Electronic International Standard Serial Number (EISSN)
Vehicles today are equipped with control systems that improve their handling and stability. Knowledge of road bank angle and vehicle parameters is crucial for good behavior in this type of control. This paper develops a new method for estimating different states, such as vehicle roll angle, road bank angle, and vehicle parameters. This method combines a dual Kalman filter with a probability density function truncation method to consider the parameter physical limitations. Experimental results show the effectiveness of the proposed method and demonstrate that the incorporation of parameter constraints improves its estimation accuracy. The proposed method provides an estimation of the parameters and the states' physical meaning and the stable values within the real boundary limits in contrast to other estimation methods.
vehicles; roads; estimation; kalman filters; control systems; probability density function; mathematical model