Generic placeholder image

Recent Advances in Electrical & Electronic Engineering

Author(s): Jun Zhang, Feng Pan*, Yilin Ji, Jinli Li and Jicheng Yu

DOI: 10.2174/0123520965272311231004051135

DownloadDownload PDF Flyer Cite As
Active Equalization of Lithium Battery Pack with Adaptive Control based on DC Energy Conversion Circuit

Page: [828 - 836] Pages: 9

  • * (Excluding Mailing and Handling)

Abstract

Background: How to solve the inconsistency of battery pack is a key point to ensure reliable operation of electric vehicles. Battery equalization is an effective measure to address the inconsistency. Passive equalization method has poor efficiency and thermal management problems. Average voltage equalization method is only suitable for situations where there is a significant voltage difference between batteries. The SOC-based equalization method is relatively difficult and may inevitably lead to the accumulation of errors during the process.

Objective: In order to avoid the disadvantages of traditional control methods, a new control method is proposed to improve the accuracy and self-adaptation of active equalization, which is easy to be realized without online calculation.

Methods: Cascaded bidirectional Buck-boost circuit is adopted as the novel equalization topology. Based on fuzzy PID theory, an adaptive digital-analog hybrid control strategy based on fuzzy PID is proposed in this paper. Parameter design of the fuzzy PID controller is carried out. A battery equalization system based on cascaded bidirectional Buck-boost circuit is designed and developed. Experimental verification is conducted on relevant hardware platforms.

Results: An adaptive digital-analog hybrid control strategy based on fuzzy PID is proposed. Compared to passive equalization, this proposed method provides high efficiency. Regarding traditional voltage control, the method improves control reliability and flexibility. Compared to the average voltage equalization method, the approach needs less convergence time. Moreover, the control method is much easier to realize than the SOC-based equalization method.

Conclusion: By using the presented adaptive control based on DC energy conversion circuit, the degree of self-adaptation of the equalization process has been obtained as higher and the inconsistency as smaller.

