Estimation of Vehicle Parameters using Kalman Filter: Review

Abstract

Automobiles are indispensable in our modern society, and vehicle safety is consequently very important in our everyday life. In the past few decades, vehicle dynamics control systems have been developed to improve control and safety of vehicles. Vehicle dynamics control systems seek to prevent unintended vehicle behavior through active control and help drivers maintain control of their vehicles. The main function of electronic stability control is to provide enhanced stability and control not only when accelerating and braking but also when cornering and avoiding obstacles. These advanced technologies of has been developed in the pursuits of increased safety, improved performance and cost efficiency. A new method of the vehicle parameters estimation by combining GPS measurements with a vehicle dynamics model based estimator. This method presents a problem because many of the vehicle parameters maybe unknown and or change over time. Therefore, a method to identify when a correct estimator model is being used must be developed. The new estimation algorithm, which is based on using GPS in a vehicle dynamics model based estimator, is tested both in simulation and on expected data.