Vehicle Parameter Identification and its Use in Control for Safe Path Following
- Author(s): HONG, SANGHYUN;
- Advisor(s): Hedrick, John Karl;
- et al.
This thesis develops vehicle parameter identification algorithms, and applies identified parameters to a controller designed for safe path following.
A tire-road friction coefficient is estimated using an in-tire accelerometer to measure acceleration signals directly from the tires.
The proposed algorithm first determines a tire-road contact patch with a radial acceleration profile.
The estimation algorithm is based on tire lateral deflections obtained from lateral acceleration measurements only inside the contact patch.
A new model is derived for the lateral deflection profiles, which provides robustness to orientation-variation of the accelerometer body frame during tire rotation.
A novel algorithm is developed to identify three inertial parameters: sprung mass, yaw moment of inertia, and longitudinal position of the center of gravity.
A correlation of inertial parameters is derived and is used for the identification algorithm.
Inertial parameters and vehicle states are simultaneously estimated with a dual unscented Kalman filter based on a nonlinear vehicle model.
In order to activate and de-activate different modes of the proposed
algorithm, a local observability analysis is performed with the nonlinear vehicle model.
The performance and robustness of the proposed approach are demonstrated with extensive CarSim simulations and experimental tests on a flat road with a constant tire-road friction coefficient.
Following a curved road can be dangerous if autonomous vehicles do not take roll motion into consideration.
A control algorithm is designed to prevent a dangerous vehicle state induced by roll motion while following a curved road.
Roll motion is suppressed throughout cornering with model predictive control.
A four-wheel nonlinear vehicle model with roll dynamics and a tire brush model are utilized for the prediction of the vehicle state.
An optimal balance in the trade-off between vehicle speed and
roll motion is achieved with full braking as a control actuator.
Identified vehicle inertial parameters are incorporated into the designed controller.
CarSim simulations illustrate the performance of the proposed controller and the effect of the vehicle parameter estimator.