Two-dimensional temperature distribution estimation for a cross-flow planar solid oxide fuel cell stack |
| |
Affiliation: | 1. School of Artificial Intelligence and Automation, Key Laboratory of Education Ministry for Image Processing and Intelligent Control, Huazhong University of Science & Technology, Wuhan, 430074, China;2. China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan, 430074, China;3. School of Materials Science and Engineering, State Key Laboratory of Material Processing and Dye and Mold Technology, Huazhong University of Science and Technology, Wuhan, 430074, China;1. Key Laboratory of Magnetic Molecules & Magnetic Information Materials Ministry of Education, Shanxi Normal University, Linfen, 041004, China;2. The School of Chemical and Material Science, Shanxi Normal University, No. 1, Gongyuan Street, Linfen, 041004, China;1. School of Artificial Intelligence and Automation, Key Laboratory of Education Ministry for Image Processing and Intelligent Control, Huazhong University of Science & Technology, Wuhan 430074, China;2. China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, China;3. School of Materials Science and Engineering, State Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science & Technology, 430074 Wuhan, Hubei, China;1. School of Artificial Intelligence and Automation, Key Laboratory of Imaging Processing and Intelligent Control, Huazhong University of Science and Technology, 430074 Wuhan, Hubei, China;2. College of Computer Science and Technology, Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, 430081 Wuhan, Hubei, China;1. School of Artificial Intelligence and Automation, Key Laboratory of Education Ministry for Image Processing and Intelligent Control, Huazhong University of Science & Technology, Wuhan 430074, China;2. School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430065, China;1. Jožef Stefan Institute, Department of Systems and Control, Jamova cesta 39, SI-1000 Ljubljana, Slovenia;2. VTT, Technical Research Centre of Finland, Espoo, Finland;3. Department of Industrial Engineering, Universita degli Studi di Salerno, Fisciano, Italy;4. Jožef Stefan International Postgraduate School, Jamova cesta 39, SI-1000 Ljubljana, Slovenia;1. School of Artificial Intelligence and Automation, Key Laboratory of Image Processing and Intelligent Control of Education Ministry, Huazhong University of Science and Technology, 430074 Wuhan, Hubei, China;2. College of Computer Science and Technology, Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, 430081 Wuhan, Hubei, China |
| |
Abstract: | The uniform temperature distribution of a cross-flow planar solid oxide fuel cell (SOFC) stack plays an essential role in stack thermal safety and electrical property. However, because of the strict requirements in stack sealing struture, it is hard to acquire the temperature inside the stack using thermal detection devices within an acceptable cost. Therefore, accurately estimating the two-dimensional (2-D) temperature distribution of the cross-flow stack is crucial for its thermal management. In this paper, Firstly, a 2-D mechanism model of a cross-flow planar SOFC stack is established. The stack is divided into 5*5 nodes along the gas flow directions, which can reflect the stack states with moderate computational burden. Then, experimental test data is utilized to modify and validate the stack model, guaranteeing the model accuracy as well as the reliability of model-based state estimator design. Finally, easily-measured stack inputs and outputs are selected, and a temperature distribution estimator combined with unscented kalman filter (UFK) approach is developed to achieve accurate and fast temperature distribution estimation of a cross-flow SOFC stack. Simulation results demonstrate that the UKF-based temperature distribution estimator can precisely and quickly achieve the temperature distribution estimation of the cross-flow stack under both static state and dynamic state changes and is applicable to cross-flow stacks with different size or cell number as well, the maximum estimated absolute error is less than 0.15 K with an absolute error rate of 0.015%, which indicates the developed estimator has good estimation performances. |
| |
Keywords: | Cross-flow SOFC stack Modeling and validation Unscented kalman filter Temperature distribution estimation |
本文献已被 ScienceDirect 等数据库收录! |
|