TY - GEN
T1 - Integrated estimation of vehicle states, tire forces, and tire-road friction coefficients
AU - Hsiao, Te-Sheng
AU - Lan, Jing Yuan
AU - Yang, Hanping
N1 - Publisher Copyright:
© 2014 Institute of Control, Robotics and Systems (ICROS).
PY - 2014/12/16
Y1 - 2014/12/16
N2 - Information about the vehicle states (e.g. the sideslip angle and the longitudinal velocity), tire forces, and tire-road friction coefficients is crucial for advanced vehicular active safety systems. In particular, the latest high-performance control system based on optimally distributing and controlling all tire forces requires feedback of the tire forces and the tire-road friction coefficient of each individual tire. Therefore, estimating all or parts of the vehicle/tire/road states from available sensor measurements in production vehicles has long been an active research topic in both academia and industry. Despite recent advances in automotive estimation technologies, it remains an open question on identifying the tire-road friction coefficient of each individual tire. This paper proposes an integrated estimation system that provides accurate estimates of the vehicle/tire/road states from available sensor measurements. More importantly, the tire-road friction coefficient of each tire can be separately estimated. The performance of the proposed estimation system is verified by simulations based on a complex nonlinear vehicle/ tire model.
AB - Information about the vehicle states (e.g. the sideslip angle and the longitudinal velocity), tire forces, and tire-road friction coefficients is crucial for advanced vehicular active safety systems. In particular, the latest high-performance control system based on optimally distributing and controlling all tire forces requires feedback of the tire forces and the tire-road friction coefficient of each individual tire. Therefore, estimating all or parts of the vehicle/tire/road states from available sensor measurements in production vehicles has long been an active research topic in both academia and industry. Despite recent advances in automotive estimation technologies, it remains an open question on identifying the tire-road friction coefficient of each individual tire. This paper proposes an integrated estimation system that provides accurate estimates of the vehicle/tire/road states from available sensor measurements. More importantly, the tire-road friction coefficient of each tire can be separately estimated. The performance of the proposed estimation system is verified by simulations based on a complex nonlinear vehicle/ tire model.
KW - lateral tire force estimation
KW - longitudinal velocity estimation
KW - sideslip angle estimation
KW - tire-road friction coefficient estimation
UR - http://www.scopus.com/inward/record.url?scp=84920185419&partnerID=8YFLogxK
U2 - 10.1109/ICCAS.2014.6987744
DO - 10.1109/ICCAS.2014.6987744
M3 - Conference contribution
AN - SCOPUS:84920185419
T3 - International Conference on Control, Automation and Systems
SP - 1227
EP - 1232
BT - International Conference on Control, Automation and Systems
PB - IEEE Computer Society
T2 - 2014 14th International Conference on Control, Automation and Systems, ICCAS 2014
Y2 - 22 October 2014 through 25 October 2014
ER -