Vehicle Longitudinal Velocity Estimation based on Kalman Filter with Unknown Input

Comprehensive knowledge about absolute or true velocity of a vehicle leads to increasing performance of dynamics control systems like auto-traction systems and anti-lock brake systems. In this paper, longitudinal velocity during braking is estimated by measuring the wheel speed and employing a Kalman filter. In estimation procedure, we use a five degree-of-freedom vehicle motion model and the corresponding analytic tire force equations. Most of previous researches, in the field of longitudinal velocity estimation, unfortunately consider the corresponding braking torque as a known input, while it is very difficult to measure or has to use additive expensive sensor. To solve this problem, in this paper, we develop the Unknown Input Kalman Filter to estimate longitudinal vehicle velocity by ignoring the braking torque effects in estimation procedure. This approach can be applied to estimate train longitudinal velocity.

Keywords:

Longitudinal velocity estimation , Kalman filter , Unknown input , real time systems