Parameter Identification of Tractor-Semitrailer Model under Steering and Braking

This paper describes a valuable linear yaw-roll tractor-semitrailer (TST) model with five-degree-of-freedom (DOFs) for control algorithm development when steering and braking. The key parameters, roll stiffness, axle cornering stiffness, and fifth-wheel stiffness, are identified by the genetic algor...

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Main Authors: Yiming Li, Qin Shi, Duoyang Qiu
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2019/1345364
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spelling doaj-063a12543ba9430ea95fa7cd640635922020-11-25T01:43:06ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/13453641345364Parameter Identification of Tractor-Semitrailer Model under Steering and BrakingYiming Li0Qin Shi1Duoyang Qiu2School of Automobile and Transportation Engineering, Hefei University of Technology, No. 193 Tunxi Road, Hefei, Anhui 230009, ChinaSchool of Automobile and Transportation Engineering, Hefei University of Technology, No. 193 Tunxi Road, Hefei, Anhui 230009, ChinaSchool of Automobile and Transportation Engineering, Hefei University of Technology, No. 193 Tunxi Road, Hefei, Anhui 230009, ChinaThis paper describes a valuable linear yaw-roll tractor-semitrailer (TST) model with five-degree-of-freedom (DOFs) for control algorithm development when steering and braking. The key parameters, roll stiffness, axle cornering stiffness, and fifth-wheel stiffness, are identified by the genetic algorithm (GA) and multistage genetic algorithm (MGA) based on TruckSim outputs to increase the accuracy of the model. Thus, the key parameters of the simplified model can be modified according to the real-time vehicle states by online lookup table and interpolation. The TruckSim vehicle model is built referring to the real tractor (JAC-HFC4251P1K7E33ZTF6×2) and semitrailer (Luyue LHX9406) used in the field test later. The validation of the linear yaw-roll model of a tractor-semitrailer using field test data is presented in this paper. The field test in the performance testing ground is detailed, and the test data of roll angle, roll rate, and yaw rate are compared with the outputs of the model with maps of the key parameters. The results indicate that the error of the tractor’s roll angle and semitrailer’s roll angle between model data and test data is 1.13% and 1.24%, respectively. The roll rate and yaw rate of the tractor and semitrailer are also in good agreement.http://dx.doi.org/10.1155/2019/1345364
collection DOAJ
language English
format Article
sources DOAJ
author Yiming Li
Qin Shi
Duoyang Qiu
spellingShingle Yiming Li
Qin Shi
Duoyang Qiu
Parameter Identification of Tractor-Semitrailer Model under Steering and Braking
Mathematical Problems in Engineering
author_facet Yiming Li
Qin Shi
Duoyang Qiu
author_sort Yiming Li
title Parameter Identification of Tractor-Semitrailer Model under Steering and Braking
title_short Parameter Identification of Tractor-Semitrailer Model under Steering and Braking
title_full Parameter Identification of Tractor-Semitrailer Model under Steering and Braking
title_fullStr Parameter Identification of Tractor-Semitrailer Model under Steering and Braking
title_full_unstemmed Parameter Identification of Tractor-Semitrailer Model under Steering and Braking
title_sort parameter identification of tractor-semitrailer model under steering and braking
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2019-01-01
description This paper describes a valuable linear yaw-roll tractor-semitrailer (TST) model with five-degree-of-freedom (DOFs) for control algorithm development when steering and braking. The key parameters, roll stiffness, axle cornering stiffness, and fifth-wheel stiffness, are identified by the genetic algorithm (GA) and multistage genetic algorithm (MGA) based on TruckSim outputs to increase the accuracy of the model. Thus, the key parameters of the simplified model can be modified according to the real-time vehicle states by online lookup table and interpolation. The TruckSim vehicle model is built referring to the real tractor (JAC-HFC4251P1K7E33ZTF6×2) and semitrailer (Luyue LHX9406) used in the field test later. The validation of the linear yaw-roll model of a tractor-semitrailer using field test data is presented in this paper. The field test in the performance testing ground is detailed, and the test data of roll angle, roll rate, and yaw rate are compared with the outputs of the model with maps of the key parameters. The results indicate that the error of the tractor’s roll angle and semitrailer’s roll angle between model data and test data is 1.13% and 1.24%, respectively. The roll rate and yaw rate of the tractor and semitrailer are also in good agreement.
url http://dx.doi.org/10.1155/2019/1345364
work_keys_str_mv AT yimingli parameteridentificationoftractorsemitrailermodelundersteeringandbraking
AT qinshi parameteridentificationoftractorsemitrailermodelundersteeringandbraking
AT duoyangqiu parameteridentificationoftractorsemitrailermodelundersteeringandbraking
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