Real-time roll angle estimation for two-wheeled vehicles
Real-time roll angle estimation for two-wheeled vehicles
An original method for the real-time estimation of the roll angle using low-cost sensors in two-wheeled vehicles is proposed. The roll angle greatly affects the dynamics of singletrack vehicles and its estimation is essential in control systems such as ABS, Traction Control, as well as Curve and Collision Warning, or even active suspensions. The proposed method uses a non-linear Kalman filter, its performances are assessed by using both a set of simulated data from a multibody model and a set of real data collected on an instrumented test vehicle.
978-079184484-7
687-693
Lot, R.
ceb0ca9c-6211-4051-a7b8-90fd6f0a6d78
Cossalter, V.
5682d553-7457-4947-ba30-f1265d206679
Massaro, M.
b9bed959-fc8a-4ea5-b87f-9fcdb9ae449c
2012
Lot, R.
ceb0ca9c-6211-4051-a7b8-90fd6f0a6d78
Cossalter, V.
5682d553-7457-4947-ba30-f1265d206679
Massaro, M.
b9bed959-fc8a-4ea5-b87f-9fcdb9ae449c
Lot, R., Cossalter, V. and Massaro, M.
(2012)
Real-time roll angle estimation for two-wheeled vehicles.
ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2012, Nantes, France.
02 - 04 Jul 2012.
.
(doi:10.1115/ESDA2012-82182).
Record type:
Conference or Workshop Item
(Paper)
Abstract
An original method for the real-time estimation of the roll angle using low-cost sensors in two-wheeled vehicles is proposed. The roll angle greatly affects the dynamics of singletrack vehicles and its estimation is essential in control systems such as ABS, Traction Control, as well as Curve and Collision Warning, or even active suspensions. The proposed method uses a non-linear Kalman filter, its performances are assessed by using both a set of simulated data from a multibody model and a set of real data collected on an instrumented test vehicle.
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Published date: 2012
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cited By 1
Venue - Dates:
ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2012, Nantes, France, 2012-07-02 - 2012-07-04
Organisations:
Energy Technology Group
Identifiers
Local EPrints ID: 382684
URI: http://eprints.soton.ac.uk/id/eprint/382684
ISBN: 978-079184484-7
PURE UUID: a88e6621-54a6-4452-9b52-de46ea1a0b1b
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Date deposited: 03 Nov 2015 12:19
Last modified: 14 Mar 2024 21:31
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Author:
R. Lot
Author:
V. Cossalter
Author:
M. Massaro
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