Title :
A neural network model of a fuel cell stack under road vibrations
Author_Institution :
Clean Energy Automotive Eng. Center, Tongji Univ., Shanghai, China
Abstract :
A model is very important for studying the dynamic response of the fuel cell stack under road vibrations. Mechanism models have many parameters which can´t be measured in real stack tests when the outside forces and the inside parameters are all needed to be known. The fuel cell stack used in new energy car which takes place of conventional engine is a complicated nonlinear mechanical system. while its durability under vibration is tested, only the driving and responding signals are collected. In this case, a neural network is used to predict the response of the stack under different vibration conditions and also to be used as a fault diagnose tool.
Keywords :
fault diagnosis; fuel cell vehicles; mechanical engineering computing; neural nets; vehicle dynamics; vibrations; dynamic response; fault diagnose tool; fuel cell stack; mechanism models; neural network model; new energy car; nonlinear mechanical system; road vibrations; Energy measurement; Predictive models; Vibration measurement; modelling; neural network; nonlinear mechanical system;
Conference_Titel :
Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2363-5
DOI :
10.1109/EEESym.2012.6258599
