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A novel temperature-compensated model for power Li-ion batteries with dual-particle-filter state of charge estimation

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Cited by:

  1. Agarwal, Daksh & Potnuru, Rakesh & Kaushik, Chiranjeev & Darla, Vinay Rajesh & Kulkarni, Kaustubh & Garg, Ashish & Gupta, Raju Kumar & Tiwari, Naveen & Nalwa, Kanwar Singh, 2022. "Recent advances in the modeling of fundamental processes in liquid metal batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
  2. Yang, Fangfang & Zhang, Shaohui & Li, Weihua & Miao, Qiang, 2020. "State-of-charge estimation of lithium-ion batteries using LSTM and UKF," Energy, Elsevier, vol. 201(C).
  3. Hong, Jichao & Wang, Zhenpo & Chen, Wen & Yao, Yongtao, 2019. "Synchronous multi-parameter prediction of battery systems on electric vehicles using long short-term memory networks," Applied Energy, Elsevier, vol. 254(C).
  4. Shifei Yuan & Hongjie Wu & Xuerui Ma & Chengliang Yin, 2015. "Stability Analysis for Li-Ion Battery Model Parameters and State of Charge Estimation by Measurement Uncertainty Consideration," Energies, MDPI, vol. 8(8), pages 1-23, July.
  5. Sun, Fengchun & Xiong, Rui & He, Hongwen, 2016. "A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique," Applied Energy, Elsevier, vol. 162(C), pages 1399-1409.
  6. Duong, Van-Huan & Bastawrous, Hany Ayad & See, Khay Wai, 2017. "Accurate approach to the temperature effect on state of charge estimation in the LiFePO4 battery under dynamic load operation," Applied Energy, Elsevier, vol. 204(C), pages 560-571.
  7. Liu, Jiahao & Fan, Yining & Wang, Jinhui & Tao, Changfa & Chen, Mingyi, 2022. "A model-scale experimental and theoretical study on a mineral oil-immersed battery cooling system," Renewable Energy, Elsevier, vol. 201(P1), pages 712-723.
  8. Zheng, Fangdan & Xing, Yinjiao & Jiang, Jiuchun & Sun, Bingxiang & Kim, Jonghoon & Pecht, Michael, 2016. "Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries," Applied Energy, Elsevier, vol. 183(C), pages 513-525.
  9. Li, Yue & Chattopadhyay, Pritthi & Xiong, Sihan & Ray, Asok & Rahn, Christopher D., 2016. "Dynamic data-driven and model-based recursive analysis for estimation of battery state-of-charge," Applied Energy, Elsevier, vol. 184(C), pages 266-275.
  10. Avvari, G.V. & Pattipati, B. & Balasingam, B. & Pattipati, K.R. & Bar-Shalom, Y., 2015. "Experimental set-up and procedures to test and validate battery fuel gauge algorithms," Applied Energy, Elsevier, vol. 160(C), pages 404-418.
  11. Tang, Xiaopeng & Gao, Furong & Zou, Changfu & Yao, Ke & Hu, Wengui & Wik, Torsten, 2019. "Load-responsive model switching estimation for state of charge of lithium-ion batteries," Applied Energy, Elsevier, vol. 238(C), pages 423-434.
  12. Xian Wang & Zhengxiang Song & Kun Yang & Xuyang Yin & Yingsan Geng & Jianhua Wang, 2019. "State of Charge Estimation for Lithium-Bismuth Liquid Metal Batteries," Energies, MDPI, vol. 12(1), pages 1-22, January.
  13. Zhu, Rui & Duan, Bin & Zhang, Junming & Zhang, Qi & Zhang, Chenghui, 2020. "Co-estimation of model parameters and state-of-charge for lithium-ion batteries with recursive restricted total least squares and unscented Kalman filter," Applied Energy, Elsevier, vol. 277(C).
  14. Zhang, Yuan Ci & Briat, Olivier & Boulon, Loïc & Deletage, Jean-Yves & Martin, Cyril & Coccetti, Fabio & Vinassa, Jean-Michel, 2019. "Non-isothermal Ragone plots of Li-ion cells from datasheet and galvanostatic discharge tests," Applied Energy, Elsevier, vol. 247(C), pages 703-715.
  15. Wang, Yujie & Zhang, Chenbin & Chen, Zonghai, 2017. "On-line battery state-of-charge estimation based on an integrated estimator," Applied Energy, Elsevier, vol. 185(P2), pages 2026-2032.
