Friction State Classification Based on Vehicle Inertial Measurements. Issue 5 (2019)

• Record Type: Journal Article
• Authors: Selmanaj, Donald; Corno, Matteo; Savaresi, Sergio M.
• Is Part Of: IFAC-PapersOnLine. Volume 52:Issue 5(2019)
• Page Start: 72
• Page End: 77
• Publication Date: 2019
• Subjects: Friction -- Vehicles dynamics -- Classification -- Recursive algorithms -- Nonlinear algorithms; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2019.09.012
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Tire-road friction is the most important characteristic defining the planar dynamics of wheeled vehicles. It has consequences on the drivability, stability and tuning of the active vehicle dynamics control systems. This paper proposes two online friction estimation methods designed for the adaptation of vehicle dynamics control algorithms. The problem is framed as a classification problem where inertial measurements are used to discriminate between high and low friction regimes. The first method merges a recursive least-squares (RLS) algorithm with a heuristic bistable logic to classify the friction condition and promptly react to its changes. The second method runs a classification algorithm on the slip-acceleration characteristic. Both methods simultaneously account for the longitudinal and lateral dynamics and are tested on experimental data.