标题/作者	年份
Maintenance, replacement, and reliability: theory and applications AKS Jardine, AHC Tsang CRC press	2021
Data-driven prediction of battery cycle life before capacity degradation KA Severson, PM Attia, N Jin, N Perkins, B Jiang, Z Yang, MH Chen, ... Nature Energy 4 (5), 383-391	2019
Battery lifetime prognostics X Hu, L Xu, X Lin, M Pecht Joule 4 (2), 310-346	2020
A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: Challenges and recommendations MSH Lipu, MA Hannan, A Hussain, MM Hoque, PJ Ker, MHM Saad, ... Journal of cleaner production 205, 115-133	2018
A data-driven approach with uncertainty quantification for predicting future capacities and remaining useful life of lithium-ion battery K Liu, Y Shang, Q Ouyang, WD Widanage IEEE Transactions on Industrial Electronics 68 (4), 3170-3180	2020
Lithium-ion battery health prognosis based on a real battery management system used in electric vehicles R Xiong, Y Zhang, J Wang, H He, S Peng, M Pecht IEEE Transactions on Vehicular Technology 68 (5), 4110-4121	2018
Remaining useful life prediction for lithium-ion batteries based on a hybrid model combining the long short-term memory and Elman neural networks X Li, L Zhang, Z Wang, P Dong Journal of Energy Storage 21, 510-518	2019
Gaussian process regression with automatic relevance determination kernel for calendar aging prediction of lithium-ion batteries K Liu, Y Li, X Hu, M Lucu, WD Widanage IEEE Transactions on Industrial Informatics 16 (6), 3767-3777	2019
Online state-of-health estimation for Li-ion battery using partial charging segment based on support vector machine X Feng, C Weng, X He, X Han, L Lu, D Ren, M Ouyang IEEE Transactions on Vehicular Technology 68 (9), 8583-8592	2019
Modified Gaussian process regression models for cyclic capacity prediction of lithium-ion batteries K Liu, X Hu, Z Wei, Y Li, Y Jiang IEEE Transactions on Transportation Electrification 5 (4), 1225-1236	2019
State-of-health estimation and remaining useful life prediction for the lithium-ion battery based on a variant long short term memory neural network P Li, Z Zhang, Q Xiong, B Ding, J Hou, D Luo, Y Rong, S Li Journal of power sources 459, 228069	2020
A comparison of methodologies for the non-invasive characterisation of commercial Li-ion cells A Barai, K Uddin, M Dubarry, L Somerville, A McGordon, P Jennings, ... Progress in Energy and Combustion Science 72, 1-31	2019
Failure prognosis and applications—A survey of recent literature M Kordestani, M Saif, ME Orchard, R Razavi-Far, K Khorasani IEEE transactions on reliability 70 (2), 728-748	2019
Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network G Ma, Y Zhang, C Cheng, B Zhou, P Hu, Y Yuan Applied Energy 253, 113626	2019
A neural-network-based method for RUL prediction and SOH monitoring of lithium-ion battery J Qu, F Liu, Y Ma, J Fan IEEE access 7, 87178-87191	2019
Intelligent algorithms and control strategies for battery management system in electric vehicles: Progress, challenges and future outlook MSH Lipu, MA Hannan, TF Karim, A Hussain, MHM Saad, A Ayob, ... Journal of Cleaner Production 292, 126044	2021
Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks J Hong, Z Wang, Y Yao Applied Energy 251, 113381	2019
A multimodal and hybrid deep neural network model for remaining useful life estimation A Al-Dulaimi, S Zabihi, A Asif, A Mohammadi Computers in industry 108, 186-196	2019
Remaining useful life prediction for supercapacitor based on long short-term memory neural network Y Zhou, Y Huang, J Pang, K Wang Journal of Power Sources 440, 227149	2019
A review on deep learning applications in prognostics and health management L Zhang, J Lin, B Liu, Z Zhang, X Yan, M Wei Ieee Access 7, 162415-162438	2019

1 - 20

计算机程序会自动估算并确定日期和引用次数。