期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 71, 期 4, 页码 3704-3714出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2022.3148133
关键词
Roads; Estimation; Quaternions; Accelerometers; Kalman filters; Mathematical models; Vehicle dynamics; Road grade estimation; quaternion unscented Kalman filter; allan variance; simplified vehicle-road model
资金
- Science and Technology on Vehicle Transmission Laboratory, China [6142213200306]
This paper presents a novel model-based road grade estimation approach, which has been verified to have good accuracy and precision through experiments.
The available road grade information makes a significant impact on improving the quality of vehicle control. In order to solve the limited application scenario and insufficient accuracy of current road grade estimation methods, this paper presents a novel model-based road grade estimation approach. First, a Quaternion Unscented Kalman Filter (QUKF) using the three-axle angular velocities and three-axle accelerations from a low-cost Inertial Measurement Unit (IMU) and the vehicle speed from CAN bus is designed to estimate the pitch angle of the vehicle. In particular, the measurement noise of UKF is analyzed by integrating Allan variance method. Second, a simplified vehicle-road model is derived to represent the road grade with the estimated pitch angle and longitudinal acceleration. Then, the performance of the proposed algorithm is tested by co-simulation of MATLAB/Simulink and CarSim, which indicates that the error rate of estimation is within 4%. Finally, the feasibility and accuracy of the proposed method implemented in the embedded prototype are verified in experiments conducted on standard slopes.
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