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Remaining Useful Life Prediction of Lithium-Ion Batteries Based on the Wiener Process with Measurement Error

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Cited by:

  1. Ye, Zhenggeng & Cai, Zhiqiang & Zhou, Fuli & Zhao, Jiangbin & Zhang, Pan, 2019. "Reliability analysis for series manufacturing system with imperfect inspection considering the interaction between quality and degradation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 345-356.
  2. Xiaodong Xu & Chuanqiang Yu & Shengjin Tang & Xiaoyan Sun & Xiaosheng Si & Lifeng Wu, 2019. "Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Wiener Processes with Considering the Relaxation Effect," Energies, MDPI, vol. 12(9), pages 1-17, May.
  3. Jingxi Yang & Matthew Beatty & Dani Strickland & Mina Abedi-Varnosfaderani & Joe Warren, 2023. "Second-Life Battery Capacity Estimation and Method Comparison," Energies, MDPI, vol. 16(7), pages 1-17, April.
  4. Zhu, Wenhao & Lei, Fei & Zhong, Hao & Wang, Dongjie, 2023. "An improved reliability assessment method for lithium-ion battery system considering imbalanced current and uneven cooling," Energy, Elsevier, vol. 276(C).
  5. Wu, Ji & Zhang, Chenbin & Chen, Zonghai, 2016. "An online method for lithium-ion battery remaining useful life estimation using importance sampling and neural networks," Applied Energy, Elsevier, vol. 173(C), pages 134-140.
  6. Shuai Wang & Lingling Zhao & Xiaohong Su & Peijun Ma, 2014. "Prognostics of Lithium-Ion Batteries Based on Battery Performance Analysis and Flexible Support Vector Regression," Energies, MDPI, vol. 7(10), pages 1-17, October.
  7. Wang, Xiaofei & Wang, Bing Xing & Jiang, Pei Hua & Hong, Yili, 2020. "Accurate reliability inference based on Wiener process with random effects for degradation data," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
  8. Thelen, Adam & Li, Meng & Hu, Chao & Bekyarova, Elena & Kalinin, Sergey & Sanghadasa, Mohan, 2022. "Augmented model-based framework for battery remaining useful life prediction," Applied Energy, Elsevier, vol. 324(C).
  9. Zhai, Qingqing & Chen, Piao & Hong, Lanqing & Shen, Lijuan, 2018. "A random-effects Wiener degradation model based on accelerated failure time," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 94-103.
  10. Hu, Yaogang & Li, Hui & Shi, Pingping & Chai, Zhaosen & Wang, Kun & Xie, Xiangjie & Chen, Zhe, 2018. "A prediction method for the real-time remaining useful life of wind turbine bearings based on the Wiener process," Renewable Energy, Elsevier, vol. 127(C), pages 452-460.
  11. Song, Kai & Shi, Jian & Yi, Xiaojian, 2020. "A time-discrete and zero-adjusted gamma process model with application to degradation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
  12. Yu, Jianbo, 2018. "State of health prediction of lithium-ion batteries: Multiscale logic regression and Gaussian process regression ensemble," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 82-95.
  13. Liu, Kai & Wang, Jiangbo & Yamamoto, Toshiyuki & Morikawa, Takayuki, 2018. "Exploring the interactive effects of ambient temperature and vehicle auxiliary loads on electric vehicle energy consumption," Applied Energy, Elsevier, vol. 227(C), pages 324-331.
  14. Taichun Qin & Shengkui Zeng & Jianbin Guo & Zakwan Skaf, 2016. "A Rest Time-Based Prognostic Framework for State of Health Estimation of Lithium-Ion Batteries with Regeneration Phenomena," Energies, MDPI, vol. 9(11), pages 1-18, November.
  15. Zhang, Caiping & Wang, Yubin & Gao, Yang & Wang, Fang & Mu, Biqiang & Zhang, Weige, 2019. "Accelerated fading recognition for lithium-ion batteries with Nickel-Cobalt-Manganese cathode using quantile regression method," Applied Energy, Elsevier, vol. 256(C).
