Vehicle Dynamics Estimation using Kalman Filtering


Experimental Validation

Vehicle Dynamics Estimation using Kalman Filtering

Moustapha Doumiati, Fahad Bin Sultan University, Saudi Arabia
Ali Charara and Alessandro Victorino, Compiègne University of Technology, France
Daniel Lechner, French National Institute for Transport and Safety Research, Bron, France


ISBN : 9781848213661

Publication Date : November 2012

Hardcover 272 pp

125.00 USD

Co-publisher

Description


Vehicle dynamics and stability have been of considerable interest for a number of years. The obvious dilemma is that people naturally desire to drive faster and faster yet expect their vehicles to be “infinitely” stable and safe during all normal and emergency maneuvers. For the most part, people pay little attention to the limited handling potential of their vehicles until some unusual behavior is observed that often results in accidents and even fatalities.

This book presents several model-based estimation methods which involve information from current potential-integrable sensors. Improving vehicle control and stabilization is possible when vehicle dynamic variables are known. The fundamental problem is that some essential variables related to tire/road friction are difficult to measure because of technical and economical reasons. Therefore, these data must be estimated. It is against this background, that this book’s objective is to develop estimators in order to estimate the vehicle’s load transfer, the sideslip angle, and the vertical and lateral tire/road forces using a roll model. The proposed estimation processes are based on the state observer (Kalman filtering) theory and the dynamic response of a vehicle instrumented with standard sensors. These estimators are able to work in real time in normal and critical driving situations. Performances are tested using an experimental car in real driving situations.

This is exactly the focus of this book, providing students, technicians and engineers from the automobile field with a theoretical basis and some practical algorithms useful for estimating vehicle dynamics in real-time during vehicle motion.

Contents


1. Modeling of Tire and Vehicle Dynamics.
2. Estimation Methods Based on Kalman Filtering.
3. Estimation of the Vertical Tire Forces.
4. Estimation of the Lateral Tire Forces.
5. Embedded Real-Time System for Vehicle State Estimation: Experimental Results.

About the authors


Moustapha Doumiati is currently Assistant Professor in the Department of Electrical Engineering, Fahad Bin Sultan University, Saudi Arabia. His main research interests include robust control, state-observers, and linear parameter-varying systems, with applications on intelligent vehicles, driving assistance systems and electric machines.

Ali Charara is Professor in the Department of Information Processing Engineering, Compiègne University of Technology, France, where he is also the Director of the Heudiasyc Laboratory. His current research interests include intelligent vehicles, driving assistance systems, state observers, and the diagnosis of electromechanical systems.

Alessandro Victorino is Associate Professor in the Computer Science Department, Compiègne University of Technology, France, where he is also a member of the Heudiasyc Laboratory. His current research interests include nonlinear state estimation, vehicle dynamics, cooperative perception systems, localization and mapping, sensor-based control, and navigation of autonomous systems.

Daniel Lechner is Research Director of the Department of Accident Mechanism Analysis (Salon de Provence) at the French National Institute for Transport and Safety Research, Bron, France, which he currently also heads. His research interests include vehicle modeling, instrumentation and testing, active safety embedded applications, and road accident analysis.