-Effective Fast Cell Balancing Technique for Lithium- Ion Batteries using a Single DC–DC Converter with Direct Energy Transfer

Notice

This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 16 | 02 | Page :
    By

    Challa Krishnarao,

  • B. Manmadha kumar,

  • Sarat Kumar sahoo,

  • Killamsettypranitha,

  • YernagulaDeekshitha,

  • Bagatti Chiranjeevi,

  1. Associate Professor, Department of Electrical and Electronics Engineering, Aditya institute of technology and management, tekkali, Srikakulam, Andhra Pradesh, India
  2. Associate Professor, Department of Electrical and Electronics Engineering, Aditya institute of technology and management, tekkali, Srikakulam, Andhra Pradesh, India
  3. Professor, Department of Electrical Engineering, Parala Maharaja Engineering College, Berhampur, Odisha, India
  4. Student, Department of Electrical and Electronics Engineering, Aditya institute of technology and management, tekkali, Srikakulam, Andhra Pradesh, India
  5. Student, Department of Electrical and Electronics Engineering, Aditya institute of technology and management, tekkali, Srikakulam, Andhra Pradesh, India
  6. Student, Department of Electrical and Electronics Engineering, Aditya institute of technology and management, tekkali, Srikakulam, Andhra Pradesh, India

Abstract

A novel quick lithium-ion battery balancing method with a single DC-DC converter for facilitating the direct energy transfer process in low and high voltage cells is introduced in this research work. Cost effectiveness in the design of the switch network is achieved by the use of relays in switching the cells. A control circuit including an MCU and a battery management IC is used for the sensing of cell voltages and hence the overall battery protection. The validity of the performance efficiency of this technology is justified by the creation of a prototype circuit setup by the employment of twelve lithium-ion batteries that consumes an incredible balance time of 48 minutes during the charging process with a maximum efficiency of 89.85%. The efficiency of the proposed balancing circuit based on balance time and implementation cost is justified over the existing technology. Hardware details regarding Battery Management Systems in static and EV applications are considered in the article. This article helps in the determination and measurement of crucial parameters while designing a Battery Management System based on its implementation scenarios with a snapshot description regarding the existing trends in state-of-the-art technology. Implementation details regarding the battery packs based on the commercial models for EVs are discussed in this article. Implementation details regarding the measurement of critical parameters like temperature, voltage, and current and balance control strategies are considered in this article.

Keywords: Battery management system (BMS), Cell balancing, DC-DC converter, MCU, Efficiency

How to cite this article:
Challa Krishnarao, B. Manmadha kumar, Sarat Kumar sahoo, Killamsettypranitha, YernagulaDeekshitha, Bagatti Chiranjeevi. A Cost-Effective Fast Cell Balancing Technique for Lithium- Ion Batteries using a Single DC–DC Converter with Direct Energy Transfer. Journal of Power Electronics and Power Systems. 2026; 16(02):-.
How to cite this URL:
Challa Krishnarao, B. Manmadha kumar, Sarat Kumar sahoo, Killamsettypranitha, YernagulaDeekshitha, Bagatti Chiranjeevi. A Cost-Effective Fast Cell Balancing Technique for Lithium- Ion Batteries using a Single DC–DC Converter with Direct Energy Transfer. Journal of Power Electronics and Power Systems. 2026; 16(02):-. Available from: https://journals.stmjournals.com/jopeps/article=2026/view=247584


