Tire model for estimator design to estimate vehicle motion in transient lateral maneuvers
Research Project, 2025
– 2028
Vehicle state estimation provides the underlying data support for environment perception, path planning and control execution, which directly affects the safety and reliability of decision-making. The selection of nonlinear tire model has a key influence on the accuracy and robustness of vehicle state estimation. On the basis of previous research, this paper selects LuGre tire model, Dugoff tire model, MF tire model and UniTire tire model as the research and analysis objects. According to the demand, the steering wheel angle signal, wheel speed signal and other information are selected as the observation signal and input signal of vehicle state estimation. The kinematics algorithm and dynamics algorithm are reasonably designed, and the high / low attachment road conditions are set up under the double lane change condition for simulation, and the longitudinal speed in the vehicle state is simulated. The friction coefficient of tire-road adhesion coefficient and the sideslip angle of mass center are estimated.
Participants
Bengt Jacobson (contact)
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Engineering and Autonomous Systems
Fredrik Bruzelius
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Engineering and Autonomous Systems
Mats Jonasson
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Engineering and Autonomous Systems
Dang Lu
Unknown organization
Funding
Jilin University
Funding Chalmers participation during 2025–2028
Related Areas of Advance and Infrastructure
Transport
Areas of Advance