State estimation for advanced battery management: Key challenges and future trends

Citations

Cited by:

1. Li, Alan G. & Wang, Weizhong & West, Alan C. & Preindl, Matthias, 2022. "Health and performance diagnostics in Li-ion batteries with pulse-injection-aided machine learning," Applied Energy, Elsevier, vol. 315(C).
2. 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).
3. Yiding, Li & Wenwei, Wang & Cheng, Lin & Xiaoguang, Yang & Fenghao, Zuo, 2021. "A safety performance estimation model of lithium-ion batteries for electric vehicles under dynamic compression," Energy, Elsevier, vol. 215(PA).
4. Zhihang Zhang & Languang Lu & Yalun Li & Hewu Wang & Minggao Ouyang, 2023. "Accurate Remaining Available Energy Estimation of LiFePO 4 Battery in Dynamic Frequency Regulation for EVs with Thermal-Electric-Hysteresis Model," Energies, MDPI, vol. 16(13), pages 1-28, July.
5. Xinwei Sun & Yang Zhang & Yongcheng Zhang & Licheng Wang & Kai Wang, 2023. "Summary of Health-State Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy," Energies, MDPI, vol. 16(15), pages 1-19, July.
6. Sun, Li & Sun, Wen & You, Fengqi, 2020. "Core temperature modelling and monitoring of lithium-ion battery in the presence of sensor bias," Applied Energy, Elsevier, vol. 271(C).
7. Xu, Zhicheng & Wang, Jun & Lund, Peter D. & Zhang, Yaoming, 2021. "Estimation and prediction of state of health of electric vehicle batteries using discrete incremental capacity analysis based on real driving data," Energy, Elsevier, vol. 225(C).
8. Balali, Yasaman & Stegen, Sascha, 2021. "Review of energy storage systems for vehicles based on technology, environmental impacts, and costs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
9. Zhao, Chunyang & Andersen, Peter Bach & Træholt, Chresten & Hashemi, Seyedmostafa, 2023. "Grid-connected battery energy storage system: a review on application and integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
10. Naseri, F. & Gil, S. & Barbu, C. & Cetkin, E. & Yarimca, G. & Jensen, A.C. & Larsen, P.G. & Gomes, C., 2023. "Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
11. Hu, Lin & Hu, Xiaosong & Che, Yunhong & Feng, Fei & Lin, Xianke & Zhang, Zhiyong, 2020. "Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering," Applied Energy, Elsevier, vol. 262(C).
12. Yu, Haijun & Dai, Hongliang & Tian, Guangdong & Wu, Benben & Xie, Yinghao & Zhu, Ying & Zhang, Tongzhu & Fathollahi-Fard, Amir Mohammad & He, Qi & Tang, Hong, 2021. "Key technology and application analysis of quick coding for recovery of retired energy vehicle battery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
13. Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiao & Fernandez, Carlos, 2023. "A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures," Energy, Elsevier, vol. 273(C).
14. Li, Xiaoyu & Xu, Jianhua & Hong, Jianxun & Tian, Jindong & Tian, Yong, 2021. "State of energy estimation for a series-connected lithium-ion battery pack based on an adaptive weighted strategy," Energy, Elsevier, vol. 214(C).
15. Wang, Fujin & Zhao, Zhibin & Zhai, Zhi & Shang, Zuogang & Yan, Ruqiang & Chen, Xuefeng, 2023. "Explainability-driven model improvement for SOH estimation of lithium-ion battery," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
16. 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).
17. Jiang, Bo & Tao, Siyi & Wang, Xueyuan & Zhu, Jiangong & Wei, Xuezhe & Dai, Haifeng, 2023. "Mechanics-based state of charge estimation for lithium-ion pouch battery using deep learning technique," Energy, Elsevier, vol. 278(PA).
18. Shen, Jiangwei & Ma, Wensai & Shu, Xing & Shen, Shiquan & Chen, Zheng & Liu, Yonggang, 2023. "Accurate state of health estimation for lithium-ion batteries under random charging scenarios," Energy, Elsevier, vol. 279(C).
19. Shen, Zu-Guo & Chen, Shuai & Liu, Xun & Chen, Ben, 2021. "A review on thermal management performance enhancement of phase change materials for vehicle lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
20. Hou, Jie & Liu, Jiawei & Chen, Fengwei & Li, Penghua & Zhang, Tao & Jiang, Jincheng & Chen, Xiaolei, 2023. "Robust lithium-ion state-of-charge and battery parameters joint estimation based on an enhanced adaptive unscented Kalman filter," Energy, Elsevier, vol. 271(C).
