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The Scientific World Journal
Volume 2013, Article ID 923901, 11 pages
Research Article

Online Soft Sensor of Humidity in PEM Fuel Cell Based on Dynamic Partial Least Squares

1School of Automation, Wuhan University of Technology, Wuhan, Hubei 430070, China
2College of Science, Huazhong Agricultural University, Wuhan, Hubei 430070, China
3School of Information Science and Engineering, Ningbo Institute of Technology, Zhejiang University, Ningbo, Zhejiang 315100, China

Received 19 September 2013; Accepted 23 October 2013

Academic Editors: A. Acir, G. Quan, and A. F. Zobaa

Copyright © 2013 Rong Long et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Online monitoring humidity in the proton exchange membrane (PEM) fuel cell is an important issue in maintaining proper membrane humidity. The cost and size of existing sensors for monitoring humidity are prohibitive for online measurements. Online prediction of humidity using readily available measured data would be beneficial to water management. In this paper, a novel soft sensor method based on dynamic partial least squares (DPLS) regression is proposed and applied to humidity prediction in PEM fuel cell. In order to obtain data of humidity and test the feasibility of the proposed DPLS-based soft sensor a hardware-in-the-loop (HIL) test system is constructed. The time lag of the DPLS-based soft sensor is selected as 30 by comparing the root-mean-square error in different time lag. The performance of the proposed DPLS-based soft sensor is demonstrated by experimental results.