Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter July 27, 2020

A cost effective accumulator management system for electric vehicles

  • Suchitra D EMAIL logo , Rajarajeswari R EMAIL logo and Dhruv Singh Bhati


An accumulator or battery is an energy storage cramped in an adaptable stockade. Lithium-ion batteries are commonly used in hybrid electric vehicles (HEV) and battery operated electric vehicles (BOEV) due to its eco-friendliness and increased efficiency. To maintain lithium batteries in the safe operating region and also to perform tasks like cell balancing, preventing thermal runaway, maintain the state of health, an effective battery management system (BMS) is required. The BMS should also communicate effectively between host devices and battery packs. This paper proposes a reliable, modular and cost-efficient BMS, which will emanate an alert when a fault occurs and thus preventing the battery from damage. An efficient control strategy has been proposed for charging and discharging of the battery pack. The thermal analysis of the lithium-ion battery used in this work is simulated using battery design studio (BDS) with the inclusion of a self-discharging effect. The proposed hardware setup also provides a provision for on-board diagnosis (OBD) and logging in the accumulator management system (AMS) to constantly monitor the cell parameters like voltage, current, and temperature. The live data display of AMS working is also shown during abnormal and normal conditions. Also, an attempt is made to use the design of proposed AMS for HEV.

Corresponding authors: Suchitra D and Rajarajeswari R, Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamilnadu, India, E-mail: and

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: No funding received for this research.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.


1. Cheng, KWE, Divakar, BP, Wu, H, Ding, K, Ho Fai, H. Battery-management system (BMS) and SOC development for electrical vehicles. IEEE Trans Vehicle Technol 2011;60:6–11. in Google Scholar

2. Tremblay, O, Dessaint, LA, Dekkiche, AIA. Generic battery model for the dynamic simulation of hybrid electric vehicles. In: Proceedings of IEEE Vehicle Power and Propulsion Conference (VPPC 2007), Arlington, TX, USA, 9–12 September 2014, 14–20.10.1109/VPPC.2007.4544139Search in Google Scholar

3. Rahimi-Eichi, H, Ojha, U, Baronti, F, Chow, M-Y. Battery management system: an overview of its application in the smart grid and electric vehicles. IEEE Ind Electro M 2013;7:4–16. in Google Scholar

4. Xing, Y, Ma, WME, Tsui, LK, Pecht, M. Battery management systems in electric and hybrid vehicles. Energies 2011;4:1840–57. in Google Scholar

5. Stuart, T, Fang, F, Wang, X, Ashtiani, C, Pesaran, A. A modular battery management system for HEVs. SAE Technical Paper; 2002. in Google Scholar

6. Velho, R, Beirão, M, Rosário Calado, Md, Pombo, J, Fermeiro, J, Mariano, S. Management system for large Li-ion battery packs with a new adaptive multistage charging method. Energies 2017;10:605. in Google Scholar

7. Meissner, E, Richter, G. Battery monitoring and electrical energy management precondition for future vehicle electric power systems. J Power Sources 2003;116:79–98. in Google Scholar

8. Goals for advanced batteries for EVs. Southfield, MI, USA: United States Council for Automotive Research LLC; 2009. Available from: [Accessed 4 Mar 2017].Search in Google Scholar

9. Fu, L, Zhu, C, Du, T. A new type battery management system for Li-ion cell packs. J Interdiscip Math 2017;20:6–7. in Google Scholar

10. Balagopal, B, Chow, M-Y. Effect of anode conductivity degradation on the Thevenin circuit model of lithium ion batteries. In: Industrial Electronics Society, IECON 2016-42nd Annual Conference of the IEEE; 2016.10.1109/IECON.2016.7793429Search in Google Scholar

11. Zhang, H, Chow, MY. Comprehensive dynamic battery modeling for PHEV applications. In Proceedings of IEEE in Power and Energy Society General Meeting, Minneapolis, MN, USA, 25–29 July 2010, 1–6.Search in Google Scholar

12. Prada, E, Di Domenico, D, Creff, Y, Sauvant-Moynot, V. Towards advanced BMS algorithms development for (P)HEV and EV by use of a physics-based model of Li-ion battery systems, Electric vehicle symposium and exhibition (EVS27), IEEE publisher; 2014.10.1109/EVS.2013.6914790Search in Google Scholar

13. Ausswamy kin, A, Plangklang, B. Design of real time battery management unit for PV-hybrid system by application of Coulomb counting method. Energy and Power Engineering 2014:06;186–93. in Google Scholar

14. Dong, Z, Long, X, Yijia, S, Jiayu, C. On-line remaining useful life prediction of lithium-ion batteries based on the optimized gray model GM (1,1). Batteries 2017;3:21. in Google Scholar

15. Liu, K, Kang, L, Qiao, P, Zhang, C. A brief review on key technologies in the battery management system of electric vehicles. Front Mech Eng 2019;14:47–64. in Google Scholar

16. Li, J, Han, Y, Zhou, S. Advances in battery manufacturing, services, and management systems. Hoboken: John Wiley-IEEE Press; 2016.10.1002/9781119060741Search in Google Scholar

17. Zhang, X, Lu, J, Yuan, S. A novel method for identification of lithium-ion battery equivalent circuit model parameters considering electrochemical properties. J Power Sources 2017;345:21–9. in Google Scholar

18. [Accessed Mar 2018].Search in Google Scholar

19. [Accessed Mar 2018].Search in Google Scholar

Received: 2019-10-13
Accepted: 2020-06-08
Published Online: 2020-07-27

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 6.2.2023 from
Scroll Up Arrow