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

Kamal Mazhar, Malik ; Khan, Muhammad Jawad ; Bhatti, Aamer Iqbal ; Naseer, Noman

Sensors (Basel, Switzerland), 2020-01, Vol.20 (2), p.340 [Periódico revisado por pares]

Switzerland: MDPI AG

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  • Título:
    A Novel Roll and Pitch Estimation Approach for a Ground Vehicle Stability Improvement Using a Low Cost IMU
  • Autor: Kamal Mazhar, Malik ; Khan, Muhammad Jawad ; Bhatti, Aamer Iqbal ; Naseer, Noman
  • Assuntos: Accelerometers ; Accuracy ; Algorithms ; attitude estimation ; Bias ; Control stability ; Estimates ; Global positioning systems ; GPS ; Inertial platforms ; Kalman filters ; Lateral loads ; Load transfer ; Low cost ; Microelectromechanical systems ; Noise ; observer ; Parameters ; Pitch (inclination) ; Pitch estimation ; roll angle ; Rolling motion ; Rollover ; Root-mean-square errors ; Sensors ; Sliding mode control ; state estimation ; vehicle dynamics ; Vehicles
  • É parte de: Sensors (Basel, Switzerland), 2020-01, Vol.20 (2), p.340
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
  • Descrição: 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.
  • Editor: Switzerland: MDPI AG
  • Idioma: Inglês
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