Intelligent air-cushion tracked vehicle performance investigation: neural-networks

被引:2
|
作者
Hossain, Altab [1 ]
Rahman, Ataur [2 ]
Mohiuddin, A. K. M. [2 ]
Ramesh, S. [1 ]
机构
[1] Univ Malaya, Dept Engn Design & Mfg, Fac Engn, Kuala Lumpur 50603, Malaysia
[2] Int Islamic Univ Malaysia, Dept Mech Engn, Fac Engn, Kuala Lumpur 50603, Malaysia
关键词
ANN; artificial neural network; CH; cushion clearance height; PC; power consumption; TE; tractive effort; MR; motion resistance; SYSTEM; DESIGN;
D O I
10.1504/IJHVS.2012.049850
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
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) arc 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.
引用
收藏
页码:407 / 426
页数:20
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