[1]
Z. Xu, "Research on energy conservation and emission reduction effect and development path of new energy electric vehicle", In 3rd International Conference on Data Science and Business Analytics (ICDSBA), Istanbul, Turkey, 2019, pp. 448-450
[http://dx.doi.org/10.1109/ICDSBA48748.2019.00097]
[2]
Y. Liu, H. Chen, J. Gao, Y. Li, K. Dave, J. Chen, M. Federici, and G. Perricone, "Comparative analysis of non-exhaust airborne particles from electric and internal combustion engine vehicles", J. Hazard. Mater., vol. 420, p. 126626, 2021.
[http://dx.doi.org/10.1016/j.jhazmat.2021.126626] [PMID: 34273888]
[3]
Tabassum-Abbasi, "M. Premalatha, T. Abbasi, and S.A. Abbasi, “Wind energy: Increasing deployment, rising environmental concerns”", Renew. Sustain. Energy Rev., vol. 31, pp. 270-288, 2014.
[http://dx.doi.org/10.1016/j.rser.2013.11.019]
[4]
J. Dunn, M. Slattery, A. Kendall, H. Ambrose, and S. Shen, "Circularity of Lithium-Ion battery materials in electric vehicles", Environ. Sci. Technol., vol. 55, no. 8, pp. 5189-5198, 2021.
[http://dx.doi.org/10.1021/acs.est.0c07030] [PMID: 33764763]
[5]
X. Sun, H. Hao, P. Hartmann, Z. Liu, and F. Zhao, "Supply risks of lithium-ion battery materials: An entire supply chain estimation", Mater. Today Energy, vol. 14, p. 100347, 2019.
[http://dx.doi.org/10.1016/j.mtener.2019.100347]
[6]
M. Naguib, P. Kollmeyer, and A. Emadi, "Lithium-Ion battery pack robust state of charge estimation, cell inconsistency, and balancing", IEEE Access, vol. 9, pp. 50570-50582, 2021.
[http://dx.doi.org/10.1109/ACCESS.2021.3068776]
[7]
M. Chen, B. Zhang, and Y. Li, "Performance of inconsistency in lithium-ion battery packs for battery energy storage systems", In EEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), Hong Kong, China, 2014, pp. 1-5
[http://dx.doi.org/10.1109/APPEEC.2014.7066009]
[8]
J. Ouyang, P. Zhang, and S. Wang, "Active balancing charging module with continuous and controllable isolation for battery management system", In IEEE Electrical Design of Advanced Packaging and Systems Symposium (EDAPS), Haining, China, 2017, pp. 1-4
[http://dx.doi.org/10.1109/EDAPS.2017.8276991]
[9]
L.A. Perisoara, I.C. Guran, and D.C. Costache, "A passive battery management system for fast balancing of four LiFePO4 cells", In 24th International Symposium for Design and Technology in Electronic Packaging (SIITME), Iasi, Romania, 2018, pp. 390-393
[http://dx.doi.org/10.1109/SIITME.2018.8599258]
[10]
R. Li, Z. Wang, and J. Yu, "Dynamic parameter identification of mathematical model of Lithium-Ion battery based on least square method", In IEEE International Power Electronics and Application Conference and Exposition (PEAC), Shenzhen, China, 2018, pp. 1-5
[http://dx.doi.org/10.1109/PEAC.2018.8590489]
[11]
A. Mondal, A. Routray, and S. Puravankara, "On-line parameter identification and state of charge estimation of Li-ion battery", In IEEE 17th India Council International Conference (INDICON), New Delhi, India, 2020, pp. 1-7
[http://dx.doi.org/10.1109/INDICON49873.2020.9342215]
[12]
X. Liu, Y. Jin, and S. Zeng, "Online identification of power battery parameters for electric vehicles using a decoupling multiple forgetting factors recursive least squares method", CSEE J. Power Energy Syst., vol. 6, no. 3, pp. 735-742, 2020.
[13]
P. Shrivastava, T.K. Soon, and M. Yamani Binidris, "Lithium-ion battery model parameter identification using modified adaptive forgetting factor-based recursive least square algorithm", In IEEE 12th Energy Conversion Congress & Exposition - Asia (ECCEAsia), Singapore, Singapore, 2021, pp. 2169-2174
[http://dx.doi.org/10.1109/ECCE-Asia49820.2021.9479079]
[14]
Z. Chen, M. Lv, and J. Bi, "Energy management of plug-in hybrid electric vehicle based on simulated annealing algorithm", In Chinese Automation Congress (CAC), Jinan, China, 2017, pp. 526-529
[http://dx.doi.org/10.1109/CAC.2017.8242824]
[15]
W. Peng, Z. Yang, and C. Liu, "An improved PSO algorithm for battery parameters identification optimization based on Thevenin battery model", In 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), Nanjing, China, 2018, pp. 295-29
[http://dx.doi.org/10.1109/CCIS.2018.8691341]
[16]
T. Kalogiannis, M.S. Hosen, and J. Jaguemont, "Static electric equivalent circuit of commercial Lithium-Ion battery cells using genetic algorithms", In IEEE Vehicle Power and Propulsion Conference (VPPC), Hanoi, Vietnam, 2019, pp. 1-6
[http://dx.doi.org/10.1109/VPPC46532.2019.8952530]
[17]
F. Lotfi, S. Ziapour, F. Faraji, and H.D. Taghirad, "A switched SDRE filter for state of charge estimation of lithium-ion batteries", Int. J. Electr. Power Energy Syst., vol. 117, p. 105666, 2020.
[http://dx.doi.org/10.1016/j.ijepes.2019.105666]
[18]
M. Feizi, and R. Beiranvand, "Simulation of a high power self-equalized battery charger using voltage multiplier and phase-shifted full bridge converter for Lithium-Ion batteries", In 11th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC), Tehran, Iran,, 2020, pp. 1-6
