Fault detection of the connection of lithium-ion power batteries in series for electric vehicles based on statistical analysis
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DOI: 10.1016/j.energy.2018.09.047
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Citations
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Cited by:
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- Liu, Qiquan & Ma, Jian & Zhao, Xuan & Zhang, Kai & Meng, Dean, 2023. "Online diagnosis and prediction of power battery voltage comprehensive faults for electric vehicles based on multi-parameter characterization and improved K-means method," Energy, Elsevier, vol. 283(C).
- Jinrui Nan & Bo Deng & Wanke Cao & Jianjun Hu & Yuhua Chang & Yili Cai & Zhiwei Zhong, 2022. "Big Data-Based Early Fault Warning of Batteries Combining Short-Text Mining and Grey Correlation," Energies, MDPI, vol. 15(15), pages 1-19, July.
- Gil-Sayas, Susana & Komnos, Dimitrios & Lodi, Chiara & Currò, Davide & Serra, Simone & Broatch, Alberto & Fontaras, Georgios, 2022. "Analysing the potential of a simulation-based method for the assessment of CO2 savings from eco-innovative technologies in light-duty vehicles," Energy, Elsevier, vol. 245(C).
- 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.
- Xu, Jun & Wang, Haitao & Shi, Hu & Mei, Xuesong, 2020. "Multi-scale short circuit resistance estimation method for series connected battery strings," Energy, Elsevier, vol. 202(C).
- Liu, Hanxiao & Li, Liwei & Duan, Bin & Kang, Yongzhe & Zhang, Chenghui, 2024. "Multi-fault detection and diagnosis method for battery packs based on statistical analysis," Energy, Elsevier, vol. 293(C).
- Li, Da & Deng, Junjun & Zhang, Zhaosheng & Liu, Peng & Wang, Zhenpo, 2023. "Multi-dimension statistical analysis and selection of safety-representing features for battery pack in real-world electric vehicles," Applied Energy, Elsevier, vol. 343(C).
- Shen, Dongxu & Yang, Dazhi & Lyu, Chao & Ma, Jingyan & Hinds, Gareth & Sun, Qingmin & Du, Limei & Wang, Lixin, 2024. "Multi-sensor multi-mode fault diagnosis for lithium-ion battery packs with time series and discriminative features," Energy, Elsevier, vol. 290(C).
- Shen, Dongxu & Lyu, Chao & Yang, Dazhi & Hinds, Gareth & Ma, Kai & Xu, Shaochun & Bai, Miao, 2024. "Concurrent multi-fault diagnosis of lithium-ion battery packs using random convolution kernel transformation and Gaussian process classifier," Energy, Elsevier, vol. 306(C).
- Shu, Xing & Li, Guang & Shen, Jiangwei & Lei, Zhenzhen & Chen, Zheng & Liu, Yonggang, 2020. "A uniform estimation framework for state of health of lithium-ion batteries considering feature extraction and parameters optimization," Energy, Elsevier, vol. 204(C).
- Mario Eduardo Carbonó dela Rosa & Graciela Velasco Herrera & Rocío Nava & Enrique Quiroga González & Rodolfo Sosa Echeverría & Pablo Sánchez Álvarez & Jaime Gandarilla Ibarra & Víctor Manuel Velasco H, 2023. "A New Methodology for Early Detection of Failures in Lithium-Ion Batteries," Energies, MDPI, vol. 16(3), pages 1-18, January.
- Sun, Zhenyu & Han, Yang & Wang, Zhenpo & Chen, Yong & Liu, Peng & Qin, Zian & Zhang, Zhaosheng & Wu, Zhiqiang & Song, Chunbao, 2022. "Detection of voltage fault in the battery system of electric vehicles using statistical analysis," Applied Energy, Elsevier, vol. 307(C).
- Yang, Jiong & Cheng, Fanyong & Liu, Zhi & Duodu, Maxwell Mensah & Zhang, Mingyan, 2023. "A novel semi-supervised fault detection and isolation method for battery system of electric vehicles," Applied Energy, Elsevier, vol. 349(C).
- Xiong, Rui & Sun, Wanzhou & Yu, Quanqing & Sun, Fengchun, 2020. "Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles," Applied Energy, Elsevier, vol. 279(C).
- Zhang, Zhendong & Kong, Xiangdong & Zheng, Yuejiu & Zhou, Long & Lai, Xin, 2019. "Real-time diagnosis of micro-short circuit for Li-ion batteries utilizing low-pass filters," Energy, Elsevier, vol. 166(C), pages 1013-1024.
- Zhu, Xiaoqing & Wang, Zhenpo & Wang, Yituo & Wang, Hsin & Wang, Cong & Tong, Lei & Yi, Mi, 2019. "Overcharge investigation of large format lithium-ion pouch cells with Li(Ni0.6Co0.2Mn0.2)O2 cathode for electric vehicles: Thermal runaway features and safety management method," Energy, Elsevier, vol. 169(C), pages 868-880.
- Ma, Mina & Li, Xiaoyu & Gao, Wei & Sun, Jinhua & Wang, Qingsong & Mi, Chris, 2022. "Multi-fault diagnosis for series-connected lithium-ion battery pack with reconstruction-based contribution based on parallel PCA-KPCA," Applied Energy, Elsevier, vol. 324(C).
- Xiang Wang & Jianjun He & Fuxin Huang & Zhenjie Liu & Aibin Deng & Rihui Long, 2024. "A Novel Voltage-Abnormal Cell Detection Method for Lithium-Ion Battery Mass Production Based on Data-Driven Model with Multi-Source Time Series Data," Energies, MDPI, vol. 17(14), pages 1-14, July.
- Chang, Chun & Wang, Qiyue & Jiang, Jiuchun & Jiang, Yan & Wu, Tiezhou, 2023. "Voltage fault diagnosis of a power battery based on wavelet time-frequency diagram," Energy, Elsevier, vol. 278(PB).
- Seunghwan Jung & Minseok Kim & Eunkyeong Kim & Baekcheon Kim & Jinyong Kim & Kyeong-Hee Cho & Hyang-A Park & Sungshin Kim, 2024. "The Early Detection of Faults for Lithium-Ion Batteries in Energy Storage Systems Using Independent Component Analysis with Mahalanobis Distance," Energies, MDPI, vol. 17(2), pages 1-23, January.
- Jeon, Jihun & Cheon, Hojin & Jung, Byungil & Kim, Hongseok, 2024. "ProADD: Proactive battery anomaly dual detection leveraging denoising convolutional autoencoder and incremental voltage analysis," Applied Energy, Elsevier, vol. 373(C).
- 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.
- Wang, Shuhui & Wang, Zhenpo & Cheng, Ximing & Zhang, Zhaosheng, 2023. "A double-layer fault diagnosis strategy for electric vehicle batteries based on Gaussian mixture model," Energy, Elsevier, vol. 281(C).
- Shen, Dongxu & Lyu, Chao & Yang, Dazhi & Hinds, Gareth & Wang, Lixin, 2023. "Connection fault diagnosis for lithium-ion battery packs in electric vehicles based on mechanical vibration signals and broad belief network," Energy, Elsevier, vol. 274(C).
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Keywords
Lithium ion battery safety; Fault detection; Series-connected; Connection fault;All these keywords.
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