Model-based humidity observer for vehicle proton exchange membrane fuel cell based on a new sliding mode observer estimation technique

The internal water content of the proton exchange membrane fuel cell (PEMFC) stack significantly affects its performance and duration. To achieve optimal humidity level, real-time monitoring of the humidity of the cathode and the anode is crucial for the PEMFC. As far as we know, the relative humidity of the PEMFC can be estimated via an observer based on the measurable output voltage. However, the rapid changes in vehicle operating conditions pose a challenge to the estimation accuracy. Different from the existing sliding mode observers (SMOs), this study pays more attention to the testing noise of voltage measuring sensor. To reduce the noise influence and improve the estimation accuracy, a new sliding mode observer (NSMO) combined with an online Kalman filter is presented based on the dimensionless model of the PEMFC in this study. The applicability of the proposed NSMO in estimating the cathode relative humidity and the anode relative humidity is illustrated by the simulation results. At the same time, comparisons between the NSMO and the online Kalman filter are provided which show a substantially higher estimation accuracy and lower cost for the NSMO. Furthermore, the final results indicate the mean absolute deviations of the cathode and the anode relative humidity for the NSMO are, respectively, reduced to 0.39% and 0.28%.

Authors

Institutions

Publication Details

Journal
International Journal of Green Energy
Published
2024-08-26
DOI
https://doi.org/10.1080/15435075.2024.2392176
Citations
2
Primary Topic
Fuel Cells and Related Materials
Type
article
Field-Weighted Citation Impact
0.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Model-based humidity observer for vehicle proton exchange membrane fuel cell based on a new sliding mode observer estimation technique

Haibo Huo, Yilei Yao, Fang Wang, Binbin Li et al.
2 citations
International Journal of Green Energy
Fuel Cells and Related Materials
0.42
article

Model-based humidity observer for vehicle proton exchange membrane fuel cell based on a new sliding mode observer estimation technique

Haibo Huo, Yilei Yao, Fang Wang, Binbin Li, Jiwei Xu, Ke Wang
article en
2 citations

Abstract

The internal water content of the proton exchange membrane fuel cell (PEMFC) stack significantly affects its performance and duration. To achieve optimal humidity level, real-time monitoring of the humidity of the cathode and the anode is crucial for the PEMFC. As far as we know, the relative humidity of the PEMFC can be estimated via an observer based on the measurable output voltage. However, the rapid changes in vehicle operating conditions pose a challenge to the estimation accuracy. Different from the existing sliding mode observers (SMOs), this study pays more attention to the testing noise of voltage measuring sensor. To reduce the noise influence and improve the estimation accuracy, a new sliding mode observer (NSMO) combined with an online Kalman filter is presented based on the dimensionless model of the PEMFC in this study. The applicability of the proposed NSMO in estimating the cathode relative humidity and the anode relative humidity is illustrated by the simulation results. At the same time, comparisons between the NSMO and the online Kalman filter are provided which show a substantially higher estimation accuracy and lower cost for the NSMO. Furthermore, the final results indicate the mean absolute deviations of the cathode and the anode relative humidity for the NSMO are, respectively, reduced to 0.39% and 0.28%.

International Journal of Green EnergyVol. 21(15)
Wuhan Ship Development & Design Institute (CN), Shanghai Ocean University (CN)
Clean water and sanitation
Openalex Percentile: Top 38%
Fuel Cells and Related Materials
0.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.