Parameters Identification for Simplified Yaw Model of Articulated Heavy Vehicle

Zhi Gen Nie; Chang Fu Zong

doi:10.4028/www.scientific.net/AMR.765-767.387

Paper Titles

Finite Element Analysis of Automobile Transmission Shaft
p.370

Simulation of Wheel Slide Protection System for Railway Vehicles
p.374

A Cutting Force Model for Face Milling Operation
p.378

Simulation of Active Suspension System Based on Optimal Control
p.382

Parameters Identification for Simplified Yaw Model of Articulated Heavy Vehicle
p.387

Co-Simulation Study on Over-Running Load Balance in Cabin Door Hydromechanical Drive System
p.392

Reliability Analysis of Dynamical Strength for Crank-Rocker Mechanism Based on Assur-Group Method
p.398

Modeling and Simulation for Overhead Hoist Transporter System in Computer Integrated Manufacturing; A Case Study on the Food Processing Business
p.404

A Visual EFSM Modeling System for Protocol Testing
p.409

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 765-767Parameters Identification for Simplified Yaw Model...

Parameters Identification for Simplified Yaw Model of Articulated Heavy Vehicle

Abstract:

In order to accurately characterize the lateral dynamic characteristics of articulated heavy vehicle, 3-dof simplified yaw model of articulated heavy vehicles is established and key parameters of models are identified by genetic algorithm. MAPs of key parameters, which the vehicle speed and steering wheel angle are independent variables for, are formed using the key identification parameters. Simulation study of dynamic state is carried out by the MAPs of key identification parameters and 3-dof simplified yaw model. That simulation result compared with Trucksim data indicates that key parameters can be accurately identified and the MAPs of key identification parameters satisfies the need of characterizing the actual state of vehicle.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 765-767)

Pages:

387-391

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.765-767.387

Citation:

Cite this paper

Online since:

September 2013

Authors:

Zhi Gen Nie, Chang Fu Zong

Keywords:

Articulated Heavy Vehicles, Dynamic Model, Genetic Algorithm (GA), Parameters Identification, Vehicle Engineering

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Caizhen Cheng. Enhancing safety of actively-steered articulated vehicles [D]. Cambridge, University of Cambridge, (2009).

Google Scholar

[2] Daniel Wesemeier, RolfIsermann. Identification of vehicle parameters using stationary driving maneuvers [J]. Control Engineering Practice, 2009, 17: 1426–1431.

DOI: 10.1016/j.conengprac.2008.10.008

Google Scholar

[3] H. Yu, L. Guvenc, U, Ozguner. Heavy duty vehicle rollover detection and active roll control [J]. Vehicle system dynamics, 2008, 46(6): 451-470.

DOI: 10.1080/00423110701477529

Google Scholar

[4] Li Mai, Changfu Zong, Hua-ji Wang, Tian-jun Zhu. Calibration method for heavy commercial vehicle rollover prediction model[J]. journal of jilin university, 2010, 9 (40): 60-65.

Google Scholar

[5] J . A . Cabrera , A . Ortiz and E . Carabias. Analtertive method to determine the magic tyre model parameters using genetic algorithms[J]. Vehicle System Dynamics , 2004, 41(2): 109-127.

DOI: 10.1076/vesd.41.2.109.26496

Google Scholar