Publication: A Constrained Dual Kalman Filter Based on pdf Truncation for Estimation of Vehicle Parameters and Road Bank Angle: Analysis and Experimental Validation
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2016-08-17
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Abstract
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.
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Vehicles, Roads, Estimation, Kalman filters, Control systems, Probability density function, Mathematical model
Bibliographic citation
Beatriz L. Boada, Daniel García-Pozuelo, Maria Jesús L. Boada, and Vicente Díaz. A Constrained Dual Kalman Filter based on pdf truncation for estimation of vehicle parameters and road bank angle: analysis and experimental validation. IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 4, April 2017. Pp. 1006-1016.