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.
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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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