LAPSE:2023.14019
Published Article
LAPSE:2023.14019
Research on Application Characteristics of Zirconia-Based High-Temperature NOx Sensors
Jie Wang, Xi Li, Zhen Wang, Jiangtao Feng, Weixun Lin, Jingxuan Peng
March 1, 2023
Abstract
The zirconia solid electrolyte SOFC (solid oxide fuel cell) has the characteristics of oxygen ion conduction function, high-temperature resistance, thermoelectric coupling effect, etc. A NOx sensor based on zirconia solid electrolyte has common characteristics and problems with the SOFC in principle and application. The research objective of this paper is to solve the application problems of smart NOx sensors in diesel vehicles or gasoline vehicles. Improvements in the application performance of the NOx sensor can help the NOx emissions of gasoline vehicles or diesel vehicles better meet the requirements of emission regulations. The smart NOx sensor is a regulatory sensor required by vehicles for China’s Phase VI Vehicle Exhaust Emission Regulations or Euro Phase VI Vehicle Exhaust Emission Regulations. The smart NOx sensor is a key sensor device for improving fuel efficiency and reducing pollution. Moreover, its measurement performance includes dynamic immunity to interference, response speed, and measurement accuracy, which are key factors affecting vehicle emissions. This paper focuses on the impact of the physical structure, electrode characteristics, and control strategies of the sensor on its performance during the application. An excellent sensor structure, electrode structure, and control strategy are given based on application analysis and experimental testing. The results show that the application performance of this smart NOx sensor meets the requirements of exhaust aftertreatment systems.
Keywords
electrode activity, exhaust gas, NOx measurement accuracy, NOx sensor, response speed, SOFC, vehicle test
Suggested Citation
Wang J, Li X, Wang Z, Feng J, Lin W, Peng J. Research on Application Characteristics of Zirconia-Based High-Temperature NOx Sensors. (2023). LAPSE:2023.14019
Author Affiliations
Wang J: Changzhou Lambda Electronic Co., Ltd., Changzhou 213161, China [ORCID]
Li X: School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Technology Research Institute, Shenzhen Huazhong University of Science, Shenzhen 518055, China
Wang Z: School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Feng J: Changzhou Lambda Electronic Co., Ltd., Changzhou 213161, China
Lin W: School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Peng J: School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China [ORCID]
Journal Name
Energies
Volume
15
Issue
8
First Page
2919
Year
2022
Publication Date
2022-04-15
ISSN
1996-1073
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Original Submission
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PII: en15082919, Publication Type: Journal Article
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LAPSE:2023.14019
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https://doi.org/10.3390/en15082919
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