IDEAS home Printed from https://ideas.repec.org/r/eee/energy/v90y2015ip2p1426-1434.html
   My bibliography  Save this item

State of charge estimation of lithium-ion batteries based on an improved parameter identification method

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Zeeshan Ahmad Khan & Prashant Shrivastava & Syed Muhammad Amrr & Saad Mekhilef & Abdullah A. Algethami & Mehdi Seyedmahmoudian & Alex Stojcevski, 2022. "A Comparative Study on Different Online State of Charge Estimation Algorithms for Lithium-Ion Batteries," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
  2. Li, Xiaoyu & Fan, Guodong & Rizzoni, Giorgio & Canova, Marcello & Zhu, Chunbo & Wei, Guo, 2016. "A simplified multi-particle model for lithium ion batteries via a predictor-corrector strategy and quasi-linearization," Energy, Elsevier, vol. 116(P1), pages 154-169.
  3. Li, Yanwen & Wang, Chao & Gong, Jinfeng, 2016. "A combination Kalman filter approach for State of Charge estimation of lithium-ion battery considering model uncertainty," Energy, Elsevier, vol. 109(C), pages 933-946.
  4. Lai, Xin & Huang, Yunfeng & Gu, Huanghui & Han, Xuebing & Feng, Xuning & Dai, Haifeng & Zheng, Yuejiu & Ouyang, Minggao, 2022. "Remaining discharge energy estimation for lithium-ion batteries based on future load prediction considering temperature and ageing effects," Energy, Elsevier, vol. 238(PA).
  5. Farmann, Alexander & Waag, Wladislaw & Sauer, Dirk Uwe, 2016. "Application-specific electrical characterization of high power batteries with lithium titanate anodes for electric vehicles," Energy, Elsevier, vol. 112(C), pages 294-306.
  6. Yujie Cheng & Laifa Tao & Chao Yang, 2017. "Lithium-Ion Battery Capacity Estimation: A Method Based on Visual Cognition," Complexity, Hindawi, vol. 2017, pages 1-13, December.
  7. Xia, Bing & Zhao, Xin & de Callafon, Raymond & Garnier, Hugues & Nguyen, Truong & Mi, Chris, 2016. "Accurate Lithium-ion battery parameter estimation with continuous-time system identification methods," Applied Energy, Elsevier, vol. 179(C), pages 426-436.
  8. Zhang, Cheng & Allafi, Walid & Dinh, Quang & Ascencio, Pedro & Marco, James, 2018. "Online estimation of battery equivalent circuit model parameters and state of charge using decoupled least squares technique," Energy, Elsevier, vol. 142(C), pages 678-688.
  9. 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.
  10. Chen, Lin & Lin, Weilong & Li, Junzi & Tian, Binbin & Pan, Haihong, 2016. "Prediction of lithium-ion battery capacity with metabolic grey model," Energy, Elsevier, vol. 106(C), pages 662-672.
  11. Meng, Jinhao & Cai, Lei & Stroe, Daniel-Ioan & Luo, Guangzhao & Sui, Xin & Teodorescu, Remus, 2019. "Lithium-ion battery state-of-health estimation in electric vehicle using optimized partial charging voltage profiles," Energy, Elsevier, vol. 185(C), pages 1054-1062.
  12. Yixing Chen & Deqing Huang & Qiao Zhu & Weiqun Liu & Congzhi Liu & Neng Xiong, 2017. "A New State of Charge Estimation Algorithm for Lithium-Ion Batteries Based on the Fractional Unscented Kalman Filter," Energies, MDPI, vol. 10(9), pages 1-19, September.
  13. Ma, Mina & Wang, Yu & Duan, Qiangling & Wu, Tangqin & Sun, Jinhua & Wang, Qingsong, 2018. "Fault detection of the connection of lithium-ion power batteries in series for electric vehicles based on statistical analysis," Energy, Elsevier, vol. 164(C), pages 745-756.
  14. 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.
  15. Lin, Cheng & Yu, Quanqing & Xiong, Rui & Wang, Le Yi, 2017. "A study on the impact of open circuit voltage tests on state of charge estimation for lithium-ion batteries," Applied Energy, Elsevier, vol. 205(C), pages 892-902.
  16. Ning, Bo & Cao, Binggang & Wang, Bin & Zou, Zhongyue, 2018. "Adaptive sliding mode observers for lithium-ion battery state estimation based on parameters identified online," Energy, Elsevier, vol. 153(C), pages 732-742.
  17. Xia, Bizhong & Cui, Deyu & Sun, Zhen & Lao, Zizhou & Zhang, Ruifeng & Wang, Wei & Sun, Wei & Lai, Yongzhi & Wang, Mingwang, 2018. "State of charge estimation of lithium-ion batteries using optimized Levenberg-Marquardt wavelet neural network," Energy, Elsevier, vol. 153(C), pages 694-705.