  16. Zhang, Yuntian & Zuo, Wei & E, Jiaqiang & Li, Jing & Li, Qingqing & Sun, Ke & Zhou, Kun & Zhang, Guangde, 2022. "Performance comparison between straight channel cold plate and inclined channel cold plate for thermal management of a prismatic LiFePO4 battery," Energy, Elsevier, vol. 248(C).
  17. Ansari, Amir Babak & Esfahanian, Vahid & Torabi, Farschad, 2016. "Discharge, rest and charge simulation of lead-acid batteries using an efficient reduced order model based on proper orthogonal decomposition," Applied Energy, Elsevier, vol. 173(C), pages 152-167.
  18. Wei, Jingwen & Dong, Guangzhong & Chen, Zonghai & Kang, Yu, 2017. "System state estimation and optimal energy control framework for multicell lithium-ion battery system," Applied Energy, Elsevier, vol. 187(C), pages 37-49.
  19. Yang, Fangfang & Xing, Yinjiao & Wang, Dong & Tsui, Kwok-Leung, 2016. "A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile," Applied Energy, Elsevier, vol. 164(C), pages 387-399.
  20. Wang, Yujie & Zhang, Chenbin & Chen, Zonghai, 2014. "A method for joint estimation of state-of-charge and available energy of LiFePO4 batteries," Applied Energy, Elsevier, vol. 135(C), pages 81-87.
  21. Dong, Guangzhong & Wei, Jingwen & Zhang, Chenbin & Chen, Zonghai, 2016. "Online state of charge estimation and open circuit voltage hysteresis modeling of LiFePO4 battery using invariant imbedding method," Applied Energy, Elsevier, vol. 162(C), pages 163-171.
  22. Changwen Zheng & Yunlong Ge & Ziqiang Chen & Deyang Huang & Jian Liu & Shiyao Zhou, 2017. "Diagnosis Method for Li-Ion Battery Fault Based on an Adaptive Unscented Kalman Filter," Energies, MDPI, vol. 10(11), pages 1-14, November.
  23. Ingvild B. Espedal & Asanthi Jinasena & Odne S. Burheim & Jacob J. Lamb, 2021. "Current Trends for State-of-Charge (SoC) Estimation in Lithium-Ion Battery Electric Vehicles," Energies, MDPI, vol. 14(11), pages 1-24, June.
  24. Oh, Ki-Yong & Epureanu, Bogdan I., 2016. "Characterization and modeling of the thermal mechanics of lithium-ion battery cells," Applied Energy, Elsevier, vol. 178(C), pages 633-646.
  25. Xiangyu Cui & Zhu Jing & Maji Luo & Yazhou Guo & Huimin Qiao, 2018. "A New Method for State of Charge Estimation of Lithium-Ion Batteries Using Square Root Cubature Kalman Filter," Energies, MDPI, vol. 11(1), pages 1-21, January.
  26. Feng, Xiong & Chen, Junxiong & Zhang, Zhongwei & Miao, Shuwen & Zhu, Qiao, 2021. "State-of-charge estimation of lithium-ion battery based on clockwork recurrent neural network," Energy, Elsevier, vol. 236(C).
  27. Cuma, Mehmet Ugras & Koroglu, Tahsin, 2015. "A comprehensive review on estimation strategies used in hybrid and battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 517-531.
  28. Xintian Liu & Xuhui Deng & Yao He & Xinxin Zheng & Guojian Zeng, 2019. "A Dynamic State-of-Charge Estimation Method for Electric Vehicle Lithium-Ion Batteries," Energies, MDPI, vol. 13(1), pages 1-16, December.
  29. Wang, Yujie & Zhang, Chenbin & Chen, Zonghai & Xie, Jing & Zhang, Xu, 2015. "A novel active equalization method for lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 145(C), pages 36-42.
  30. Deng Ma & Kai Gao & Yutao Mu & Ziqi Wei & Ronghua Du, 2022. "An Adaptive Tracking-Extended Kalman Filter for SOC Estimation of Batteries with Model Uncertainty and Sensor Error," Energies, MDPI, vol. 15(10), pages 1-18, May.
  31. Song, Zhen & Pan, Yue & Chen, Huicui & Zhang, Tong, 2021. "Effects of temperature on the performance of fuel cell hybrid electric vehicles: A review," Applied Energy, Elsevier, vol. 302(C).
