Validation of Neural Network-based Fault Diagnosis for Multi-stack Fuel Cell Systems: Stack Voltage Deviation Detection
Author:
Publisher
Elsevier BV
Reference9 articles.
1. Babu N, Arulmozhivarman P. Dynamic neural network based very short-term wind speed forecasting. Wind Engineering 2014; 38:121-128.
2. Sorrentino M, Marra D, Pianese C, Guida M, Postiglione F, Wang K, Pohjoranta A. On the use of neural networks and statistical tools for nonlinear modeling and on-field diagnosis of solid oxide fuel cell stacks. Energy Procedia 2014; 45:298-307.
3. Arsie I., Pianese C., Sorrentino M. Development and real-time implementation of recurrent neural networks for AFR prediction and control. SAE International Journal of Passenger Cars - Electronic and Electrical Systems 2009; 1:403-412.
4. Nørgaard M, Ravn O, Poulsen NL, Hansen LK. Neural Networks for Modelling and Control of Dynamic Systems. London: Springer-Verlag; 2000.
5. Noponen M, Hottinen T. WFC20 Biogas Unit Operation. Proceedings of the 9th European Solid Oxide Fuel Cell Forum (2010), (pp. 2-90--2-97). Lucerne, Switzerland.
Cited by 21 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. Modeling and analysis of the multiphysics transport parameters of a kilowatt-class multistack module of reversible solid oxide cells;Applied Thermal Engineering;2023-11
2. Recent progress and challenges of multi-stack fuel cell systems: Fault detection and reconfiguration, energy management strategies, and applications;Energy Conversion and Management;2023-06
3. Progress and challenges in multi-stack fuel cell system for high power applications: Architecture and energy management;Green Energy and Intelligent Transportation;2023-04
4. Structural Design, Matching, and Analysis of Air Supply Devices for Multi‐Stack Fuel Cell Systems;Energy Technology;2023-01-18
5. Generalized Spatial–Temporal Fault Location Method for Solid Oxide Fuel Cells Using LSTM and Causal Inference;IEEE Transactions on Transportation Electrification;2022-12
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3