21. Rauf, Huzaifa & Khalid, Muhammad & Arshad, Naveed, 2022. "Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
22. Deng, Zhongwei & Hu, Xiaosong & Lin, Xianke & Che, Yunhong & Xu, Le & Guo, Wenchao, 2020. "Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression," Energy, Elsevier, vol. 205(C).
23. Jin, Haiyan & Cui, Ningmin & Cai, Lei & Meng, Jinhao & Li, Junxin & Peng, Jichang & Zhao, Xinchao, 2023. "State-of-health estimation for lithium-ion batteries with hierarchical feature construction and auto-configurable Gaussian process regression," Energy, Elsevier, vol. 262(PB).
24. Xue, Qiao & Li, Junqiu & Xu, Peipei, 2022. "Machine learning based swift online capacity prediction of lithium-ion battery through whole cycle life," Energy, Elsevier, vol. 261(PA).
25. Wang, Shuai & Ma, Hongyan & Zhang, Yingda & Li, Shengyan & He, Wei, 2023. "Remaining useful life prediction method of lithium-ion batteries is based on variational modal decomposition and deep learning integrated approach," Energy, Elsevier, vol. 282(C).
26. Zhao, Hongqian & Chen, Zheng & Shu, Xing & Shen, Jiangwei & Lei, Zhenzhen & Zhang, Yuanjian, 2023. "State of health estimation for lithium-ion batteries based on hybrid attention and deep learning," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
27. Mei Zhang & Wanli Chen & Jun Yin & Tao Feng, 2022. "Lithium Battery Health Factor Extraction Based on Improved Douglas–Peucker Algorithm and SOH Prediction Based on XGboost," Energies, MDPI, vol. 15(16), pages 1-18, August.
28. 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.
29. Xu, Xiaodong & Tang, Shengjin & Han, Xuebing & Lu, Languang & Wu, Yu & Yu, Chuanqiang & Sun, Xiaoyan & Xie, Jian & Feng, Xuning & Ouyang, Minggao, 2023. "Fast capacity prediction of lithium-ion batteries using aging mechanism-informed bidirectional long short-term memory network," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
30. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
31. Guo, Yuanjun & Yang, Zhile & Liu, Kailong & Zhang, Yanhui & Feng, Wei, 2021. "A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system," Energy, Elsevier, vol. 219(C).
32. Yan, Lisen & Peng, Jun & Gao, Dianzhu & Wu, Yue & Liu, Yongjie & Li, Heng & Liu, Weirong & Huang, Zhiwu, 2022. "A hybrid method with cascaded structure for early-stage remaining useful life prediction of lithium-ion battery," Energy, Elsevier, vol. 243(C).
33. 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).
34. Hamed Sadegh Kouhestani & Xiaoping Yi & Guoqing Qi & Xunliang Liu & Ruimin Wang & Yang Gao & Xiao Yu & Lin Liu, 2022. "Prognosis and Health Management (PHM) of Solid-State Batteries: Perspectives, Challenges, and Opportunities," Energies, MDPI, vol. 15(18), pages 1-26, September.
35. Chen, Zheng & Zhao, Hongqian & Shu, Xing & Zhang, Yuanjian & Shen, Jiangwei & Liu, Yonggang, 2021. "Synthetic state of charge estimation for lithium-ion batteries based on long short-term memory network modeling and adaptive H-Infinity filter," Energy, Elsevier, vol. 228(C).
36. Tang, Xiaopeng & Liu, Kailong & Lu, Jingyi & Liu, Boyang & Wang, Xin & Gao, Furong, 2020. "Battery incremental capacity curve extraction by a two-dimensional Luenberger–Gaussian-moving-average filter," Applied Energy, Elsevier, vol. 280(C).
37. Liu, Kailong & Ashwin, T.R. & Hu, Xiaosong & Lucu, Mattin & Widanage, W. Dhammika, 2020. "An evaluation study of different modelling techniques for calendar ageing prediction of lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
38. Liu, Chunli & Li, Qiang & Wang, Kai, 2021. "State-of-charge estimation and remaining useful life prediction of supercapacitors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
39. Yang, Yang & Yuan, Wei & Zhang, Xiaoqing & Wang, Chun & Yuan, Yuhang & Huang, Yao & Ye, Yintong & Qiu, Zhiqiang & Tang, Yong, 2020. "A review on FexOy-based materials for advanced lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
40. Michael Bosello & Carlo Falcomer & Claudio Rossi & Giovanni Pau, 2023. "To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders," Energies, MDPI, vol. 16(6), pages 1-17, March.
