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Comparative study of reduced order equivalent circuit models for on-board state-of-available-power prediction of lithium-ion batteries in electric vehicles

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Cited by:

  1. Guo, Ruohan & Shen, Weixiang, 2022. "A data-model fusion method for online state of power estimation of lithium-ion batteries at high discharge rate in electric vehicles," Energy, Elsevier, vol. 254(PA).
  2. Leone Martellucci & Mirko Dell’Aria & Roberto Capata, 2023. "Experimental Analysis and Simulation of Mixed Storage with Lithium-Ion Batteries and Supercapacitors for a PHEV," Energies, MDPI, vol. 16(9), pages 1-18, May.
  3. Yun Bao & Yuansheng Chen, 2021. "Lithium-Ion Battery Real-Time Diagnosis with Direct Current Impedance Spectroscopy," Energies, MDPI, vol. 14(15), pages 1-16, July.
  4. Guoqing Jin & Lan Li & Yidan Xu & Minghui Hu & Chunyun Fu & Datong Qin, 2020. "Comparison of SOC Estimation between the Integer-Order Model and Fractional-Order Model Under Different Operating Conditions," Energies, MDPI, vol. 13(7), pages 1-17, April.
  5. Tae-Won Noh & Junghoon Ahn & Byoung Kuk Lee, 2022. "Online Cell Screening Algorithm for Maximum Peak Current Estimation of a Lithium-Ion Battery Pack for Electric Vehicles," Energies, MDPI, vol. 15(4), pages 1-14, February.
  6. Pingwei Gu & Zhongkai Zhou & Shaofei Qu & Chenghui Zhang & Bin Duan, 2019. "Influence Analysis and Optimization of Sampling Frequency on the Accuracy of Model and State-of-Charge Estimation for LiNCM Battery," Energies, MDPI, vol. 12(7), pages 1-19, March.
  7. Zhang, Hao & Gao, Jingyi & Kang, Le & Zhang, Yi & Wang, Licheng & Wang, Kai, 2023. "State of health estimation of lithium-ion batteries based on modified flower pollination algorithm-temporal convolutional network," Energy, Elsevier, vol. 283(C).
  8. Theodoros Kalogiannis & Md Sazzad Hosen & Mohsen Akbarzadeh Sokkeh & Shovon Goutam & Joris Jaguemont & Lu Jin & Geng Qiao & Maitane Berecibar & Joeri Van Mierlo, 2019. "Comparative Study on Parameter Identification Methods for Dual-Polarization Lithium-Ion Equivalent Circuit Model," Energies, MDPI, vol. 12(21), pages 1-35, October.
  9. Shunli Wang & Pu Ren & Paul Takyi-Aninakwa & Siyu Jin & Carlos Fernandez, 2022. "A Critical Review of Improved Deep Convolutional Neural Network for Multi-Timescale State Prediction of Lithium-Ion Batteries," Energies, MDPI, vol. 15(14), pages 1-27, July.
  10. Kim, Seongyoon & Choi, Yun Young & Choi, Jung-Il, 2022. "Impedance-based capacity estimation for lithium-ion batteries using generative adversarial network," Applied Energy, Elsevier, vol. 308(C).
  11. Li, Shuangqi & He, Hongwen & Zhao, Pengfei & Cheng, Shuang, 2022. "Health-Conscious vehicle battery state estimation based on deep transfer learning," Applied Energy, Elsevier, vol. 316(C).
  12. Sanjay K. Chaudhary & Allan F. Cupertino & Remus Teodorescu & Jan R. Svensson, 2020. "Benchmarking of Modular Multilevel Converter Topologies for ES-STATCOM Realization," Energies, MDPI, vol. 13(13), pages 1-22, July.
  13. Yang, Jufeng & Cai, Yingfeng & Pan, Chaofeng & Mi, Chris, 2019. "A novel resistor-inductor network-based equivalent circuit model of lithium-ion batteries under constant-voltage charging condition," Applied Energy, Elsevier, vol. 254(C).
