Comparison between 6x6 and 6x4 vehicle behavior in steady-state cornering

Rodrigues, Gustavo Simão; Acuña, Marcelo Andrés; Queiroz, Rafael Vitor Guerra Queiroz; Neto, Ricardo Teixeira da Costa

doi:10.26678/abcm.diname2019.din2019-0089

Cited by 1 publication

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“…Thus, the resulting characteristic curve is capable of adequately quantify the tire longitudinal force, F x , for the entire range angle. 1,11,24 The longitudinal force, F x , is formulated from equations (3)–(11) as follows…”

Section: Mathematical Modelsmentioning

confidence: 99%

“…The movement of the front steerable axle is modeled by using the Ackerman geometry. The kinematic condition involves the steer angle of the inner wheel, δ in ; the steer angle of the outer wheel, δ out ; the track, b w ; and the distance between the front axle to the link bogie suspension, L 5,11…”

Section: Mathematical Modelsmentioning

confidence: 99%

“…A better understanding about the parameters involved, can improve the design of vehicle. 2,7,11,18–21…”

Section: Introductionmentioning

confidence: 99%

“…In a steady-state cornering, and due to varying velocity and forces modules actuating in the vehicle, a 3 degrees of freedom (DOF) is a good approximation. 11 A severe double lane change maneuver (DLCM) with obstacle avoidance are used to evaluate and determinate the lateral kinematic parameters. The commonly used specification for passenger car of a DCLM is described in the ISO 3888-1:2000 specification, ISO 14791:2018 for heavy commercial vehicles and NATO AVTP 3-160 for military vehicle.…”

Section: Introductionmentioning

confidence: 99%

“…A better understanding about the parameters involved, can improve the design of vehicle. 2,7,11,[18][19][20][21] The rest of this article is organized as follows: In the second section, we describe the mathematical models of longitudinal dynamics (transmission line dynamics, powertrain, tire model, rolling resistance, and drag resistance) and lateral dynamics by using the bicycle model to three wheels and driver behavior using an AMPC including the vertical loads. The third section presents the development of the simulation framework.…”

Section: Introductionmentioning

confidence: 99%

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Modeling and dynamic analysis of a 6 x 6 heavy military truck by adaptive model predictive control with application to NATO lane change test course

Acuña

Rodrigues

Queiroz

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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In this paper, the computer-aided vehicle dynamic analysis of a 6x6 heavy military truck is presented and examined. For the analysis, a MATLAB/Simulink® platform is used to design and model a truck. The vehicle configuration taken into account for the analysis is the powertrain (engine, gear box, transfer gear, differential), suspension, steering system and tire model according to the Pacekja 89’ formulation. In addition, the effect of the rolling resistance and drag is considered, in order to represent the vehicle behavior as real as possible. The longitudinal dynamic and lateral dynamic are formulated. First, the longitudinal dynamic model is established by means of implementation of the weight transfer function. The vehicles are considered as rigid bodies with 1 degree of freedom. Second, the vehicular planar model with three wheels, well known as bicycle model, is applied following the North Atlantic Treaty Organization double line change maneuver test reaching 3 degree of freedom. The driver behavior is represented by using an adaptive model predictive control varying the longitudinal velocity. The forces for braking, inertia of the rotating components, the energy lost in the powertrain, and the effect of dive squat and rollover. The numerical simulation results are shown and compared with a full-vehicle model formed by using Mechanical Simulation Corporation’s truckSIM®. There were chosen simulation scenarios applied to the model to observe the effects of different parameters concerning the dynamic behavior, and also prepared in truckSIM® environment. The main contributions of this article are the development of the vehicular model, through the use of block diagrams in a reliable and relatively simple programming code such as MATLAB/Simulink®, with innovative tools used in the control of autonomous vehicle driving and the flexibility to adapt said model to different environmental conditions and different vehicle parameters.

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