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RUL Estimation Method for Lithium-ion Batteries Based on Multi-dimensional and Multi-scale Features
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Qiuyan Zhang1, Ze Cheng2, Xu Liu2
Automotive Engineering | 2024, 46(10) : 1897 - 1903
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Automotive Engineering | 2024, 46(10): 1897-1903
• Selected Papers •
RUL Estimation Method for Lithium-ion Batteries Based on Multi-dimensional and Multi-scale Features
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Qiuyan Zhang1, Ze Cheng2, Xu Liu2
Affiliations
  • 1. School of Energy Engineering, Yulin University, Yulin 719000
  • 2. School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300000
Published: 2024-10-25 doi: 10.19562/j.chinasae.qcgc.2024.10.016
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Accurately predicting the remaining useful life （RUL） of lithium-ion batteries is important for the efficient and safe operation of energy storage systems. For the deficiencies of existing data-driven methods for RUL estimation，which extract aging features non-comprehensively enough and need to predict health state changes before estimating RUL，a RUL estimation method using multi-dimensional and multi-scale features is proposed in this paper to directly estimate the RUL of a battery using constant-current charging voltage segment data. The model maps RUL by extracting aging features of voltage segments using different scale convolution operation after dimensionally transforming the data. The model is validated using publicly available datasets from the University of Oxford，NASA，and the University of Maryland. The validation results show that the model can directly estimate the RUL of the batteries using the voltage segment data without the need of the current historical SOH of the batteries as the training data，which has higher accuracy and universality compared to fixed scale features based on a single dimension.

lithium-ion battery  /  remaining useful life  /  multi-dimensional and multi-scale features  /  deep learning
Qiuyan Zhang, Ze Cheng, Xu Liu. RUL Estimation Method for Lithium-ion Batteries Based on Multi-dimensional and Multi-scale Features[J]. Automotive Engineering, 2024 , 46 (10) : 1897 -1903 . DOI: 10.19562/j.chinasae.qcgc.2024.10.016
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Article Info
doi: 10.19562/j.chinasae.qcgc.2024.10.016
  • Receive Date：2024-03-10
  • Online Date：2025-07-21
  • Published：2024-10-25
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  • Received：2024-03-10
  • Revised：2024-06-10
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Affiliations
    1. School of Energy Engineering, Yulin University, Yulin 719000
    2. School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300000
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表12种不同金属材料的力学参数
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Family		 属数
Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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