Fault and defect diagnosis of battery for electric vehicles based on big data analysis methods-Reference-Cited by-同舟云学术

Fault and defect diagnosis of battery for electric vehicles based on big data analysis methods

Published:2017-12 Issue: Volume:207 Page:354-362
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Zhao Yang,Liu Peng,Wang Zhenpo,Zhang Lei,Hong Jichao

Funder

State Key Program of National Natural Science Foundation of China

Application and Demonstration of Innovative Methods in New Energy Vehicle Industry

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference29 articles.

1. Battery durability and longevity based power management for plug-in hybrid electric vehicle with hybrid energy storage system;Zhang;Appl Energy,2016

2. A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures;Jaguemont;Appl Energy,2016

3. State-of-health estimation of lithium-ion battery packs in electric vehicles based on genetic resampling particle filter;Bi;Appl Energy,2016

4. Individual trip chain distributions for passenger cars: Implications for market acceptance of battery electric vehicles and energy consumption by plug-in hybrid electric vehicles;Xiaoyi;Appl Energy,2016

5. A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique;Sun;Appl Energy,2016

Cited by 251 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Empowering lithium-ion battery manufacturing with big data: Current status, challenges, and future;Journal of Power Sources;2024-12

2. An intelligent diagnosis method for battery pack connection faults based on multiple correlation analysis and adaptive fusion decision-making;Energy;2024-10

3. Improvement of local outlier factor algorithms for lithium-ion battery fault diagnosis;Journal of Energy Storage;2024-09

4. SDANet: Sub-domain adaptive network for multi-fault diagnosis of lithium-ion battery packs;Journal of Energy Storage;2024-09

5. Progress on the Fault Diagnosis Approach for Lithium-ion Battery Systems: Advances, Challenges, and Prospects;Protection and Control of Modern Power Systems;2024-09