  16. Shengjin Tang & Xiaosong Guo & Zhijie Zhou, 2014. "Mis-specification analysis of linear Wiener process–based degradation models for the remaining useful life estimation," Journal of Risk and Reliability, , vol. 228(5), pages 478-487, October.
  17. Ma, Guijun & Zhang, Yong & Cheng, Cheng & Zhou, Beitong & Hu, Pengchao & Yuan, Ye, 2019. "Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
  18. Zhai, Qingqing & Ye, Zhi-Sheng & Yang, Jun & Zhao, Yu, 2016. "Measurement errors in degradation-based burn-in," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 126-135.
  19. Muhammad Umair Ali & Amad Zafar & Sarvar Hussain Nengroo & Sadam Hussain & Gwan-Soo Park & Hee-Je Kim, 2019. "Online Remaining Useful Life Prediction for Lithium-Ion Batteries Using Partial Discharge Data Features," Energies, MDPI, vol. 12(22), pages 1-14, November.
  20. Ding, Pan & Liu, Xiaojuan & Li, Huiqin & Huang, Zequan & Zhang, Ke & Shao, Long & Abedinia, Oveis, 2021. "Useful life prediction based on wavelet packet decomposition and two-dimensional convolutional neural network for lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
  21. Jianxun Zhang & Xiao He & Xiaosheng Si & Changhua Hu & Donghua Zhou, 2017. "A Novel Multi-Phase Stochastic Model for Lithium-Ion Batteries’ Degradation with Regeneration Phenomena," Energies, MDPI, vol. 10(11), pages 1-24, October.
  22. Xu, Xiaodong & Tang, Shengjin & Yu, Chuanqiang & Xie, Jian & Han, Xuebing & Ouyang, Minggao, 2021. "Remaining Useful Life Prediction of Lithium-ion Batteries Based on Wiener Process Under Time-Varying Temperature Condition," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
  23. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
  24. Yuan Chen & Yigang He & Zhong Li & Liping Chen, 2019. "A Combined Multiple Factor Degradation Model and Online Verification for Electric Vehicle Batteries," Energies, MDPI, vol. 12(22), pages 1-12, November.
  25. Liu, Di & Wang, Shaoping, 2021. "Reliability estimation from lifetime testing data and degradation testing data with measurement error based on evidential variable and Wiener process," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
  26. 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).
  27. Xiangang Cao & Pengfei Li & Song Ming, 2021. "Remaining Useful Life Prediction-Based Maintenance Decision Model for Stochastic Deterioration Equipment under Data-Driven," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
  28. Wang, Zhijie & Zhai, Qingqing & Chen, Piao, 2021. "Degradation modeling considering unit-to-unit heterogeneity-A general model and comparative study," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
  29. Jiangbo Wang & Kai Liu & Toshiyuki Yamamoto, 2017. "Improving Electricity Consumption Estimation for Electric Vehicles Based on Sparse GPS Observations," Energies, MDPI, vol. 10(1), pages 1-12, January.
  30. Shuming Wang & Yan-Fu Li & Tong Jia, 2020. "Distributionally Robust Design for Redundancy Allocation," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 620-640, July.
  31. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
  32. Yongma Moon, 2014. "Optimal Time to Invest Energy Storage System under Uncertainty Conditions," Energies, MDPI, vol. 7(4), pages 1-19, April.
  33. Moon, Yongma & Baran, Mesut, 2018. "Economic analysis of a residential PV system from the timing perspective: A real option model," Renewable Energy, Elsevier, vol. 125(C), pages 783-795.
  34. Paulino José García Nieto & Esperanza García-Gonzalo & Antonio Bernardo Sánchez & Marta Menéndez Fernández, 2016. "A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines," Energies, MDPI, vol. 9(6), pages 1-19, May.
  35. Tianyu Liu & Zhengqiang Pan & Quan Sun & Jing Feng & Yanzhen Tang, 2017. "Residual useful life estimation for products with two performance characteristics based on a bivariate Wiener process," Journal of Risk and Reliability, , vol. 231(1), pages 69-80, February.
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