41. Che, Yunhong & Deng, Zhongwei & Li, Penghua & Tang, Xiaolin & Khosravinia, Kavian & Lin, Xianke & Hu, Xiaosong, 2022. "State of health prognostics for series battery packs: A universal deep learning method," Energy, Elsevier, vol. 238(PB).
42. Li, Alan G. & West, Alan C. & Preindl, Matthias, 2022. "Towards unified machine learning characterization of lithium-ion battery degradation across multiple levels: A critical review," Applied Energy, Elsevier, vol. 316(C).
43. Xin Lai & Ming Yuan & Xiaopeng Tang & Yi Yao & Jiahui Weng & Furong Gao & Weiguo Ma & Yuejiu Zheng, 2022. "Co-Estimation of State-of-Charge and State-of-Health for Lithium-Ion Batteries Considering Temperature and Ageing," Energies, MDPI, vol. 15(19), pages 1-20, October.
44. Li, Xiaoyu & Yuan, Changgui & Wang, Zhenpo, 2020. "State of health estimation for Li-ion battery via partial incremental capacity analysis based on support vector regression," Energy, Elsevier, vol. 203(C).
45. Jingwei Hu & Bing Lin & Mingfen Wang & Jie Zhang & Wenliang Zhang & Yu Lu, 2022. "State of Charge Centralized Estimation of Road Condition Information Based on Fuzzy Sunday Algorithm," Energies, MDPI, vol. 15(8), pages 1-15, April.
46. Jiang, Lulu & Deng, Zhongwei & Tang, Xiaolin & Hu, Lin & Lin, Xianke & Hu, Xiaosong, 2021. "Data-driven fault diagnosis and thermal runaway warning for battery packs using real-world vehicle data," Energy, Elsevier, vol. 234(C).
47. Han, Ying & Yang, Hanqing & Li, Qi & Chen, Weirong & Zare, Firuz & Guerrero, Josep M., 2020. "Mode-triggered droop method for the decentralized energy management of an islanded hybrid PV/hydrogen/battery DC microgrid," Energy, Elsevier, vol. 199(C).
48. Ouyang, Tiancheng & Xu, Peihang & Chen, Jingxian & Su, Zixiang & Huang, Guicong & Chen, Nan, 2021. "A novel state of charge estimation method for lithium-ion batteries based on bias compensation," Energy, Elsevier, vol. 226(C).
49. Dai, Haifeng & Jiang, Bo & Hu, Xiaosong & Lin, Xianke & Wei, Xuezhe & Pecht, Michael, 2021. "Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
50. Chen, Junxiong & Feng, Xiong & Jiang, Lin & Zhu, Qiao, 2021. "State of charge estimation of lithium-ion battery using denoising autoencoder and gated recurrent unit recurrent neural network," Energy, Elsevier, vol. 227(C).
51. Lai, Xin & Zhou, Long & Zhu, Zhiwei & Zheng, Yuejiu & Sun, Tao & Shen, Kai, 2023. "Experimental investigation on the characteristics of coulombic efficiency of lithium-ion batteries considering different influencing factors," Energy, Elsevier, vol. 274(C).
52. Wang, Ya-Xiong & Chen, Zhenhang & Zhang, Wei, 2022. "Lithium-ion battery state-of-charge estimation for small target sample sets using the improved GRU-based transfer learning," Energy, Elsevier, vol. 244(PB).
53. Cheng, Gong & Wang, Xinzhi & He, Yurong, 2021. "Remaining useful life and state of health prediction for lithium batteries based on empirical mode decomposition and a long and short memory neural network," Energy, Elsevier, vol. 232(C).
54. Liu, Gengfeng & Zhang, Xiangwen & Liu, Zhiming, 2022. "State of health estimation of power batteries based on multi-feature fusion models using stacking algorithm," Energy, Elsevier, vol. 259(C).
55. Khaleghi, Sahar & Hosen, Md Sazzad & Karimi, Danial & Behi, Hamidreza & Beheshti, S. Hamidreza & Van Mierlo, Joeri & Berecibar, Maitane, 2022. "Developing an online data-driven approach for prognostics and health management of lithium-ion batteries," Applied Energy, Elsevier, vol. 308(C).
