全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Principles and Research Progress of Lithium Battery Management Systems for New Energy Vehicles

DOI: 10.4236/jpee.2026.148001, PP. 1-21

Keywords: Lithium-Ion Battery, Battery Management System, New Energy Vehicles

Full-Text   Cite this paper   Add to My Lib

Abstract:

Lithium-ion batteries have become the cornerstone of New Energy Vehicles (NEVs) owing to their high energy density, long cycle life, and high energy efficiency. Nevertheless, there is an increasing need for the integration of a complex battery functionality, safety and longevity. This article critically evaluates recent advances in the principles, developmental trends, and research progress of lithium battery management systems developed for NEV applications. The paper examines the basics of battery types, BMS architecture, state estimation methods, safety features, thermal control, and the next generation technology, including AI-based diagnostics and wireless technology. Also, the second-life applications, circular economy strategies and policy standardization are given special attention. The review highlights several important challenges and opportunities, including real time state estimation, small-scale hardware integration, and constraints in high-speed charging, as well as opportunities in solid-state BMS, federated learning, and cyber-physical simulation platforms. Overall, the article offers a perspective on the future of intelligent, safe and sustainable battery systems in academia and industry.

References

[1]  Liu, W., Placke, T. and Chau, K.T. (2022) Overview of Batteries and Battery Management for Electric Vehicles. Energy Reports, 8, 4058-4084.
https://doi.org/10.1016/j.egyr.2022.03.016
[2]  Veza, I., Syaifuddin, M., Idris, M., Herawan, S.G., Yusuf, A.A. and Fattah, I.M.R. (2024) Electric Vehicle (EV) Review: Bibliometric Analysis of Electric Vehicle Trend, Policy, Lithium-Ion Battery, Battery Management, Charging Infrastructure, Smart Charging, and Electric Vehicle-to-Everything (V2X). Energies, 17, Article 3786.
https://doi.org/10.3390/en17153786
[3]  Hu, X., Zou, C., Zhang, C. and Li, Y. (2023) Technological Developments in Batteries: A Survey of Principal Roles, Types, and Management Needs. IEEE Power and Energy Magazine, 21, 52-63.
https://doi.org/10.1109/mpae.2023.10083081
[4]  Pramuanjaroenkij, A. and Kaka?, S. (2023) The Fuel Cell Electric Vehicles: The Highlight Review. International Journal of Hydrogen Energy, 48, 9401-9425.
https://doi.org/10.1016/j.ijhydene.2022.11.103
[5]  Manas, M., Yadav, R. and Dubey, R.K. (2023) Designing a Battery Management System for Electric Vehicles: A Congregated Approach. Journal of Energy Storage, 74, Article 109439.
https://doi.org/10.1016/j.est.2023.109439
[6]  Jacobson, M.Z. (2009) Review of Solutions to Global Warming, Air Pollution, and Energy Security. Energy Environ. Sci., 2, 148-173.
https://doi.org/10.1039/b809990c
[7]  Zhang, X., Li, Z., Luo, L., Fan, Y. and Du, Z. (2022) A Review on Thermal Management of Lithium-Ion Batteries for Electric Vehicles. Energy, 238, Article 121652.
https://doi.org/10.1016/j.energy.2021.121652
[8]  Cen, J. and Jiang, F. (2020) Li-Ion Power Battery Temperature Control by a Battery Thermal Management and Vehicle Cabin Air Conditioning Integrated System. Energy for Sustainable Development, 57, 141-148.
https://doi.org/10.1016/j.esd.2020.06.004
[9]  Lu, Z., Yu, X.L., Wei, L.C., Cao, F., Zhang, L.Y., Meng, X.Z., et al. (2019) A Comprehensive Experimental Study on Temperature-Dependent Performance of Lithium-Ion Battery. Applied Thermal Engineering, 158, Article 113800.
