What is it about?

In regard to vehicle designing, advanced vehicle safety systems have recently received great attention. In these systems, knowledge of longitudinal and lateral velocities and road friction coefficient variable is needed. In this article, with integration of EKF, RLS and NN algorithms, tire /road friction coefficient is estimated.

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Why is it important?

In many previous works, the estimation methods were not accurate or often were confined to estimation of the longitudinal and lateral normalized traction forces instead of maximum friction coefficient. We believe that our proposed algorithm is a novel work with low cost which could be developed and consequently used in many vehicle safety systems.

Perspectives

This article gave me a creative viewpoint at how to deal with the difficult situations of solving an issue. Having an analytical understanding of issues is always a need for engineering researchers, but analytical methods for solving complex problems are not always responsive, and numerical methods can be used together with reverse engineering techniques.

Mr Arash Zareian
Khajeh Nasir Toosi University of Technology

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This page is a summary of: Estimation of road friction coefficient using extended Kalman filter, recursive least square, and neural network, Proceedings of the Institution of Mechanical Engineers Part K Journal of Multi-body Dynamics, May 2015, SAGE Publications,
DOI: 10.1177/1464419315573353.
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