  32. Shichun Yang & Cheng Deng & Yulong Zhang & Yongling He, 2017. "State of Charge Estimation for Lithium-Ion Battery with a Temperature-Compensated Model," Energies, MDPI, vol. 10(10), pages 1-14, October.
  33. Lin, Wei-Jen & Chen, Kuo-Ching, 2022. "Evolution of parameters in the Doyle-Fuller-Newman model of cycling lithium ion batteries by multi-objective optimization," Applied Energy, Elsevier, vol. 314(C).
  34. Xie, Yanping & Zhao, Hongbin & Cheng, Hongwei & Hu, Chenji & Fang, Wenying & Fang, Jianhui & Xu, Jiaqiang & Chen, Zhongwei, 2016. "Facile large-scale synthesis of core–shell structured sulfur@polypyrrole composite and its application in lithium–sulfur batteries with high energy density," Applied Energy, Elsevier, vol. 175(C), pages 522-528.
  35. Xiaopeng Tang & Ke Yao & Boyang Liu & Wengui Hu & Furong Gao, 2018. "Long-Term Battery Voltage, Power, and Surface Temperature Prediction Using a Model-Based Extreme Learning Machine," Energies, MDPI, vol. 11(1), pages 1-16, January.
  36. Linhui Zhao & Guohuang Ji & Zhiyuan Liu, 2017. "Design and Experiment of Nonlinear Observer with Adaptive Gains for Battery State of Charge Estimation," Energies, MDPI, vol. 10(12), pages 1-20, December.
  37. Wang, Yujie & Zhang, Chenbin & Chen, Zonghai, 2015. "A method for state-of-charge estimation of Li-ion batteries based on multi-model switching strategy," Applied Energy, Elsevier, vol. 137(C), pages 427-434.
  38. Salpakari, Jyri & Rasku, Topi & Lindgren, Juuso & Lund, Peter D., 2017. "Flexibility of electric vehicles and space heating in net zero energy houses: an optimal control model with thermal dynamics and battery degradation," Applied Energy, Elsevier, vol. 190(C), pages 800-812.
  39. Renxin, Xiao & Yi, Yang & Xianguang, Jia & Nan, Pan, 2023. "Collaborative estimations of state of energy and maximum available energy of lithium-ion batteries with optimized time windows considering instantaneous energy efficiencies," Energy, Elsevier, vol. 274(C).
  40. 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).
  41. Wang, Tao & Tseng, K.J. & Zhao, Jiyun & Wei, Zhongbao, 2014. "Thermal investigation of lithium-ion battery module with different cell arrangement structures and forced air-cooling strategies," Applied Energy, Elsevier, vol. 134(C), pages 229-238.
  42. Lin, Cheng & Mu, Hao & Xiong, Rui & Cao, Jiayi, 2017. "Multi-model probabilities based state fusion estimation method of lithium-ion battery for electric vehicles: State-of-energy," Applied Energy, Elsevier, vol. 194(C), pages 560-568.
  43. Dong, Guangzhong & Zhang, Xu & Zhang, Chenbin & Chen, Zonghai, 2015. "A method for state of energy estimation of lithium-ion batteries based on neural network model," Energy, Elsevier, vol. 90(P1), pages 879-888.
  44. Tang, Xiaopeng & Liu, Boyang & Lv, Zhou & Gao, Furong, 2017. "Observer based battery SOC estimation: Using multi-gain-switching approach," Applied Energy, Elsevier, vol. 204(C), pages 1275-1283.
  45. Zuo, Wei & Zhang, Yuntian & E, Jiaqiang & Huang, Yuhan & Li, Qingqing & Zhou, Kun & Zhang, Guangde, 2022. "Effects of multi-factors on performance of an improved multi-channel cold plate for thermal management of a prismatic LiFePO4 battery," Energy, Elsevier, vol. 261(PB).
  46. Xingtao Liu & Chaoyi Zheng & Ji Wu & Jinhao Meng & Daniel-Ioan Stroe & Jiajia Chen, 2020. "An Improved State of Charge and State of Power Estimation Method Based on Genetic Particle Filter for Lithium-ion Batteries," Energies, MDPI, vol. 13(2), pages 1-16, January.
  47. Bo Huang & Yuting Ma & Chun Wang & Yongzhi Chen & Quanqing Yu, 2021. "A Multi-Model Probability Based Two-Layer Fusion Modeling Approach of Supercapacitor for Electric Vehicles," Energies, MDPI, vol. 14(15), pages 1-16, July.
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