Tire Radii Estimation Using a Marginalized Particle Filter

Christian Lundquist, Rickard Karlsson, Emre Ozkan, Fredrik Gustafsson
2014 IEEE transactions on intelligent transportation systems (Print)  
In this work measurements of individual wheel speeds and absolute position from a global positioning system (GPS) are used for high-precision estimation of vehicle tire radii. The radii deviation from its nominal value is modeled as a Gaussian random variable and included as noise components in a simple vehicle motion model. The novelty lies in a Bayesian approach to estimate online both the state vector and the parameters representing the process noise statistics using a marginalized particle
more » ... ilter. Field tests show that the absolute radius can be estimated with sub-millimeter accuracy. The approach is tested in accordance with the ECE R-64 regulation on a large data set (22 tests, using two vehicles and 12 different tire sets), where tire deflations are detected successfully, with high robustness, i.e., no false alarms. The proposed marginalized particle filter approach outperforms common Kalman filter based methods used for joint state and parameter estimation when compared with respect to accuracy and robustness.
doi:10.1109/tits.2013.2284930 fatcat:uxo4aclzsrdibnynr4nyrgool4