DocumentCode :
1847
Title :
Rollover Risk Prediction of Heavy Vehicle Using High-Order Sliding-Mode Observer: Experimental Results
Author :
imine, hocine ; Benallegue, A. ; Madani, T. ; Srairi, Salim
Author_Institution :
Lab. for Road Oper., Perception, Simulators & Simulations, French Inst. of Sci. & Technol. for Transp., Dev. & Networks, Marne la Vallée, France
Volume :
63
Issue :
6
fYear :
2014
fDate :
Jul-14
Firstpage :
2533
Lastpage :
2543
Abstract :
In this paper, an original method about heavy-vehicle rollover risk prediction is presented and validated experimentally. It is based on the calculation of the load transfer ratio (LTR), which depends on the estimated vertical forces using high-order sliding-mode (HOSM) observers. Previously, a tractor model is developed. The validation tests were carried out on an instrumented tractor rolling on the road at various speeds and lane-change maneuvers. Many scenarios have been experienced: driving tests in a straight line, a curve, and a zigzag line, and brake tests to emphasize the rollover phenomenon and its prediction to set off an alarm to the driver. In this paper, the vehicle dynamic parameters (masses, inertia, stiffness, etc.) and the static-force infrastructure characteristics (road profile, radius of curvature, longitudinal and lateral slopes, and skid resistance) are measured or calculated before the tests.
Keywords :
braking; mechanical testing; observers; risk analysis; road traffic control; variable structure systems; vehicle dynamics; HOSM observers; LTR; brake tests; curve; driving tests; estimated vertical forces; heavy-vehicle rollover risk prediction; high-order sliding-mode observer; instrumented tractor; lane-change maneuvers; load transfer ratio; rollover phenomenon; static-force infrastructure characteristics; straight line; tractor model; vehicle dynamic parameters; zigzag line; Acceleration; Agricultural machinery; Gravity; Observers; Roads; Vehicles; Wheels; Estimation; Heavy vehicle modeling; Prediction; Rollover; Sliding mode observer; heavy-vehicle modeling; prediction; rollover; sliding-mode observer;
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2013.2292998
Filename :
6675869
Link To Document :
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