期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 70, 期 3, 页码 2239-2249出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2021.3059432
关键词
Tires; Accelerometers; Acceleration; Testing; Intelligent sensors; Vehicle dynamics; Optical sensors; Intelligent tire technology; machine learning; neural network; vehicle system dynamics; tire slip angle estimation
资金
- National Natural Science Foundation of China [51875236, 61790561]
- China Automobile Industry Innovation and Development Joint Fund [U1864206]
This study proposes an accurate estimation method for tire slip angles by combining intelligent tire technology and machine learning techniques. Experimental results show that machine learning techniques, especially in frequency domain, can accurately estimate tire slip angles up to 10 degrees. Accurate estimation of tire slip angles is crucial for advanced vehicle control.
Tire slip angle is a vital parameter in tire/vehicle dynamics and control. This paper proposes an accurate estimation method by the fusion of intelligent tire technology and machine-learning techniques. The intelligent tire is equipped by MEMS accelerometers attached to its inner liner. First, we describe the intelligent tire system along with the implemented testing apparatus. Second, experimental results under different loading and velocity conditions are provided. Then, we show the procedure of data processing, which will be used for training five different machine learning techniques to estimate tire slip angles. The results show that the machine learning techniques, especially in frequency domain, can accurately estimate tire slip angles up to 10 degrees. More importantly, with the accurate tire slip angle estimation, all other states and parameters can be easily and precisely obtained, which is significant to vehicle advanced control, and thus this study has a high potential to obviously improve the vehicle safety especially in extreme maneuvers.
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