Prediction Model of the Mechanical Behavior of a Fuel Cell Stack under Strengthened Road Vibrating Conditions

In this paper, a data-oriented model has been presented by nonlinear autoregressive exogenous model (NARX) neural network, which aims at predicting the mechanical behavior of a fuel cell stack for vehicle under the real-life operational conditions. A 300-hour vibration test with reproduction of SVP...

Full description

Saved in:
Bibliographic Details
Main Authors: Liying Ma, Bo Lv, Yongping Hou, Xiangmin Pan
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Modelling and Simulation in Engineering
Online Access:http://dx.doi.org/10.1155/2021/6671547
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849406540277088256
author Liying Ma
Bo Lv
Yongping Hou
Xiangmin Pan
author_facet Liying Ma
Bo Lv
Yongping Hou
Xiangmin Pan
author_sort Liying Ma
collection DOAJ
description In this paper, a data-oriented model has been presented by nonlinear autoregressive exogenous model (NARX) neural network, which aims at predicting the mechanical behavior of a fuel cell stack for vehicle under the real-life operational conditions. A 300-hour vibration test with reproduction of SVP road spectrum was completed on a Multi-Axial Simulation Table. At the same time, data acquisition of drive displacement and acceleration response on stack was carried out in every 50 hours. All data collected were used to train and evaluate the model based on NARX. Result shows that the prediction model built is of good precision and consistent with the actual situation.
format Article
id doaj-art-4d4d064570634c0a9f7832b4f495e2af
institution Kabale University
issn 1687-5591
1687-5605
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Modelling and Simulation in Engineering
spelling doaj-art-4d4d064570634c0a9f7832b4f495e2af2025-08-20T03:36:21ZengWileyModelling and Simulation in Engineering1687-55911687-56052021-01-01202110.1155/2021/66715476671547Prediction Model of the Mechanical Behavior of a Fuel Cell Stack under Strengthened Road Vibrating ConditionsLiying Ma0Bo Lv1Yongping Hou2Xiangmin Pan3Lab of Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, ChinaLab of Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, ChinaLab of Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, ChinaShanghai Motor Vehicle Inspection Certification & Technology Innovation Center, No. 68 Yutian South Road, Shanghai 201805, ChinaIn this paper, a data-oriented model has been presented by nonlinear autoregressive exogenous model (NARX) neural network, which aims at predicting the mechanical behavior of a fuel cell stack for vehicle under the real-life operational conditions. A 300-hour vibration test with reproduction of SVP road spectrum was completed on a Multi-Axial Simulation Table. At the same time, data acquisition of drive displacement and acceleration response on stack was carried out in every 50 hours. All data collected were used to train and evaluate the model based on NARX. Result shows that the prediction model built is of good precision and consistent with the actual situation.http://dx.doi.org/10.1155/2021/6671547
spellingShingle Liying Ma
Bo Lv
Yongping Hou
Xiangmin Pan
Prediction Model of the Mechanical Behavior of a Fuel Cell Stack under Strengthened Road Vibrating Conditions
Modelling and Simulation in Engineering
title Prediction Model of the Mechanical Behavior of a Fuel Cell Stack under Strengthened Road Vibrating Conditions
title_full Prediction Model of the Mechanical Behavior of a Fuel Cell Stack under Strengthened Road Vibrating Conditions
title_fullStr Prediction Model of the Mechanical Behavior of a Fuel Cell Stack under Strengthened Road Vibrating Conditions
title_full_unstemmed Prediction Model of the Mechanical Behavior of a Fuel Cell Stack under Strengthened Road Vibrating Conditions
title_short Prediction Model of the Mechanical Behavior of a Fuel Cell Stack under Strengthened Road Vibrating Conditions
title_sort prediction model of the mechanical behavior of a fuel cell stack under strengthened road vibrating conditions
url http://dx.doi.org/10.1155/2021/6671547
work_keys_str_mv AT liyingma predictionmodelofthemechanicalbehaviorofafuelcellstackunderstrengthenedroadvibratingconditions
AT bolv predictionmodelofthemechanicalbehaviorofafuelcellstackunderstrengthenedroadvibratingconditions
AT yongpinghou predictionmodelofthemechanicalbehaviorofafuelcellstackunderstrengthenedroadvibratingconditions
AT xiangminpan predictionmodelofthemechanicalbehaviorofafuelcellstackunderstrengthenedroadvibratingconditions