References

  1. Hassan MU, Saha S, Haque ME, Islam S, Mahmud A, Mendis N. A comprehensive review of battery state of charge estimation techniques. Sustainable Energy Technologies and Assessments. 2022 Dec 1;54:102801.
  2. Goh HH, Lan Z, Zhang D, Dai W, Kurniawan TA, Goh KC. Estimation of the state of health (SOH) of batteries using discrete curvature feature extraction. Journal of Energy Storage. 2022 Jun 1;50:104646.
  3. Nuroldayeva G, Serik Y, Adair D, Uzakbaiuly B, Bakenov Z. State of health estimation methods for lithium‐ion batteries. International Journal of Energy Research. 2023;2023(1):4297545.
  4. Zhao H, Chen Z, Shu X, Shen J, Lei Z, Zhang Y. State of health estimation for lithium-ion batteries based on hybrid attention and deep learning. Reliability Engineering & System Safety. 2023 Apr 1;232:109066.
  5. Sarda J, Patel H, Popat Y, Hui KL, Sain M. Review of management system and state-of-charge estimation methods for electric vehicles. World Electric Vehicle Journal. 2023 Nov 27;14(12):325.
  6. Lipu MH, Miah MS, Jamal T, Rahman T, Ansari S, Rahman MS, Ashique RH, Shihavuddin AS, Shakib MN. Artificial intelligence approaches for advanced battery management system in electric vehicle applications: A statistical analysis towards future research opportunities. Vehicles. 2023 Dec 25;6(1):22-70.
  7. Ibezim O, Prasad K, Kilby J. Intelligent Hybrid Solar–Wind Off-Grid (Standalone) Electric Vehicle Charging Stations for Remote Areas and Developing Countries: A Comprehensive Review. Electronics. 2026 May 22;15(11):2253.
  8. Krishna TN, Kumar SV, Srinivasa Rao S, Chang L. Powering the future: Advanced battery management systems (BMS) for electric vehicles. Energies. 2024 Jul 9;17(14):3360.
  9. Nyamathulla S, Dhanamjayulu C. A review of battery energy storage systems and advanced battery management system for different applications: Challenges and recommendations. Journal of Energy Storage. 2024 May 1;86:111179.
  10. Vijaychandra J, Vanajakshi B, Prasad BR, Prakash KV, Anjaneyulu US, Lakshmi PV. A Critical Review on Battery Management Systems in Electric Vehicles: Key Features, Challenges and Recommendations. Emerging Technologies & Applications in Electrical Engineering. 2024 Jul 8:1-6.
  11. Khan N, Ooi CA, Alturki A, Amir M, Alharbi T. A critical review of battery cell balancing techniques, optimal design, converter topologies, and performance evaluation for optimizing storage system in electric vehicles. Energy Reports. 2024 Jun 1;11:4999-5032.
  12. Khan N, Ooi CA, Shreasth, Alturki A, Desa MK, Amir M, Ahmad AB, Ishak MK. A novel active cell balancing topology for serially connected Li-ion cells in the battery pack for electric vehicle applications. Scientific Reports. 2024 Aug 10;14(1):18600.
  13. Ashraf A, Ali B, Alsunjury MS, Goren H, Kilicoglu H, Hardan F, Tricoli P. Review of cell-balancing schemes for electric vehicle battery management systems. Energies. 2024 Mar 7;17(6):1271.
  14. Oloyede MO, Akpakwu GA, Myburgh HC, De Freitas A, Kunatsa T. A review on state-of-charge estimation methods, energy storage technologies and state-of-the-art simulators: recent developments and challenges. World Electric Vehicle Journal. 2024 Aug 23;15(9):381.
  15. Kelkar A, Dasari Y, Williamson SS. A comprehensive review of power electronics enabled active battery cell balancing for smart energy management. In2020 IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy (PESGRE2020) 2020 Jan 2 (pp. 1-6). IEEE.I
  16. Itagi AR, Kallimani R, Pai K, Iyer S, López OL, Mutagekar S. Cell Balancing Paradigms: Advanced Types, Algorithms, and Optimization Frameworks. arXiv preprint arXiv:2411.05478. 2024 Nov 8.
  17. Shreasth, Ooi CA, Khan N, Desa MK, Ishak MK, Ammar K. A novel active lithium-ion cell balancing method based on charging and discharging state of power in electric vehicles. Scientific Reports. 2025 May 6;15(1):15764.
  18. Shan R, Wang Y, Guo S, Cui Y, Zhao L, Li J, Wang Z. From Empirical Measurements to AI Fusion—A Holistic Review of SOH Estimation Techniques for Lithium-Ion Batteries in Electric and Hybrid Vehicles. Energies. 2025 Jul 4;18(13):3542.
  19. Liu K, Gao Y, Zhu C, Li K, Fei M, Peng C, Zhang X, Han QL. Electrochemical modeling and parameterization towards control-oriented management of lithium-ion batteries. Control Engineering Practice. 2022 Jul 1;124:105176.

Ahead of Print Subscription Review Article
Volume 16
02
Received 10/06/2026
Accepted 22/06/2026
Published 25/06/2026
Publication Time 15 Days


Login


My IP

PlumX Metrics