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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2019-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/1345364 |
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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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