Earticle

초록

영어

Many vehicle state parameters such as the sideslip angle, yaw rate, and steering angle are important for the Advanced Driver Assist System and vehicle safety system. In the past, most methods used to estimate the vehicle state parameters were based on models with directly measured parameters (steering angle, yaw rate, etc.). In this paper, we pro-pose a method to estimate the vehicle state parameters (sideslip angle, yaw rate, and steering angle) based on the Extended Kalman Filter (EKF). The EKF is designed to deal with the bicycle model, linear tire model, and steering wheel model with measurements from in-vehicle sensors such as the electronic stability control system. Therefore, the re-sults show that the proposed algorithm for estimating the vehicle state parameters, side-slip angle, yaw rate, and steering angle can effectively estimate the vehicle state parame-ters when the speed of the vehicle varies. The results from this study can be evaluated and analyzed by evaluating the root mean square error. In future, the proposed algorithm can be used not only for the design of an automatic control system for the tracking vehicle but also for steering system fault diagnosis.

목차

Abstract
 1. Introduction
 2. Estimation of the Steering Angle
  2.1. System Configuration
  2.2. Vehicle Dynamic Model
  2.3. Extended Kalman Filter (EKF)
 3. Simulation and Results
 4. Conclusion
 References

키워드

저자

• Gyoungeun Kim [ Dept. of Electrical Engineering, Ulsan University, Korea ]
• Jaewoo Yoon [ Dept. of Electrical Engineering, Ulsan University, Korea ]
• Byeongwoo Kim [ Dept. of Electrical Engineering, Ulsan University, Korea ] corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605