Title :
On Estimations of Stochastic Slip Rates by Using Kalman Filter
Author :
Feng Rung Hu ; Jia Sheng Hu
Author_Institution :
Dept. of Mathematic Educ., Nat. Taichung Univ. of Educ., Taichung, Taiwan
Abstract :
In this study, a stochastic model with two independent Levy processes is considered. This model can endow the tires´ slip ratio estimation of electric vehicles with a new aspect. With the manipulations of stochastic model, the purposes are to probe the asymptotic behavior of the states in a specific vehicle model. Three important results are obtained in this study. Firstly, under the specific framework, the state of Kalman filter has relation to the expectation. Secondly, for any fixed time period, as the Levy process decays to Brownian motion, the filtering states are the same. Finally, the system´s controllability can be checked under the affections of stochastic injections.
Keywords :
Kalman filters; electric vehicles; stochastic processes; tyres; Brownian motion; Kalman filter; asymptotic behavior; electric vehicles; filtering states; fixed time period; independent Levy processes; stochastic injections; stochastic model; stochastic slip rate estimation; system controllability; tire slip ratio estimation; Controllability; Electric vehicles; Estimation; Kalman filters; Tires; Wheels; Kalman filter; controllability; slip rate of tires; stochastic process;
Conference_Titel :
Computer, Consumer and Control (IS3C), 2014 International Symposium on
Conference_Location :
Taichung
DOI :
10.1109/IS3C.2014.196