https://doi.org/10.1016/j.applthermaleng.2019.113800
[10]  Yang, R., Xiong, R., He, H., Mu, H. and Wang, C. (2017) A Novel Method on Estimating the Degradation and State of Charge of Lithium-Ion Batteries Used for Electrical Vehicles. Applied Energy, 207, 336-345.
https://doi.org/10.1016/j.apenergy.2017.05.183
[11]  Qiu, Y. and Jiang, F. (2022) A Review on Passive and Active Strategies of Enhancing the Safety of Lithium-Ion Batteries. International Journal of Heat and Mass Transfer, 184, Article 122288.
https://doi.org/10.1016/j.ijheatmasstransfer.2021.122288
[12]  Liang, K., Wang, M., Gao, C., Dong, B., Feng, C., Zhou, X., et al. (2021) Advances and Challenges of Integrated Thermal Management Technologies for Pure Electric Vehicles. Sustainable Energy Technologies and Assessments, 46, Article 101319.
https://doi.org/10.1016/j.seta.2021.101319
[13]  Hannan, M.A., Lipu, M.S.H., Hussain, A. and 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, 78, 834-854.
https://doi.org/10.1016/j.rser.2017.05.001
[14]  Xiong, R., Sun, W., Yu, Q. and Sun, F. (2020) Research Progress, Challenges and Prospects of Fault Diagnosis on Battery System of Electric Vehicles. Applied Energy, 279, Article 115855.
https://doi.org/10.1016/j.apenergy.2020.115855
[15]  Smith, J., Singh, R., Hinterberger, M. and Mochizuki, M. (2018) Battery Thermal Management System for Electric Vehicle Using Heat Pipes. International Journal of Thermal Sciences, 134, 517-529.
https://doi.org/10.1016/j.ijthermalsci.2018.08.022
[16]  Li, W., Xiao, M., Peng, X., Garg, A. and Gao, L. (2019) A Surrogate Thermal Modeling and Parametric Optimization of Battery Pack with Air Cooling for EVs. Applied Thermal Engineering, 147, 90-100.
https://doi.org/10.1016/j.applthermaleng.2018.10.060
[17]  Zhou, H., Zhou, F., Zhang, Q., Wang, Q. and Song, Z. (2019) Thermal Management of Cylindrical Lithium-Ion Battery Based on a Liquid Cooling Method with Half-Helical Duct. Applied Thermal Engineering, 162, Article 114257.
https://doi.org/10.1016/j.applthermaleng.2019.114257
[18]  Tran, T., Harmand, S., Desmet, B. and Filangi, S. (2014) Experimental Investigation on the Feasibility of Heat Pipe Cooling for HEV/EV Lithium-Ion Battery. Applied Thermal Engineering, 63, 551-558.
https://doi.org/10.1016/j.applthermaleng.2013.11.048
[19]  Gan, Y., He, L., Liang, J., Tan, M., Xiong, T. and Li, Y. (2020) A Numerical Study on the Performance of a Thermal Management System for a Battery Pack with Cylindrical Cells Based on Heat Pipes. Applied Thermal Engineering, 179, Article 115740.
https://doi.org/10.1016/j.applthermaleng.2020.115740
[20]  Lyu, Y., Siddique, A.R.M., Majid, S.H., Biglarbegian, M., Gadsden, S.A. and Mahmud, S. (2019) Electric Vehicle Battery Thermal Management System with Thermoelectric Cooling. Energy Reports, 5, 822-827.
https://doi.org/10.1016/j.egyr.2019.06.016
[21]  Zhao, C., Sousa, A.C.M. and Jiang, F. (2019) Minimization of Thermal Non-Uniformity in Lithium-Ion Battery Pack Cooled by Channeled Liquid Flow. International Journal of Heat and Mass Transfer, 129, 660-670.
https://doi.org/10.1016/j.ijheatmasstransfer.2018.10.017
[22]  Li, W., Garg, A., Xiao, M. and Gao, L. (2020) Optimization for Liquid Cooling Cylindrical Battery Thermal Management System Based on Gaussian Process Model. Journal of Thermal Science and Engineering Applications, 13, Article 021015.
https://doi.org/10.1115/1.4047526
[23]  Wei, Y. and Agelin-Chaab, M. (2018) Experimental Investigation of a Novel Hybrid Cooling Method for Lithium-Ion Batteries. Applied Thermal Engineering, 136, 375-387.
