Online temperature estimation of Shell coal gasification process based on extended Kalman filter
Full Length Article|Updated:2026-01-06
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Online temperature estimation of Shell coal gasification process based on extended Kalman filter
Chinese Journal of Chemical EngineeringVol. 47, Issue 7, Pages: 134-144(2022)
Affiliations:
1. Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University,Beijing,China,100084
2. School of Engineering, Merz Court, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom
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Published:2022
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Kangcheng Wang, Jie Zhang, Dexian Huang. Online temperature estimation of Shell coal gasification process based on extended Kalman filter[J]. Chinese Journal of Chemical Engineering, 2022, 47(7): 134-144.
DOI:
Kangcheng Wang, Jie Zhang, Dexian Huang. Online temperature estimation of Shell coal gasification process based on extended Kalman filter[J]. Chinese Journal of Chemical Engineering, 2022, 47(7): 134-144.DOI:
Online temperature estimation of Shell coal gasification process based on extended Kalman filter
Obtaining the temperature inside the gasifier of a Shell coal gasification process (SCGP) in real-time is very important for safe process operation. However
this temperature cannot be measured directly due to the harsh operating condition. Estimating this temperature using the extended Kalman filter (EKF) based on a simplified mechanistic model is proposed in this paper. The gasifier is partitioned into three zones. The quench pipe and the transfer duct are seen as two additional zones. A simplified mechanistic model is developed in each zone and formulated as a state-space representation. The temperature in each zone is estimated by the EKF in real-time. The proposed method is applied to an industrial SCGP and the effectiveness of the estimated temperatures is verified by a process variable both qualitatively and quantitatively. The prediction capability of the simplified mechanistic model is validated. The effectiveness of the proposed method is further verified by comparing it to a Kalman filter-based single-zone temperature estimation method.
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