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Estimation of Vehicle Lateral Velocity

Pettersson, Pierre (2008) In MSc Theses
Department of Automatic Control
Abstract
For the performance of the Haldex Active Yaw Control, accurate information about vehicle's lateral dynamic is important. It is for practical reasons not possible to measure the vehicle's lateral velocity, wherefore this state has to be estimated. Previous work [1] with an observer based on a single track bicycle model show promising results but with limited accuracy at high lateral acceleration, therefore was the approach in this thesis to expand the single track model into a two track model to at a more extensive level capture the chassis dynamics. An alternative tire model was developed, because the well known Magic Formula was for this application too computational expensive and the alternative, Exponential tire model, which was... (More)
For the performance of the Haldex Active Yaw Control, accurate information about vehicle's lateral dynamic is important. It is for practical reasons not possible to measure the vehicle's lateral velocity, wherefore this state has to be estimated. Previous work [1] with an observer based on a single track bicycle model show promising results but with limited accuracy at high lateral acceleration, therefore was the approach in this thesis to expand the single track model into a two track model to at a more extensive level capture the chassis dynamics. An alternative tire model was developed, because the well known Magic Formula was for this application too computational expensive and the alternative, Exponential tire model, which was previously used in [1] have several disadvantages. Two observers have been evaluated, the Extended Kalman Filter (EKF) and an Averaging Observer. The EKF is a well known observer that is able to perform well but with the disadvantage to require much calculation power. The Averaging Observer is on the other hand light on calculations, which in this application are desired. Therefore it is tested how well the Averaging Observer performs compared to the EKF. The evaluation was done by comparing the estimated states with the states from both a more complex vehicle model and also real world measurements. The observers performed well in both the cases. The EKF and the Averaging Observer performed almost similar results, which is a favor for the Averaging Observer to achieve same accuracy with less computational effort. Brief tests to do road friction estimations were done and showed promising results if the lateral acceleration sensor signal is reliable. (Less)
Please use this url to cite or link to this publication:
author
Pettersson, Pierre
supervisor
organization
year
type
H3 - Professional qualifications (4 Years - )
subject
publication/series
MSc Theses
report number
TFRT-5827
ISSN
0280-5316
language
English
id
8847658
date added to LUP
2016-03-17 10:23:30
date last changed
2016-03-17 10:23:30
@misc{8847658,
  abstract     = {{For the performance of the Haldex Active Yaw Control, accurate information about vehicle's lateral dynamic is important. It is for practical reasons not possible to measure the vehicle's lateral velocity, wherefore this state has to be estimated. Previous work [1] with an observer based on a single track bicycle model show promising results but with limited accuracy at high lateral acceleration, therefore was the approach in this thesis to expand the single track model into a two track model to at a more extensive level capture the chassis dynamics. An alternative tire model was developed, because the well known Magic Formula was for this application too computational expensive and the alternative, Exponential tire model, which was previously used in [1] have several disadvantages. Two observers have been evaluated, the Extended Kalman Filter (EKF) and an Averaging Observer. The EKF is a well known observer that is able to perform well but with the disadvantage to require much calculation power. The Averaging Observer is on the other hand light on calculations, which in this application are desired. Therefore it is tested how well the Averaging Observer performs compared to the EKF. The evaluation was done by comparing the estimated states with the states from both a more complex vehicle model and also real world measurements. The observers performed well in both the cases. The EKF and the Averaging Observer performed almost similar results, which is a favor for the Averaging Observer to achieve same accuracy with less computational effort. Brief tests to do road friction estimations were done and showed promising results if the lateral acceleration sensor signal is reliable.}},
  author       = {{Pettersson, Pierre}},
  issn         = {{0280-5316}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{MSc Theses}},
  title        = {{Estimation of Vehicle Lateral Velocity}},
  year         = {{2008}},
}