https://doi.org/10.1016/j.applthermaleng.2018.03.024
[24]  Yuan, X., Tang, A., Shan, C., Liu, Z. and Li, J. (2020) Experimental Investigation on Thermal Performance of a Battery Liquid Cooling Structure Coupled with Heat Pipe. Journal of Energy Storage, 32, Article 101984.
https://doi.org/10.1016/j.est.2020.101984
[25]  Hu, X., Jiang, H., Feng, F. and Liu, B. (2020) An Enhanced Multi-State Estimation Hierarchy for Advanced Lithium-Ion Battery Management. Applied Energy, 257, Article 114019.
https://doi.org/10.1016/j.apenergy.2019.114019
[26]  Schmuch, R., Wagner, R., H?rpel, G., Placke, T. and Winter, M. (2018) Performance and Cost of Materials for Lithium-Based Rechargeable Automotive Batteries. Nature Energy, 3, 267-278.
https://doi.org/10.1038/s41560-018-0107-2
[27]  Janek, J. and Zeier, W.G. (2016) A Solid Future for Battery Development. Nature Energy, 1, Article No. 16141.
https://doi.org/10.1038/nenergy.2016.141
[28]  Ali, M.U., Zafar, A., Nengroo, S.H., Hussain, S., Junaid Alvi, M. and Kim, H. (2019) Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation. Energies, 12, Article 446.
https://doi.org/10.3390/en12030446
[29]  Ng, M., Zhao, J., Yan, Q., Conduit, G.J. and Seh, Z.W. (2020) Predicting the State of Charge and Health of Batteries Using Data-Driven Machine Learning. Nature Machine Intelligence, 2, 161-170.
https://doi.org/10.1038/s42256-020-0156-7
[30]  Aghmadi, A., Hussein, H. and Mohammed, O.A. (2023) Enhancing Energy Management System for a Hybrid Wind Solar Battery Based Standalone Microgrid. 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Madrid, 6-9 June 2023, 1-6.
https://doi.org/10.1109/eeeic/icpseurope57605.2023.10194769
[31]  Abdelrahman, M.S., Hussein, H. and Mohammed, O.A. (2023) Rule-Based Power and Energy Management System for Shipboard Microgrid with HESS to Mitigate Propulsion and Pulsed Load Fluctuations. 2023 IEEE Green Technologies Conference (GreenTech), Denver, 19-21 April 2023, 224-228.
https://doi.org/10.1109/greentech56823.2023.10173813
[32]  Zhang, J., Zhang, L., Sun, F. and Wang, Z. (2018) An Overview on Thermal Safety Issues of Lithium-Ion Batteries for Electric Vehicle Application. IEEE Access, 6, 23848-23863.
https://doi.org/10.1109/access.2018.2824838
[33]  Gabbar, H., Othman, A. and Abdussami, M. (2021) Review of Battery Management Systems (BMS) Development and Industrial Standards. Technologies, 9, Article 28.
https://doi.org/10.3390/technologies9020028
[34]  Zhang, R., Xia, B., Li, B., Cao, L., Lai, Y., Zheng, W., et al. (2018) State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles. Energies, 11, Article 1820.
https://doi.org/10.3390/en11071820
[35]  Sanguesa, J.A., Torres-Sanz, V., Garrido, P., Martinez, F.J. and Marquez-Barja, J.M. (2021) A Review on Electric Vehicles: Technologies and Challenges. Smart Cities, 4, 372-404.
https://doi.org/10.3390/smartcities4010022
[36]  Chemali, E., Kollmeyer, P.J., Preindl, M. and Emadi, A. (2018) State-of-Charge Estimation of Li-Ion Batteries Using Deep Neural Networks: A Machine Learning Approach. Journal of Power Sources, 400, 242-255.
https://doi.org/10.1016/j.jpowsour.2018.06.104
[37]  Ghaeminezhad, N., Ouyang, Q., Wei, J., Xue, Y. and Wang, Z. (2023) Review on State of Charge Estimation Techniques of Lithium-Ion Batteries: A Control-Oriented Approach. Journal of Energy Storage, 72, Article 108707.
https://doi.org/10.1016/j.est.2023.108707
