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Study on the Handling Stability for an Articulated Truck with Four Motor-Driven Wheels
ISSN: 0148-7191, e-ISSN: 2688-3627
Published June 5, 2017 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Articulated engineering vehicle travels on complex road, its working condition is bad and because of the non-rigid connection between the front and rear body, additional DOF is brought in and the transverse stiffness is relatively weak. When the articulated vehicle runs in a high speed along a straight line, it is easy to cause the transverse swing and the poor handling stability. If it is serious enough, it will lead to "snakelike" instability phenomenon. This kind of instability will increase driving resistance and tire wear, the lateral dynamic load and aggravate the damage of the parts. The vehicle will have a lateral migration of center of gravity (CG) when steering, which will lead a higher probability of rollover accident. A dynamic mathematical model for a 35t articulated truck with four motor-driven wheels was established in this paper, to study the condition for its stable driving and the influence of the vehicle structural parameters. This part research focused on the position changes of the pivot and front and rear axle center, which impact the handling stability. Then a multi-body dynamic model was built in ADAMS and simulation of steady state circular test and steering wheel angle step input test were conducted to observe the handling stability of vehicle and compare the results in empty load, full load and different steering angle step inputting. On this basis, the influence of the CG position of rear body on truck handling stability was studied. The results of simulation has a good reference value for the articulated truck handling stability design and verify the correctness of the models.
CitationQin, B., Yang, J., and Zhao, X., "Study on the Handling Stability for an Articulated Truck with Four Motor-Driven Wheels," SAE Technical Paper 2017-01-1833, 2017, https://doi.org/10.4271/2017-01-1833.
Data Sets - Support Documents
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