Voltage fault diagnosis and misdiagnosis analysis of battery systems using the modified Shannon entropy in real-world electric vehicles
Tài liệu tham khảo
Lu, 2013, A review on the key issues for lithium-ion battery management in electric vehicles, J. Power Sources, 226, 272, 10.1016/j.jpowsour.2012.10.060
Wang, 2016, Lithium-ion battery structure that self-heats at low temperatures, Nature, 529, 515, 10.1038/nature16502
Jaguemont, 2016, A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures, Appl. Energy, 164, 99, 10.1016/j.apenergy.2015.11.034
Wang, 2012, Thermal runaway caused fire and explosion of lithium ion battery, J. Power Sources, 208, 210, 10.1016/j.jpowsour.2012.02.038
Hannan, 2017, A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: challenges and recommendations, Renew. Sust. Energ. Rev., 78, 834, 10.1016/j.rser.2017.05.001
Wu, 2015, A review on fault mechanism and diagnosis approach for Li-ion batteries, J. Nanomater., 2015, 10.1155/2015/631263
Rahimi-Eichi, 2013, Battery management system: an overview of its application in the smart grid and electric vehicles, IEEE Ind. Electron. Mag., 7, 4, 10.1109/MIE.2013.2250351
Kang, 2020, Online multi-fault detection and diagnosis for battery packs in electric vehicles, Appl. Energy, 259
Xiong, 2019, A sensor fault diagnosis method for a Lithium-ion battery pack in electric vehicles, IEEE Trans. Power Electron., 34, 9709, 10.1109/TPEL.2019.2893622
Xu, 2020, Detection technology for battery safety in electric vehicles: a review, Energies, 13, 10.3390/en13184636
Panchal, 2018, Design and simulation of a lithium-ion battery at large C-rates and varying boundary conditions through heat flux distributions, Meas. J. Int. Meas. Confed., 116, 382, 10.1016/j.measurement.2017.11.038
Li, 2022, A novel method for Lithium-ion battery fault diagnosis of electric vehicle based on real-time voltage, Wirel. Commun. Mob. Comput., 2022
Yokoshima, 2018, Direct observation of internal state of thermal runaway in lithium ion battery during nail-penetration test, J. Power Sources, 393, 67, 10.1016/j.jpowsour.2018.04.092
Finegan, 2019, Modelling and experiments to identify high-risk failure scenarios for testing the safety of lithium-ion cells, J. Power Sources, 417, 29, 10.1016/j.jpowsour.2019.01.077
Han, 2014, Cycle life of commercial lithium-ion batteries with lithium titanium oxide anodes in electric vehicles, Energies, 7, 4895, 10.3390/en7084895
Feng, 2014, Characterization of large format lithium ion battery exposed to extremely high temperature, J. Power Sources, 272, 457, 10.1016/j.jpowsour.2014.08.094
Li, 2020, Swelling force in Lithium-ion power batteries, Ind. Eng. Chem. Res., 59, 12313, 10.1021/acs.iecr.0c01035
Zhao, 2016, Simulation and experimental study on lithium ion battery short circuit, Appl. Energy, 173, 29, 10.1016/j.apenergy.2016.04.016
Xia, 2014, External short circuit fault diagnosis for lithium-ion batteries, 2014
Liu, 2022, Fault diagnosis for battery systems based on voltage frequency-domain indicator and abnormal coefficient, China J. Highw. Transp., 35, 89
Yu, 2019, Model-based sensor fault detection for lithium-ion batteries in electric vehicles, IEEE Veh. Technol. Conf.
Sidhu, 2015, Adaptive nonlinear model-based fault diagnosis of li-ion batteries, IEEE Trans. Ind. Electron., 62, 1002, 10.1109/TIE.2014.2336599
Dey, 2016, Model-based real-time thermal fault diagnosis of Lithium-ion batteries, Control. Eng. Pract., 56, 37, 10.1016/j.conengprac.2016.08.002
Dey, 2019, Model-based battery thermal fault diagnostics: algorithms, analysis, and experiments, IEEE Trans. Control Syst. Technol., 27, 576, 10.1109/TCST.2017.2776218
Wang, 2017, Voltage fault diagnosis and prognosis of battery systems based on entropy and Z-score for electric vehicles, Appl. Energy, 196, 289, 10.1016/j.apenergy.2016.12.143
Sun, 2022, Modified relative entropy-based Lithium-ion battery pack online short-circuit detection for electric vehicle, IEEE Trans. Transp. Electrif., 8, 1710, 10.1109/TTE.2021.3128048
Hu, 2014, Enhanced sample entropy-based health management of Li-ion battery for electrified vehicles, Energy, 64, 953, 10.1016/j.energy.2013.11.061
Zhang, 2019, Intelligent simultaneous fault diagnosis for solid oxide fuel cell system based on deep learning, Appl. Energy, 233–234, 930, 10.1016/j.apenergy.2018.10.113
Hong, 2019, Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks, Appl. Energy, 251, no. January
Xu, 2021, Estimation and prediction of state of health of electric vehicle batteries using discrete incremental capacity analysis based on real driving data, Energy, 225, 10.1016/j.energy.2021.120160
Li, 2020, Digital twin for battery systems: cloud battery management system with online state-of-charge and state-of-health estimation, J. Energy Storage, 30, no. May
Zhang, 2020, Cloud computing-based real-time global optimization of battery aging and energy consumption for plug-in hybrid electric vehicles, J. Power Sources, 479
Liu, 2022, An incentive mechanism for sustainable Blockchain storage, IEEE/ACM Trans. Netw., 30, 2131, 10.1109/TNET.2022.3166459
Pack, 2023, OCV-SOC-temperature relationship construction and state of charge estimation for a series – parallel lithium-ion battery pack, IEEE Trans. Intell. Transp. Syst., 24, 6362, 10.1109/TITS.2023.3252164
Liu, 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, 283
Tang, 2023, A hybrid neural network model with attention mechanism for state of health estimation of lithium-ion batteries, J. Energy Storage, 68
Tang, 2023, A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models, Appl. Energy, 348
Liu, 2023, Abnormal voltage detection of battery for electric vehicles based on value rate model, Automot. Eng., 45, 1728
