A comparative study of the recursive least squares and fuzzy logic estimation methods for the measurement of road adhesion coefficient

ABSTRACT

Vehicle active safety system is the hotspot of current research and development, and the road adhesion coefficient is one of the essential parameters in the development of automobile active safety system, which plays a pivotal role in automobile safety. To improve the real-time performance and accuracy of the road adhesion coefficient, this paper proposes different control methods and compares and analyzes them. To accurately estimate the road adhesion coefficient in real-time, an eight-degree-of-freedom vehicle model was adopted in this paper. According to the tire torque and wheel speed, the adhesion coefficient was estimated based on the second-order nonlinear extended state observer. The experimental data, such as slip rate, using the improved tire model, is based on the recursive least squares method with forgetting factor and fuzzy logic algorithm real-time of tire-road friction coefficient estimation. The results show that the observer can effectively observe utilisation adhesion coefficient, and both control algorithms can estimate the road adhesion coefficient in real-time, effectively and quickly. On different roads, the use of the recursive least squares algorithm resulted in higher estimation accuracy, better robustness, and better control effect than using a fuzzy logic algorithm.

KEYWORDS:

• Road adhesion coefficient
• Vehicle active safety system
• Extended state observer
• Utilisation adhesion coefficient
• Recursive least squares method
• Fuzzy logic algorithm

Acknowledgments

This research was supported by the Key scientific and technological project of Henan Province (No. 172102210022, No. 182102210086), Natural Science Foundation of Henan Province of China (No. 182300410265), and National Undergraduate Training Program for Innovation and Entrepreneurship (No. 201810460069).

Availability of data and materials

Not applicable.

Consent for publication

The authors provided consent to publish the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Natural Science Foundation of Henan Province [182300410265]; Key scientific and technological project of Henan Province [172102210022]; Key scientific and technological project of Henan Province [182102210086]; National Undergraduate Training Program for Innovation and Entrepreneurship [201810460069].

Notes on contributors

Gengxin Qi

Gengxin Qi was born in 1997 in Zibo, Shandong Province. He received his bachelor's degree in vehicle engineering from Henan Polytechnic University in 2019 and is currently pursuing a master's degree in mechanical engineering at Henan Polytechnic University. His research interests include vehicle system dynamics and its control technology and active safety control system development.

Xiaobin Fan

Xiaobin Fan, male, Han nationality, born in Nanyang, Henan Province, in July 1977, doctor, associate professor, graduated from University of Science and Technology Beijing, majoring in mechanical design and theory in 2007.His main research interests include vehicle system dynamics and control, active safety control system development, system parameter identification, etc.

Hao Li

Hao Li was born in Xincai County, Henan Province in 1996.He received his bachelor's degree in vehicle engineering from Henan Polytechnic University in 2019 and is currently pursuing a master's degree in mechanical engineering at Henan Polytechnic University. His research interests are automotive system dynamics and its control technology and active safety control system development.