Online soft sensor of humidity in PEM fuel cell based on dynamic partial least squares.
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.
School of Automation, Wuhan University of Technology, Wuhan, Hubei 430070, China ; College of Science, Huazhong Agricultural University, Wuhan, Hubei 430070, China.
Rong
R
Long
School of Automation, Wuhan University of Technology, Wuhan, Hubei 430070, China.
Qihong
Q
Chen
School of Automation, Wuhan University of Technology, Wuhan, Hubei 430070, China.
Liyan
L
Zhang
School of Information Science and Engineering, Ningbo Institute of Technology, Zhejiang University, Ningbo, Zhejiang 315100, China.
Longhua
L
Ma
School of Automation, Wuhan University of Technology, Wuhan, Hubei 430070, China.
Shuhai
S
Quan
D011211:Electric Power Supplies; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods; D006813:Humidity; D008567:Membranes, Artificial; D009862:Online Systems / Q000295:instrumentation*
D008567:Membranes, Artificial