Optimal algorithms for the charge equalisation controller of series connected lithium-ion battery cells in electric vehicle applications

Optimal algorithms for the charge equalisation controller of series connected lithium-ion battery cells in electric vehicle applications

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Electrical Systems in Transportation — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A charge equalisation controller (CEC) was developed for continuously monitoring individual battery cells and equalising the charge or voltage levels of all cells in a series pack. A charge equalisation control algorithm was developed to equalise undercharged, overcharged, and unprotected cells through the use of a bidirectional fly-back converter. The equalisation involves charging and discharging by employing constant current–constant voltage and discontinuous current mode proportional–integral (PI) control techniques. Particle swarm optimisation is applied to optimising the PI controller parameters that generate the regulated pulse width modulation switching signal for the converter. A CEC model was applied to 90 lithium-ion battery cells (nominally 15.5 Ah and 3.7 V each) connected in series. The results showed that the developed CEC model performed well at equalising both undercharged and overcharged cells with ∼92% efficiency and equalised every cell within the safe operation range of 3.73–3.87 V. The developed system realises excellent equalisation speed, a simple design and efficiency with low power loss. Thus, the CEC model has great potential for implementation in real-world electric vehicle energy storage systems.


    1. 1)
      • 1. Fathabadi, H.: ‘Lithium-ion battery equipped with AC feature for using in electric/hybrid vehicles’, IET Electr. Syst. Transp., 2015, 5, (3), pp. 95102.
    2. 2)
      • 2. Hannan, M.A., Hoque, M.M., Mohamed, A., et al: ‘Review of energy storage systems for electric vehicle applications: issues and challenges’, Renew. Sustain. Energy Rev., 2017, 69, pp. 771789.
    3. 3)
      • 3. Tannahill, V.R., Sutanto, D., Muttaqi, K.M., et al: ‘Future vision for reduction of range anxiety by using an improved state of charge estimation algorithm for electric vehicle batteries implemented with low-cost microcontrollers’, IET Electr. Syst. Transp., 2015, 5, (1), pp. 2432.
    4. 4)
      • 4. Oakley, J., McHenry, M.P., Bräunl, T.: ‘Limitations of testing standards for battery electric vehicles: accessories, energy usage, and range’, IET Electr. Syst. Transp., 2016, 6, (3), pp. 215221.
    5. 5)
      • 5. Cheng, M.W., Lee, Y.S., Liu, M., et al: ‘State-of-charge estimation with aging effect and correction for lithium-ion battery’, IET Electr. Syst. Transp., 2015, 5, (2), pp. 7076.
    6. 6)
      • 6. Lehner, S., Baumhöfer, T., Sauer, D.U.: ‘Disparity in initial and lifetime parameters of lithium-ion cells’, IET Electr. Syst. Transp., 2016, 6, (1), pp. 3440.
    7. 7)
      • 7. Feng, F., Lu, R., Wei, G., et al: ‘Identification and analysis of model parameters used for LiFePO4 cells series battery pack at various ambient temperature’, IET Electr. Syst. Transp., 2016, 6, (2), pp. 5055.
    8. 8)
      • 8. Hoque, M.M., Hannan, M.A., Mohamed, A.: ‘Charging and discharging model of lithium-ion battery for charge equalization control using particle swarm optimization algorithm’, J. Renew. Sustain. Energy, 2016, 8, (065701), pp. 116.
    9. 9)
      • 9. Baronti, F., Roncella, R., Saletti, R.: ‘Performance comparison of active balancing techniques for lithium-ion batteries’, J. Power Sources, 2014, 267, pp. 603609.
    10. 10)
      • 10. Lin, J.C.: ‘Development of a two-staged balancing scheme for charging lithium iron cells in series’, IET Electr. Syst. Transp., 2016, 6, (3), pp. 145152.
    11. 11)
      • 11. Park, H.S., Kim, C.E., Kim, C.H., et al: ‘A modularized charge equalizer for an HEV lithium-ion battery string’, IEEE Trans. Ind. Electron., 2009, 56, (5), pp. 14641476.
    12. 12)
      • 12. Kim, M.Y., Kim, C.H., Kim, J.H., et al: ‘A chain structure of switched capacitor for improved cell balancing speed of lithium-ion batteries’, IEEE Trans. Ind. Electron., 2014, 61, (8), pp. 39893999.
    13. 13)
      • 13. Li, S., Mi, C., Zhang, M.: ‘A high-efficiency active battery-balancing circuit using multiwinding transformer’, IEEE Trans. Ind. Appl., 2013, 49, pp. 198207.
    14. 14)
      • 14. Ling, R., Dan, Q., Wang, L.: ‘Energy bus-based equalization scheme with bidirectional isolated Cuk equalizer for series connected battery strings’. Proc. IEEE Applied Power Electronics Conf. and Exposition (APEC), North Carolina, USA, March 2015, pp. 33353340.
    15. 15)
