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.

Highlights

  • Nowadays, one major objective in road transport systems is to reduce the number of accident victims

  • sliding mode observer (SMO) may have better performance compared to Luenberger observer (LO) because inherent properties of sliding mode theory

  • The results clearly indicate that, during real time implementation of second order complementary filter, the root mean square error of 0.62 degrees is observed for roll angle estimate

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Summary

Introduction

One major objective in road transport systems is to reduce the number of accident victims. Vehicles on the market are equipped with control system variants, such as ESC (Electronic Stability Control) and RSC (Roll Stability Control) [1,2] for the improvement of vehicle safety standards. The discussed systems must have knowledge of expected vehicle behavior in advance during different conditions and maneuvers for the proper actuation of the control system [3,4,5]. Knowledge about the roll angle of the vehicle is useful in RSC systems. Rollover accidents are responsible for nearly 33% of all deaths from passenger vehicle crashes [6].

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