Power Switching Based on Trajectory Planning and Sliding Mode Control for Solid Oxide Fuel Cell Systems

被引:0
|
作者
Zhen Wang [1 ]
Guoqiang Liu [1 ]
Xingbo Liu [2 ]
Jie Wang [1 ]
Zhiyang Jin [1 ]
Xiaowei Fu [3 ]
Zhuo Wang [1 ]
Bing Jin [2 ]
Zhonghua Deng [4 ,5 ]
Xi Li [1 ,6 ]
机构
[1] the Key Laboratory of Imaging Processing and Intelligent Control of Ministry of Education, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology
[2] the Hubei Huazhong Electric Power Technology Development Co, Ltd
[3] the School of Computer Science and Technology, Wuhan University of Science and Technology
[4] the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology
[5] the Wuhan Huamao Automation Co, Ltd
[6] the Research Institute of Huazhong University of Science and Technology in
关键词
D O I
暂无
中图分类号
TM911.4 [燃料电池]; TP273 [自动控制、自动控制系统];
学科分类号
080201 ; 0835 ;
摘要
To improve the safety of the solid oxide fuel cell(SOFC) systems and avoid the generation of large amounts of pollutants during power switching, this paper designs a power switching strategy based on trajectory planning and sliding mode control(TP-SMC). The design elements of the power switching strategy are proposed through simulation analysis at first. Then, based on the gas transmission delay time and the change of gas flow obtained from testing, trajectory planning(TP) is implemented. Compared with other power switching strategies, it has been proven that the power switching strategy based on TP has significantly better control performance. Furthermore, considering the shortcomings and problems of TP in practical application, this paper introduces sliding mode control(SMC) on the basis of TP to improve the power switching strategy. The final simulation results also prove that the TP-SMC can effectively suppress the impact of uncertainty in gas flow and gas transmission delay time. Compared with TP, TP-SMC can ensure that under uncertain conditions, the SOFC system does not experience fuel starvation and temperature exceeding limit during power switching. Meanwhile, the NOx emissions are also within the normal and acceptable range. This paper can guide the power switching process of the actual SOFC systems to avoid safety issues and excessive generation of NOx, which is very helpful for improving the performance and service life of the SOFC systems.
引用
收藏
页码:1968 / 1979
页数:12
相关论文
共 50 条
  • [21] Nonlinear model predictive control for mode-switching operation of reversible solid oxide cell systems
    Li, Mingrui
    Allan, Douglas A.
    Dinh, San
    Bhattacharyya, Debangsu
    Dabadghao, Vibhav
    Giridhar, Nishant
    Zitney, Stephen E.
    Biegler, Lorenz T.
    AICHE JOURNAL, 2024, 70 (11)
  • [22] Fuzzy Integral Sliding Mode Control Based on Microbial Fuel Cell
    Lian, Lei
    Ji, Peng
    OuYang, Tianyu
    Ma, Fengying
    Xu, Shanwen
    Gao, Chao
    Liu, Jing
    COMPLEXITY, 2021, 2021
  • [23] A Novel Adaptive Model Predictive Control Strategy of Solid Oxide Fuel Cell in Power Systems
    Liu, Yulin
    Chau, Tat Kei
    Zhang, Xinan
    Iu, Herbert
    Fernando, Tyrone
    Li, Ran
    Hu, Yingjie
    PROCEEDINGS OF 2021 31ST AUSTRALASIAN UNIVERSITIES POWER ENGINEERING CONFERENCE (AUPEC), 2021,
  • [24] Sliding Mode Integral Separation PID Control for Hydrogen Fuel Cell Systems
    Yu, Qingrui
    Wang, Jun
    Huang, Wenhui
    Li, Xiaoning
    Liu, Zenghui
    Dong, Haiying
    APPLIED SCIENCES-BASEL, 2024, 14 (17):
  • [25] Power Split of Fuel Cell/Ultracapacitor Hybrid Power System by Backstepping Sliding Mode Control
    Lee, Chao-Ming
    Han, Shin-Han
    Zheng, Chen-Hong
    Lin, We-Song
    2012 CONFERENCE ON POWER & ENERGY - IPEC, 2012, : 538 - 543
  • [26] Modeling and Control of Solid Oxide Fuel cell With Predictive Power Control Method
    Kanani, Heidar
    Gorji, Jafar Gholami
    Abbaszadeh, K.
    2020 11TH POWER ELECTRONICS, DRIVE SYSTEMS, AND TECHNOLOGIES CONFERENCE (PEDSTC), 2020,
  • [27] A learning-based sliding mode control for switching systems with dead zone
    Wang, Bo
    Zou, Fucheng
    Wu, Junhui
    Cheng, Jun
    APPLIED MATHEMATICS AND COMPUTATION, 2025, 494
  • [28] Control of fuel cell-based electric power system using adaptive sliding mode control and observation techniques
    Ashok, Roshini
    Shtessel, Yuri
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2015, 352 (11): : 4911 - 4934
  • [29] Solid oxide fuel cell systems for distributed power generation and cogeneration
    Verda, Vittorio
    Quaglia, Michele Cali
    INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2008, 33 (08) : 2087 - 2096
  • [30] Performance comparison of three solid oxide fuel cell power systems
    Jia, Junxi
    Abudula, Abuliti
    Wei, Liming
    Shi, Yue
    INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2013, 37 (14) : 1821 - 1830