[http://dx.doi.org/10.1109/PEDSTC49159.2020.9088454]
[19]
W. Sun, Y. Li, L. Liu, and R. Mai, "A switched‐capacitor battery equalization method for improving balancing speed", IET Electr. Power Appl., vol. 15, no. 5, pp. 555-569, 2021.
[http://dx.doi.org/10.1049/elp2.12045]
[20]
S. Jinlei, L. Wei, T. Chuanyu, W. Tianru, J. Tao, and T. Yong, "A novel active equalization method for series-connected battery packs based on clustering analysis with genetic algorithm", IEEE Trans. Power Electron., vol. 36, no. 7, pp. 7853-7865, 2021.
[http://dx.doi.org/10.1109/TPEL.2021.3049166]
[21]
X.L. Bian, Z.G. Wei, and W.H. Li, "State-of-health estimation of Lithium-Ion batteries by fusing an open circuit voltage model and incremental capacity analysis", IEEE Trans. Power Electron., vol. 37, no. 2, pp. 2226-2236, 2022.
[22]
C-S. Moo, T-H. Wu, and C-H. Hou, "Balanced discharging of power bank with buck-boost battery power modules", In International Power Electronics Conference (IPEC-Hiroshima 2014 - ECCE ASIA), Hiroshima, Japan, 2014, pp. 1796-1800
[http://dx.doi.org/10.1109/IPEC.2014.6869827]
[23]
D. Saji, P.S. Babu, and K. Ilango, "SoC Estimation of Lithium Ion battery using combined coulomb counting and fuzzy logic method", In 4th International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT), Bangalore, India, 2019, pp. 948-952
[http://dx.doi.org/10.1109/RTEICT46194.2019.9016956]
[24]
D.A. Martinez, J.D. Poveda, and D. Montenegro, "Li-Ion battery management system based in fuzzy logic for improving electric vehicle autonomy", In IEEE Workshop on Power Electronics and Power Quality Applications (PEPQA), Bogota, Colombia, 2017, pp. 1-6
[http://dx.doi.org/10.1109/PEPQA.2017.7981677]
[25]
J. Bakalarczyk, "Charging of PV battery at constant current mode by using fuzzy logic control", In 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), Lviv, Ukraine, 2017, pp. 397-400
[http://dx.doi.org/10.1109/STC-CSIT.2017.8098814]
[26]
K.F. Hussein, I. Abdel-qader, and M.K. Hussain, "Hybrid fuzzy PID controller for buck-boost converter in solar energy-battery systems", In IEEE International Conference on Electro/Information Technology (EIT), Dekalb, IL, USA, 2015, pp. 070-075
[http://dx.doi.org/10.1109/EIT.2015.7293323]
[27]
H. Wang, F. Zhang, and P. Liu, "Test system design of Lithium battery based on fuzzy self-tuning PID control", In 8th International Conference on Future Generation Communication and Networking, Hainan, China, 2014, pp. 96-99
[http://dx.doi.org/10.1109/FGCN.2014.31]
[28]
G. Parise, L. Martirano, and M. Kermani, "Designing a power control strategy in a microgrid using PID/fuzzy controller based on battery energy storage", In IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Milan, Italy, 2017, pp. 1-5
[29]
A. Khosla, S. Kumar, and K.K. Aggarwal, "Fuzzy controller for rapid nickel-cadmium batteries charger through adaptive neuro-fuzzy inference system (ANFIS) architecture", In 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003, Chicago, IL, USA, 2003, pp. 540-544
[30]
O. Ouramdane, E. Elbouchikhi, Y. Amirat, and E. Sedgh Gooya, "Optimal sizing and energy management of microgrids with vehicle-to-grid technology: A critical review and future trends", Energies, vol. 14, no. 14, p. 4166, 2021.
[http://dx.doi.org/10.3390/en14144166]
[31]
G. Navarro, J. Nájera, J. Torres, M. Blanco, M. Santos, and M. Lafoz, "Development and ex-perimental validation of a supercapacitor frequency domain model for industrial energy applications considering dynamic behaviour at high frequencies", Energies, vol. 13, no. 5, p. 1156, 2020.
[http://dx.doi.org/10.3390/en13051156]
[32]
A. Morandi, A. Lampasi, A. Cocchi, F. Gherdovich, U. Melaccio, P.L. Ribani, C. Rossi, and F. Soavi, "Characterization and model parameters of large commercial supercapacitor cells", IEEE Access, vol. 9, pp. 20376-20390, 2021.
[http://dx.doi.org/10.1109/ACCESS.2021.3053626]
[33]
Y. Zhao, W. Xie, Z. Fang, and S. Liu, "A parameters identification method of the equivalent circuit model of the supercapacitor cell module based on segmentation optimization", IEEE Access, vol. 8, p. 1, 2020.
[http://dx.doi.org/10.1109/ACCESS.2020.2993285]
[34]
B. SanthiBhushan, M.S. Khan, V.K. Bohat, A. Srivastava, and S. Khan, "Quantum capacitance estimations of pyrrolic-rich graphene for supercapacitor electrodes", IEEE Trans. Nanotechnol., vol. 17, no. 2, pp. 205-211, 2018.
[http://dx.doi.org/10.1109/TNANO.2017.2786715]
[35]
Y. Parvini, A. Vahidi, and S.A. Fayazi, "Heuristic versus optimal charging of supercapacitors, Lithium-Ion, and Lead-Acid batteries: an efficiency point of view", IEEE Trans. Control Syst. Technol., vol. 26, no. 1, pp. 167-180, 2018.
[http://dx.doi.org/10.1109/TCST.2017.2665540]