56. Molla Shahadat Hossain Lipu & Tahia F. Karim & Shaheer Ansari & Md. Sazal Miah & Md. Siddikur Rahman & Sheikh T. Meraj & Rajvikram Madurai Elavarasan & Raghavendra Rajan Vijayaraghavan, 2022. "Intelligent SOX Estimation for Automotive Battery Management Systems: State-of-the-Art Deep Learning Approaches, Open Issues, and Future Research Opportunities," Energies, MDPI, vol. 16(1), pages 1-31, December.
57. Li, Penghua & Zhang, Zijian & Grosu, Radu & Deng, Zhongwei & Hou, Jie & Rong, Yujun & Wu, Rui, 2022. "An end-to-end neural network framework for state-of-health estimation and remaining useful life prediction of electric vehicle lithium batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
58. Hu, Xiaosong & Deng, Zhongwei & Lin, Xianke & Xie, Yi & Teodorescu, Remus, 2021. "Research directions for next-generation battery management solutions in automotive applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
59. Zheng Chen & Jiapeng Xiao & Xing Shu & Shiquan Shen & Jiangwei Shen & Yonggang Liu, 2020. "Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire Lifespan," Energies, MDPI, vol. 13(6), pages 1-15, March.
60. Neha Bhushan & Saad Mekhilef & Kok Soon Tey & Mohamed Shaaban & Mehdi Seyedmahmoudian & Alex Stojcevski, 2022. "Overview of Model- and Non-Model-Based Online Battery Management Systems for Electric Vehicle Applications: A Comprehensive Review of Experimental and Simulation Studies," Sustainability, MDPI, vol. 14(23), pages 1-31, November.
61. Xiong, Rui & Pan, Yue & Shen, Weixiang & Li, Hailong & Sun, Fengchun, 2020. "Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
62. 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).
63. Park, Jinhyeong & Kim, Kunwoo & Park, Seongyun & Baek, Jongbok & Kim, Jonghoon, 2021. "Complementary cooperative SOC/capacity estimator based on the discrete variational derivative combined with the DEKF for electric power applications," Energy, Elsevier, vol. 232(C).
64. Shu, Xing & Li, Guang & Shen, Jiangwei & Lei, Zhenzhen & Chen, Zheng & Liu, Yonggang, 2020. "An adaptive multi-state estimation algorithm for lithium-ion batteries incorporating temperature compensation," Energy, Elsevier, vol. 207(C).
65. Bosong Zou & Lisheng Zhang & Xiaoqing Xue & Rui Tan & Pengchang Jiang & Bin Ma & Zehua Song & Wei Hua, 2023. "A Review on the Fault and Defect Diagnosis of Lithium-Ion Battery for Electric Vehicles," Energies, MDPI, vol. 16(14), pages 1-19, July.
66. Qin, Yechen & Tang, Xiaolin & Jia, Tong & Duan, Ziwen & Zhang, Jieming & Li, Yinong & Zheng, Ling, 2020. "Noise and vibration suppression in hybrid electric vehicles: State of the art and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
67. Tian, Jiaqiang & Wang, Yujie & Liu, Chang & Chen, Zonghai, 2020. "Consistency evaluation and cluster analysis for lithium-ion battery pack in electric vehicles," Energy, Elsevier, vol. 194(C).
68. Wang, Yujie & Zhang, Xingchen & Chen, Zonghai, 2022. "Low temperature preheating techniques for Lithium-ion batteries: Recent advances and future challenges," Applied Energy, Elsevier, vol. 313(C).
69. Sui, Xin & He, Shan & Vilsen, Søren B. & Meng, Jinhao & Teodorescu, Remus & Stroe, Daniel-Ioan, 2021. "A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery," Applied Energy, Elsevier, vol. 300(C).
70. Claudio Rossi & Carlo Falcomer & Luca Biondani & Davide Pontara, 2022. "Genetically Optimized Extended Kalman Filter for State of Health Estimation Based on Li-Ion Batteries Parameters," Energies, MDPI, vol. 15(9), pages 1-18, May.
71. Che, Yunhong & Zheng, Yusheng & Wu, Yue & Sui, Xin & Bharadwaj, Pallavi & Stroe, Daniel-Ioan & Yang, Yalian & Hu, Xiaosong & Teodorescu, Remus, 2022. "Data efficient health prognostic for batteries based on sequential information-driven probabilistic neural network," Applied Energy, Elsevier, vol. 323(C).