      • 15. Wu, T.H., Chang, C.S., Moo, C.S.: ‘A charging scenario for parallel buck-boost battery power modules with full power utilization and charge equalization’. Proc. IEEE Int. Conf. Industrial Technology (ICIT), Seville, Spain, March 2015, pp. 860865.
    16. 16)
      • 16. Lee, K.M., Chung, Y.C., Sung, C.H., et al: ‘Active cell balancing of Li-ion batteries using LC series resonant circuit’, IEEE Trans. Ind. Electron., 2015, 62, (9), pp. 54915501.
    17. 17)
      • 17. Imtiaz, M., Khan, F.H.: ‘Time shared flyback converter based regenerative cell balancing technique for series connected Li-ion battery strings’, IEEE Trans. Power Electron., 2013, 28, (12), pp. 59605975.
    18. 18)
      • 18. Chatzinikolaou, E., Rogers, D.J.: ‘Cell SoC balancing using a cascaded full-bridge multilevel converter in battery energy storage systems’, IEEE Trans. Ind. Electron., 2016, 63, (9), pp. 53945402.
    19. 19)
      • 19. Wang, Y., Zhang, C., Chen, Z., et al: ‘A novel active equalization method for lithium-ion batteries in electric vehicles’, Appl. Energy, 2015, 145, pp. 3642.
    20. 20)
      • 20. Wei, J., Dong, G., Chen, Z., et al: ‘System state estimation and optimal energy control framework for multicell lithium-ion battery system’, Appl. Energy, 2017, 187, pp. 3749.
    21. 21)
      • 21. Wang, Y., Zhang, C., Chen, Z.: ‘An adaptive remaining energy prediction approach for lithium-ion batteries in electric vehicles’, J. Power Sources, 2016, 305, pp. 8088.
    22. 22)
      • 22. Yu, S., Nguyen, M.Q., Choi, W.: ‘A novel soft-switching battery charge/discharge converter with the zero voltage discharge function’, IEEE Trans. Power Electron., 2016, 31, pp. 50675078.
    23. 23)
      • 23. Chao, P.C.P., Chen, W.D., Wu, R.H.: ‘A battery charge controller realized by a flyback converter with digital primary side regulation for mobile phones’, Microsyst. Technol., 2014, 20, pp. 16891703.
    24. 24)
      • 24. Paul, C.P.C., Chen, W.D., Cheng, C.W.: ‘A fast charging algorithm for an intelligent PV system with capability of on-line temperature compensation’, Microsyst. Technol., 2013, 19, pp. 12891306.
    25. 25)
      • 25. Chen, L.R., Chu, N.Y., Wang, C.S., et al: ‘Design of a reflex based bidirectional converter with the energy recovery function’, IEEE Trans. Ind. Electron., 2008, 55, pp. 30223029.
    26. 26)
      • 26. Tremblay, O., Dessaint, L.A., Dekkiche, A.I.: ‘A generic battery model for the dynamic simulation of hybrid electric vehicles’. Proc. IEEE Vehicle Power and Propulsion Conf. (VPPC), Arlington, TX, USA, September 2007, pp. 284289.
    27. 27)
      • 27. Hu, X., Li, S.E., Yang, Y.: ‘Advanced machine learning approach for lithium-ion battery state estimation in electric vehicles’, IEEE Trans. Transport. Electrific., 2016, 2, (2), pp. 140149.
    28. 28)
      • 28. Malysz, P., Gu, R., Ye, J., et al: ‘State-of-charge and state-of-health estimation with state constraints and current sensor bias correction for electrified powertrain vehicle batteries’, IET Electr. Syst. Transp., 2016, 6, (2), pp. 136144.
    29. 29)
      • 29. Pei, L., Lu, R., Zhu, C.: ‘Relaxation model of the open-circuit voltage for state-of-charge estimation in lithium-ion batteries’, IET Electr. Syst. Transp., 2013, 3, (4), pp. 112117.
    30. 30)
      • 30. Chen, Z., Fu, Y., Mi, C.C.: ‘State of charge estimation of lithium-ion batteries in electric drive vehicles using extended Kalman filtering’, IEEE Trans. Veh. Technol., 2013, 62, (3), pp. 10201030.
    31. 31)
      • 31. El-Din, M.S., Abdel-Hafez, M.F., Hussein, A.A.: ‘Enhancement in Li-ion battery cell state-of-charge estimation under uncertain model statistics’, IEEE Trans. Veh. Technol., 2016, 65, (6), pp. 46084618.
    32. 32)
      • 32. Tang, X., Wang, Y., Chen, Z.: ‘A method for state-of-charge estimation of LiFePO4 batteries based on a dual-circuit state observer’, J. Power Sources, 2015, 296, pp. 2329.
    33. 33)
      • 33. Hoque, M.M., Hannan, M.A., Mohamed, A.: ‘Voltage equalization control algorithm for monitoring and balancing of series connected lithium-ion battery’, J. Renew. Sustain. Energy, 2016, 8, (025703), pp. 115.
    34. 34)
      • 34. Kazimierczuk, M.K.: ‘Flyback PWM DC–DC converter’, in ‘Pulse-width modulated DC–DC power converters’ (John Wiley & Sons, UK, 2008, 1st edn.), pp. 189237.
    35. 35)
      • 35. Yang, Y.P., Shih, Y.C., Chen, J.M.: ‘Real-time torque-distribution strategy for a pure electric vehicle with multiple traction motors by particle swarm optimisation’, IET Electr. Syst. Transp., 2016, 6, (2), pp. 7687.
    36. 36)
      • 36. Rahman, M.A., Anwar, S., Izadian, A.: ‘Electrochemical model parameter identification of a lithium-ion battery using particle swarm optimization method’, J. Power Sources, 2016, 307, pp. 8697.

Related content

This is a required field
Please enter a valid email address