PRACA ORYGINALNA
Simulation of curvilinear motion of automobile with the use of two-degree-of-freedom flat model
Więcej
Ukryj
1
Institute of Vehicles, Warsaw University of Technology, Polska
Data nadesłania: 04-02-2020
Data ostatniej rewizji: 29-02-2020
Data akceptacji: 02-03-2020
Data publikacji: 30-03-2020
Autor do korespondencji
Hubert Sar
Institute of Vehicles, Warsaw University of Technology, Narbutta 84, 02-524, Warsaw, Polska
The Archives of Automotive Engineering – Archiwum Motoryzacji 2020;87(1):19-32
SŁOWA KLUCZOWE
DZIEDZINY
STRESZCZENIE
Development of active safety systems of automobiles is nowadays based not only on road tests, but also on computer simulation of vehicle's curvilinear motion. To properly perform simulation, all required model parameters have to be properly estimated. The less complicated model is, the less parameters it requires. So that, it makes no sense to apply too complicated models, if we are not able to estimate parameters with relatively low error. One of the most popular is two- degree-of-freedom flat model to describe curvilinear motion of automobile. It is widely used in design and improvement of active safety systems.
The article discusses the application of simple two- degree-of-freedom flat model of automobile, which requires only several parameters. These parameters are: mass of a vehicle, location of center of gravity of a vehicle, yaw mass moment of inertia of a vehicle, side-slip characteristics. Furthermore, to be able to compare simulation and measurement results, it is necessary to know some input signals such as steering wheel angle and velocity of a vehicle, recorded during road tests. In this article signal of steering wheel angle was taken from Controller Area Network (CAN) bus.
In case of model of a vehicle, the Authors decided to compare the results of simulation using two different side slip characteristics known as the dependence between lateral reaction force and side slip angle: linear characteristic (constant cornering stiffness) and the characteristic represented by Pacejka’s Magic Formula in steady-state version.
REFERENCJE (18)
1.
Ammon D.: Vehicle dynamics analysis tasks and related tyre simulation challenges. Vehicle System Dynamics, 2005, 43(Sup. 1), 30–47, DOI: 10.1080/00423110500141003.
2.
Cheng S., Li L., Yan B., Liu C., Wang X., Fang J.: Simultaneous estimation of tire side-slip angle and lateral tire force for vehicle lateral stability control. Mechanical Systems and Signal Processing, 2019, 132, 168–182, DOI: 10.1016/j.ymssp.2019.06.022.
3.
El-Sayegh Z., Sharifi M., Gheshlaghi F., Mardani A.: Development of an HLFS agricultural tire model using FEA technique. SN Applied Sciences, 2019, 1454(1), DOI: 10.1007/s42452-019-1524-y.
4.
Garcia-Pozuelo D., Olatunbosun O. A., Romano L., Strano S., Terzo M., Tuononen AJ. et al.: Development and experimental validation of a real-time analytical model for different intelligent tyre concepts. Vehicle System Dynamics, 2019, 57(12), 1970-1988, DOI: 10.1080/00423114.2019.1566560.
5.
Hyun M., Cho W.: Estimation of Road Bank Angle and Vehicle Side Slip Angle Using Bayesian Tracking and Kalman Filter Approach. International Journal of Automotive Technology, 2018, 19(6), 993–1000, DOI: 10.1007/s12239-018-0096-y.
6.
ISO 3888-1:2018, Passenger cars — Test track for a severe lane-change manoeuvre — Part 1: Double lane-change.
7.
ISO 3888-2:2011, Passenger cars — Test track for a severe lane-change manoeuvre — Part 2: Obstacle avoidance.
8.
Jin C., Shao L., Lex C., Eichberger A.: Vehicle Side Slip Angle Observation with Road Friction Adaptation. IFAC-PapersOnLine, 2017, 50(1), 3406–3411, DOI: 10.1016/j.ifacol.2017.08.593.
9.
Johnson DK., Botha TR., Els PS.: Real-time side-slip angle measurements using digital image correlation. Journal of Terramechanics, 2019, 81, 35–42, DOI: 10.1016/j.jterra.2018.08.001.
10.
Kansake B. A., Frimpong S.: Analytical modelling of dump truck tire dynamic response to haul road surface excitations. International Journal of Mining, Reclamation and Environment, 2020, 34(1), 1-18, DOI: 10.1080/17480930.2018.1507608.
11.
Lozia Z.: Rollover Thresholds of the Biaxial Truck During Motion on an Even Road. Vehicle System Dynamics, 1998, 29(Sup. 1), 735–740, DOI: 10.1080/00423119808969601.
12.
Nakashima H., Wong JY.: A three-dimensional tire model by the finite element method. Journal of Terramechanics, 1993, 30(1), 21–34, DOI: 10.1016/0022-4898(93)90028-V.
13.
Pacejka HB.: Tire and Vehicle Dynamics. Elsevier, 2012.
14.
Reński A.: Analysis of the Influence of the Drive Force Distribution Between Axles on an Automobile Stability in Its Curvilinear Motion. Springer International Publishing Switzerland 2017 A. Chiru and N. Ispas (eds.), CONAT 2016 International Congress of Automotive and Transport Engineering, DOI 10.1007/978-3-319-45447-4_6.
15.
Sandu C., Taheri S., Taheri S., Gorsich D.: Hybrid Soft Soil Tire Model (HSSTM). Part I: Tire material and structure modeling. Journal of Terramechanics, 2019, 86, 1-13, DOI:10.1016/j.jterra.2019.08.002.
16.
Sun X., Zhang H., Cai Y., Wang S., Chen L.: Hybrid modeling and predictive control of intelligent vehicle longitudinal velocity considering nonlinear tire dynamics. Nonlinear Dynamics, 2019, 97, 1051–1066, DOI: 10.1007/s11071-019-05030-5.
17.
Uhlar S., Heyder F., König T.: Assessment of two physical tyre models in relation to their NVH performance up to 300 Hz. Vehicle System Dynamics, 2019, 1–21, DOI: 10.1080/00423114.2019.1681475.
18.
Yu X., Huang H., Zhang T.: A theoretical three-dimensional ring based model for tire high-order bending vibration. Journal of Sound and Vibration, 2019, 459, 114820, DOI: 10.1016/j.jsv.2019.06.027.
CYTOWANIA (1):
1.
The planning process of transport tasks for autonomous vans
Aleksander Nieoczym, Jacek Caban, Ondrej Stopka, Tomasz Krajka, Mária Stopková
Open Engineering