Abstract: Fuzzy logic approach is used in this study to predict
the tractive performance in terms of traction force, and motion
resistance for an intelligent air cushion track vehicle while it operates
in the swamp peat. The system is effective to control the intelligent
air –cushion system with measuring the vehicle traction force (TF),
motion resistance (MR), cushion clearance height (CH) and cushion
pressure (CP). Sinkage measuring sensor, magnetic switch, pressure
sensor, micro controller, control valves and battery are incorporated
with the Fuzzy logic system (FLS) to investigate experimentally the
TF, MR, CH, and CP. In this study, a comparison for tractive
performance of an intelligent air cushion track vehicle has been
performed with the results obtained from the predicted values of FLS
and experimental actual values. The mean relative error of actual and
predicted values from the FLS model on traction force, and total
motion resistance are found as 5.58 %, and 6.78 % respectively. For
all parameters, the relative error of predicted values are found to be
less than the acceptable limits. The goodness of fit of the prediction
values from the FLS model on TF, and MR are found as 0.90, and
0.98 respectively.
Abstract: Fuzzy logic system (FLS) is used in this study to
predict the tractive performance in terms of traction force, and
motion resistance for an intelligent air cushion track vehicle while it
operates in the swamp peat. The system is effective to control the
intelligent air –cushion system with measuring the vehicle traction
force (TF), motion resistance (MR), cushion clearance height (CH)
and cushion pressure (CP). Ultrasonic displacement sensor, pull-in
solenoid electromagnetic switch, pressure control sensor, micro
controller, and battery pH sensor are incorporated with the Fuzzy
logic system to investigate experimentally the TF, MR, CH, and CP.
In this study, a comparison for tractive performance of an intelligent
air cushion track vehicle has been performed with the results obtained
from the predicted values of FLS and experimental actual values. The
mean relative error of actual and predicted values from the FLS
model on traction force, and total motion resistance are found as 5.58
%, and 6.78 % respectively. For all parameters, the relative error of
predicted values are found to be less than the acceptable limits. The
goodness of fit of the prediction values from the FLS model on TF,
and MR are found as 0.90, and 0.98 respectively.
Abstract: Modeling of the dynamic behavior and motion are
renewed interest in the improved tractive performance of an
intelligent air-cushion tracked vehicle (IACTV). This paper presents
a new dynamical model for the forces on the developed small scale
intelligent air-cushion tracked vehicle moving over swamp peat. The
air cushion system partially supports the 25 % of vehicle total weight
in order to make the vehicle ground contact pressure 7 kN/m2. As the
air-cushion support system can adjust automatically on the terrain, so
the vehicle can move over the terrain without any risks. The springdamper
system is used with the vehicle body to control the aircushion
support system on any undulating terrain by making the
system sinusoidal form. Experiments have been carried out to
investigate the relationships among tractive efficiency, slippage,
traction coefficient, load distribution ratio, tractive effort, motion
resistance and power consumption in given terrain conditions.
Experiment and simulation results show that air-cushion system
improves the vehicle performance by keeping traction coefficient of
71% and tractive efficiency of 62% and the developed model can
meet the demand of transport efficiency with the optimal power
consumption.