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International Journal of Automotive Technology

, Volume 19, Issue 6, pp 993–1000 | Cite as

Estimation of Road Bank Angle and Vehicle Side Slip Angle Using Bayesian Tracking and Kalman Filter Approach

  • Minje Hyun
  • Wanki ChoEmail author
Article
  • 21 Downloads

Abstract

A lateral acceleration is considered to be a significant sensor signal for an estimation of a side slip angle. Due to the fact that a characteristic of a lateral G sensor, the sensor has a technical issue when a road bank angle has presented. In order to resolve the issue, this paper describes a novel method for the real time estimation of a vehicle side slip angle and a road bank angle simultaneously. A Bayesian tracking approach is used to estimate the road bank angle by comparing a measured lateral acceleration with the calculated one in the case of various angle. A Kalman Filter has been implemented through bicycle model using vehicle roll angle, road bank angle and angular velocity of side slip angle. The performance of the proposed estimation method has been evaluated via vehicle tests on a real road.

Key Words

Vehicle side slip angle Road bank angle Bayesian tracking Kalman-filter 

Nomenclature

ay.mea

measured lateral acceleration

Vx

longitudinal velocity

m

mass of vehicle

ß

side-slip angle

ß

side-slip angular velocity

ß

yaw rate

Cf

front cornering stiffness

Cr

rear cornering stiffness

lf

distance from center of mass to front axle

lr

distance from center of mass to rear axle

Ix

roll inertia

Iz

yaw inertia

df

front steering angle

A

system matrix

B

input matrix

ϕRoll

roll angle

ϕBank

bank angle

g

gravitational acceleration

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Copyright information

© The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Intelligent Vehicle Safety System Development TeamHyundai Kia Motors R&D CenterGyeonggiKorea

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