[38]  Xi, Z., Wang, R., Fu, Y. and Mi, C. (2022) Accurate and Reliable State of Charge Estimation of Lithium Ion Batteries Using Time-Delayed Recurrent Neural Networks through the Identification of Overexcited Neurons. Applied Energy, 305, Article 117962.
https://doi.org/10.1016/j.apenergy.2021.117962
[39]  Tete, P.R., Gupta, M.M. and Joshi, S.S. (2021) Developments in Battery Thermal Management Systems for Electric Vehicles: A Technical Review. Journal of Energy Storage, 35, Article 102255.
https://doi.org/10.1016/j.est.2021.102255
[40]  Kummitha, O.R. (2023) Thermal Cooling of Li-Ion Cylindrical Cells Battery Module with Baffles Arrangement For Airflow Cooling Numerical Analysis. Journal of Energy Storage, 59, Article 106474.
https://doi.org/10.1016/j.est.2022.106474
[41]  Ren, D., Hsu, H., Li, R., Feng, X., Guo, D., Han, X., et al. (2019) A Comparative Investigation of Aging Effects on Thermal Runaway Behavior of Lithium-Ion Batteries. eTransportation, 2, Article 100034.
https://doi.org/10.1016/j.etran.2019.100034
[42]  Lin, C., Burggr?f, P., Liu, L., Adlon, T., Mueller, K., Beyer, M., et al. (2023) Deep-Dive Analysis of the Latest Lithium-Ion Battery Safety Testing Standards and Regulations in Germany and China. Renewable and Sustainable Energy Reviews, 173, Article 113077.
https://doi.org/10.1016/j.rser.2022.113077
[43]  Yu, Q., Nie, Y., Peng, S., Miao, Y., Zhai, C., Zhang, R., et al. (2023) Evaluation of the Safety Standards System of Power Batteries for Electric Vehicles in China. Applied Energy, 349, Article 121674.
https://doi.org/10.1016/j.apenergy.2023.121674
[44]  Habib, A.K.M.A., Hasan, M.K., Issa, G.F., Singh, D., Islam, S. and Ghazal, T.M. (2023) Lithium-Ion Battery Management System for Electric Vehicles: Constraints, Challenges, and Recommendations. Batteries, 9, Article 152.
https://doi.org/10.3390/batteries9030152
[45]  Park, S., Jang, D.S., Lee, D., Hong, S.H. and Kim, Y. (2019) Simulation on Cooling Performance Characteristics of a Refrigerant-Cooled Active Thermal Management System for Lithium Ion Batteries. International Journal of Heat and Mass Transfer, 135, 131-141.
https://doi.org/10.1016/j.ijheatmasstransfer.2019.01.109
[46]  Zhou, R., Chen, Y., Zhang, J. and Guo, P. (2023) Research Progress in Liquid Cooling Technologies to Enhance the Thermal Management of LIBs. Materials Advances, 4, 4011-4040.
https://doi.org/10.1039/D3MA00299C
[47]  Alkhulaifi, Y.M., Qasem, N.A.A. and Zubair, S.M. (2019) Improving the Performance of Thermal Management System for Electric and Hybrid Electric Vehicles by Adding an Ejector. Energy Conversion and Management, 201, Article 112133.
https://doi.org/10.1016/j.enconman.2019.112133
[48]  Severson, K.A., Attia, P.M., Jin, N., Perkins, N., Jiang, B., Yang, Z., et al. (2019) Data-Driven Prediction of Battery Cycle Life before Capacity Degradation. Nature Energy, 4, 383-391.
https://doi.org/10.1038/s41560-019-0356-8
[49]  Chen, J., Zhang, Y., Wu, J., Cheng, W. and Zhu, Q. (2023) SOC Estimation for Lithium-Ion Battery Using the LSTM-RNN with Extended Input and Constrained Output. Energy, 262, Article 125375.
https://doi.org/10.1016/j.energy.2022.125375
[50]  Zhai, J., Zhang, S., Chen, J. and He, Q. (2018) Autoencoder and Its Various Variants. 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, 7-10 October 2018, 415-419.
https://doi.org/10.1109/smc.2018.00080
[51]  Bank, D., Koenigstein, N. and Giryes, R. (2023) Autoencoders. In: Rokach, L., Maimon, O. and Shmueli, E., Eds., Machine Learning for Data Science Handbook, Springer International Publishing, 353-374.
https://doi.org/10.1007/978-3-031-24628-9_16

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133