Estimation of tire-road friction coefficient based on frequency domain data fusion

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• 作者：Long Chen ; Yugong Luo ; Mingyuan Bian ; Zhaobo Qin ; Jian Luo ; Keqiang Li ; ^{likq@tsinghua.edu.cn" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Tire-road friction coefficient ; Data fusion ; Active front steering system ; Dynamic tire model ; Natural frequency
• 刊名：Mechanical Systems and Signal Processing
• 出版年：2017
• 出版时间：15 February 2017
• 年：2017
• 卷：85
• 期：Complete
• 页码：177-192
• 全文大小：1565 K

文摘

Due to the noise of sensing equipment, the tire states, such as the sideslip angle and the slip ratio, cannot be accurately observed under the conditions with small acceleration, which results in the inapplicability of the time domain data based tire-road friction coefficient (TRFC) estimation method. In order to overcome this shortcoming, frequency domain data fusion is proposed to estimate the TRFC based on the natural frequencies of the steering system and the in-wheel motor driving system. Firstly, a relationship between TRFC and the steering system natural frequency is deduced by investigating its frequency response function (FRF). Then the lateral TRFC is determined by the steering natural frequency which is only identified using the information of the assist motor current and the steering speed of the column. With spectral comparison between the steering and driving systems, the data fusion is carried out to get a comprehensive TRFC result, using the different frequency information of the longitudinal and lateral value. Finally, simulations and experiments on different road surfaces validated the correctness of the steering system FRF and the effectiveness of the proposed approach.