A Novel Roll and Pitch Estimation Approach for a Ground Vehicle Stability Improvement Using a Low Cost IMU.

Clicks: 213
ID: 92231
2020
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Onboard attitude estimation for a ground vehicle is persuaded by its application in active anti-roll bar design. Conventionally, the attitude estimation problem for a ground vehicle is a complex one, and computationally, its solution is very intensive. Lateral load transfer is an important parameter which should be taken in account for all roll stability control systems. This parameter is directly related to vehicle roll angle, which can be measured using devices such as dual antenna global positioning system (GPS) which is a costly technique, and this led to the current work in which we developed a simple and robust attitude estimation technique that is tested on a ground vehicle for roll mitigation. In the first phase Luenberger and Sliding mode observer is implemented using simplest roll dynamics model to measure the roll angle of a vehicle and the validation of results is carried using commercial software, CarSim (CarSim, Ann Arbor, MI, USA). In the second phase of research, complementary and Kalman filters have been designed for attitude estimation. In the third phase, a low-cost inertial measurement unit (IMU) is mounted on a vehicle, and both the complementary filter (CF) and Kalman filter (KF) are applied independently to measure the data for both smooth and uneven terrains at four different frequencies. We compared the simulated and real-time results of roll and pitch angles obtained using the complementary and Kalman filters. Using the proposed method, the achieved root mean square error (RMSE) is less than 0.73 degree for pitch and 0.68 degree for roll, with a sample time of 2 ms. Thus, a warning signal can be generated to mitigate roll over. Hence, we claim that our proposed method can provide a low-cost solution to the roll-over problem for a road vehicle.
Reference Key
kamal-mazhar2020asensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Kamal Mazhar, Malik;Khan, Muhammad Jawad;Bhatti, Aamer Iqbal;Naseer, Noman;
Journal sensors
Year 2020
DOI
E340
URL
Keywords
state estimation attitude estimation vehicle dynamics observer roll angle health risk assessment delphi technique left-behind elderly antibacterial enterococcus faecalis endodontic sealer mineral trioxide aggregate tricalcium silicate white portland cement

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.