  18. Guanghai Zhu & Jianbin Lin & Qingwu Liu & Hongwen He, 2019. "Research on the Energy-Saving Strategy of Path Planning for Electric Vehicles Considering Traffic Information," Energies, MDPI, vol. 12(19), pages 1-14, September.
  19. Xiong, Rui & Yu, Quanqing & Wang, Le Yi & Lin, Cheng, 2017. "A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter," Applied Energy, Elsevier, vol. 207(C), pages 346-353.
  20. Fan Zhang & Lele Yin & Jianqiang Kang, 2021. "Enhancing Stability and Robustness of State-of-Charge Estimation for Lithium-Ion Batteries by Using Improved Adaptive Kalman Filter Algorithms," Energies, MDPI, vol. 14(19), pages 1-18, October.
  21. Cui, Yingzhi & Zuo, Pengjian & Du, Chunyu & Gao, Yunzhi & Yang, Jie & Cheng, Xinqun & Ma, Yulin & Yin, Geping, 2018. "State of health diagnosis model for lithium ion batteries based on real-time impedance and open circuit voltage parameters identification method," Energy, Elsevier, vol. 144(C), pages 647-656.
  22. Dai, Haifeng & Yu, Chenchen & Wei, Xuezhe & Sun, Zechang, 2017. "State of charge estimation for lithium-ion pouch batteries based on stress measurement," Energy, Elsevier, vol. 129(C), pages 16-27.
  23. Jiahui Zhao & Yong Zhu & Bin Zhang & Mingyi Liu & Jianxing Wang & Chenghao Liu & Xiaowei Hao, 2023. "Review of State Estimation and Remaining Useful Life Prediction Methods for Lithium–Ion Batteries," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
  24. Sun, Daoming & Yu, Xiaoli & Wang, Chongming & Zhang, Cheng & Huang, Rui & Zhou, Quan & Amietszajew, Taz & Bhagat, Rohit, 2021. "State of charge estimation for lithium-ion battery based on an Intelligent Adaptive Extended Kalman Filter with improved noise estimator," Energy, Elsevier, vol. 214(C).
  25. Fotouhi, Abbas & Auger, Daniel J. & Propp, Karsten & Longo, Stefano & Wild, Mark, 2016. "A review on electric vehicle battery modelling: From Lithium-ion toward Lithium–Sulphur," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1008-1021.
  26. Singh, Karanjot & Tjahjowidodo, Tegoeh & Boulon, Loïc & Feroskhan, Mir, 2022. "Framework for measurement of battery state-of-health (resistance) integrating overpotential effects and entropy changes using energy equilibrium," Energy, Elsevier, vol. 239(PA).
  27. Cheng, Yujie & Song, Dengwei & Wang, Zhenya & Lu, Chen & Zerhouni, Noureddine, 2020. "An ensemble prognostic method for lithium-ion battery capacity estimation based on time-varying weight allocation," Applied Energy, Elsevier, vol. 266(C).
  28. Stefano Leonori & Luca Baldini & Antonello Rizzi & Fabio Massimo Frattale Mascioli, 2021. "A Physically Inspired Equivalent Neural Network Circuit Model for SoC Estimation of Electrochemical Cells," Energies, MDPI, vol. 14(21), pages 1-29, November.
  29. Dongchen Qin & Shuai Qin & Tingting Wang & Hongxia Wu & Jiangyi Chen, 2022. "Balanced Control System Based on Bidirectional Flyback DC Converter," Energies, MDPI, vol. 15(19), pages 1-25, October.
  30. Li, Yanwen & Wang, Chao & Gong, Jinfeng, 2017. "A multi-model probability SOC fusion estimation approach using an improved adaptive unscented Kalman filter technique," Energy, Elsevier, vol. 141(C), pages 1402-1415.
  31. Wang, Yujie & Tian, Jiaqiang & Sun, Zhendong & Wang, Li & Xu, Ruilong & Li, Mince & Chen, Zonghai, 2020. "A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  32. Zhu, Rui & Duan, Bin & Zhang, Chenghui & Gong, Sizhao, 2019. "Accurate lithium-ion battery modeling with inverse repeat binary sequence for electric vehicle applications," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  33. Firouz, Y. & Relan, R. & Timmermans, J.M. & Omar, N. & Van den Bossche, P. & Van Mierlo, J., 2016. "Advanced lithium ion battery modeling and nonlinear analysis based on robust method in frequency domain: Nonlinear characterization and non-parametric modeling," Energy, Elsevier, vol. 106(C), pages 602-617.
  34. Deng, Zhongwei & Yang, Lin & Cai, Yishan & Deng, Hao & Sun, Liu, 2016. "Online available capacity prediction and state of charge estimation based on advanced data-driven algorithms for lithium iron phosphate battery," Energy, Elsevier, vol. 112(C), pages 469-480.
  35. Maheshwari, A. & Nageswari, S., 2022. "Real-time state of charge estimation for electric vehicle power batteries using optimized filter," Energy, Elsevier, vol. 254(PB).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.