  14. Li, Yong & Wang, Liye & Feng, Yanbiao & Liao, Chenglin & Yang, Jue, 2024. "An online state-of-health estimation method for lithium-ion battery based on linear parameter-varying modeling framework," Energy, Elsevier, vol. 298(C).
  15. Zhu, Jiangong & Knapp, Michael & Darma, Mariyam Susana Dewi & Fang, Qiaohua & Wang, Xueyuan & Dai, Haifeng & Wei, Xuezhe & Ehrenberg, Helmut, 2019. "An improved electro-thermal battery model complemented by current dependent parameters for vehicular low temperature application," Applied Energy, Elsevier, vol. 248(C), pages 149-161.
  16. Murat Akil & Emrah Dokur & Ramazan Bayindir, 2021. "The SOC Based Dynamic Charging Coordination of EVs in the PV-Penetrated Distribution Network Using Real-World Data," Energies, MDPI, vol. 14(24), pages 1-19, December.
  17. Qi, Kaijian & Zhang, Weigang & Zhou, Wei & Cheng, Jifu, 2022. "Integrated battery power capability prediction and driving torque regulation for electric vehicles: A reduced order MPC approach," Applied Energy, Elsevier, vol. 317(C).
  18. Yang, Jufeng & Huang, Wenxin & Xia, Bing & Mi, Chris, 2019. "The improved open-circuit voltage characterization test using active polarization voltage reduction method," Applied Energy, Elsevier, vol. 237(C), pages 682-694.
  19. Mina Naguib & Aashit Rathore & Nathan Emery & Shiva Ghasemi & Ryan Ahmed, 2023. "Robust Electro-Thermal Modeling of Lithium-Ion Batteries for Electrified Vehicles Applications," Energies, MDPI, vol. 16(16), pages 1-20, August.
  20. Adrian Chmielewski & Jakub Możaryn & Piotr Piórkowski & Krzysztof Bogdziński, 2018. "Comparison of NARX and Dual Polarization Models for Estimation of the VRLA Battery Charging/Discharging Dynamics in Pulse Cycle," Energies, MDPI, vol. 11(11), pages 1-28, November.
  21. Mehta, Rohit & Gupta, Amit, 2024. "Mathematical modelling of electrochemical, thermal and degradation processes in lithium-ion cells—A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  22. Biju, Nikhil & Fang, Huazhen, 2023. "BattX: An equivalent circuit model for lithium-ion batteries over broad current ranges," Applied Energy, Elsevier, vol. 339(C).
  23. Li, Shuangqi & He, Hongwen & Zhao, Pengfei & Cheng, Shuang, 2022. "Data cleaning and restoring method for vehicle battery big data platform," Applied Energy, Elsevier, vol. 320(C).
  24. Gao, Yizhao & Liu, Chenghao & Chen, Shun & Zhang, Xi & Fan, Guodong & Zhu, Chong, 2022. "Development and parameterization of a control-oriented electrochemical model of lithium-ion batteries for battery-management-systems applications," Applied Energy, Elsevier, vol. 309(C).
  25. Amiri, Mahshid N. & Håkansson, Anne & Burheim, Odne S. & Lamb, Jacob J., 2024. "Lithium-ion battery digitalization: Combining physics-based models and machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 200(C).
  26. Yao, Jiachi & Chang, Zhonghao & Han, Te & Tian, Jingpeng, 2024. "Semi-supervised adversarial deep learning for capacity estimation of battery energy storage systems," Energy, Elsevier, vol. 294(C).
  27. Tae-Won Noh & Jung-Hoon Ahn & Byoung Kuk Lee, 2019. "Cranking Capability Estimation Algorithm Based on Modeling and Online Update of Model Parameters for Li-Ion SLI Batteries," Energies, MDPI, vol. 12(17), pages 1-14, September.
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