Adaptive joint estimates of vehicle mass and road grades for small acceleration driving scenarios
SUN Enxin1, YIN Yuming2, XIN Zhe1, LI Shengbo3, HE Jugang4, KONG Zhouwei4, LIU Xiupeng4
1. College of Engineering, China Agricultural University, Beijing 100083, China; 2. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; 3. Department of Automotive Engineering, Tsinghua University, Beijing 100084, China; 4. Chongqing Chang'an Automobile Co., Ltd., Chongqing 400023, China
Abstract：Vehicle mass and the road grade are key input parameters for automated vehicle decision and control algorithms. These two parameters are difficult to know accurately, but are tightly coupled for small acceleration driving scenarios with small inertias. The accuracy and convergence speed of existing estimation algorithms need to be further improved. A vehicle dynamics model is used here with an adaptive unscented Kalman filter (AUKF) algorithm for rapid, accurate joint estimates of the vehicle mass and road grade during small acceleration scenarios. The prediction model has a large initial mass noise with an adaptive shrink coefficient designed to adjust the prediction error covariance matrices. The adaptive shrink coefficient is related to the estimation result and the prediction error covariance matrices. Simulations and vehicle tests for various initial conditions show that the AUKF algorithm can accurately estimate the vehicle mass and road grade with an estimated vehicle mass error of less than 3% and a root-mean-square error in the road grade of less than 0.4°. In addition, the AUKF algorithm gives better convergence speeds for the vehicle mass and road grade estimates with longitudinal accelerations less than 0.3 m/s2 than the traditional UKF algorithm. When the initial mass error is within 40%, the estimated mass error converges to less than 3% within 10 seconds.
孙恩鑫, 殷玉明, 辛喆, 李升波, 何举刚, 孔周维, 刘秀鹏. 微小加速度下汽车质量-道路坡度自适应估计[J]. 清华大学学报（自然科学版）, 2022, 62(1): 125-132.
SUN Enxin, YIN Yuming, XIN Zhe, LI Shengbo, HE Jugang, KONG Zhouwei, LIU Xiupeng. Adaptive joint estimates of vehicle mass and road grades for small acceleration driving scenarios. Journal of Tsinghua University(Science and Technology), 2022, 62(1): 125-132.
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2022, Vol. 62 
