Intelligent air-cushion tracked vehicle performance investigation: neural-networks Online publication date: Sat, 20-Dec-2014
by Altab Hossain; Ataur Rahman; A.K.M. Mohiuddin; S. Ramesh
International Journal of Heavy Vehicle Systems (IJHVS), Vol. 19, No. 4, 2012
Abstract: Intelligent Air-Cushion Tracked Vehicle (IACTV) is intended as an alternative to conventional off-road vehicles, which are driven by track system and air-cushion system. To make IACTV as efficient as possible, proper investigation of vehicle performance is essential. However, most relevant factors that affect the competitive efficiency of the air-cushion tracked vehicle are the tractive effort, motion resistance and power consumption. Therefore, an Artificial Neural-Network (ANN) model is proposed to investigate the vehicle performance. Cushion Clearance Height (CH), and Air-Cushion Pressure (CP) are used at the input layers while Power Consumption (PC), Tractive Effort (TE) and Motion Resistance (MR) are used at the output layers. Experiments are carried out in the field to investigate the vehicle performance and compared with the results obtained from ANN.
Online publication date: Sat, 20-Dec-2014
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Heavy Vehicle Systems (IJHVS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org