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Title Vehicle dynamics estimation using Kalman filtering : experimental validation / Moustapha Doumiati [and others]
Published London : Iste ; Hoboken, NJ : Wiley, 2013
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Description 1 online resource (xxii, 239 pages) : illustrations
Series Automation-control and industrial engineering series
Automation-control and industrial engineering series.
Contents Title Page; Contents; Preface; Introduction; I.1. Needs of ADAS systems; I.2. Limitation of available ADAS systems; I.3. This book versus existing studies; I.4. Laboratory vehicle; I.5. Outline; Chapter 1. Modeling of Tire and Vehicle Dynamics; 1.1. Introduction; 1.2. Tire dynamics; 1.2.1. Tire forces and moments; 1.2.1.1. Vertical/normal forces; 1.2.1.2. Longitudinal forces and longitudinal slip ratio; 1.2.1.3. Lateral forces and sideslip angle; 1.2.1.4. Aligning moment; 1.2.1.5. Coupling effects between longitudinal and lateral tire forces; 1.2.2. Tire-road friction coefficient
1.2.2.1. Normalized longitudinal traction force1.2.2.2. Normalized lateral traction force; 1.2.3. Quasi-static tire model; 1.2.3.1. Pacejka's magic tire model; 1.2.3.2. Dugoff's tire model; 1.2.3.3. Linear model; 1.2.4. Transient tire model; 1.3. Wheel rotational dynamics; 1.3.1. Static tire radius; 1.3.2. Effective tire radius; 1.4. Vehicle body dynamics; 1.4.1. Vehicle's vertical dynamics; 1.4.1.1. Suspension functions; 1.4.1.2. Quarter-car vehicle model; 1.4.2. Vehicle planar dynamics; 1.4.2.1. Four-wheel vehicle model; 1.4.2.2. Wheel-ground vertical forces calculation
1.4.2.3. Bicycle model1.4.3. Roll dynamics and lateral load transfer evaluation; 1.5. Summary; Chapter 2. Estimation Methods Based on Kalman Filtering; 2.1. Introduction; 2.2. State-space representation and system observability; 2.2.1. Linear system; 2.2.2. Nonlinear system; 2.3. Estimation method: why stochastic models?; 2.3.1. Closed-loop observer; 2.3.2. Choice of the observer type; 2.4. The linear Kalman filter; 2.5. Extension to the nonlinear case; 2.6. The unscented Kalman filter; 2.6.1. Unscented transformation; 2.6.2. UKF algorithm
2.7. Illustration of a linear Kalman filter application: road profile estimation2.7.1. Motivation; 2.7.2. Observer design; 2.7.3. Experimental results: observer evaluation; 2.7.3.1. Comparison with LPA signal; 2.7.3.2. Comparison with GMP signal; 2.8. Summary; Chapter 3. Estimation of the Vertical Tire Forces; 3.1. Introduction; 3.1.1. Related works; 3.2. Algorithm description; 3.3. Techniques for lateral load transfer calculation in an open-loop scheme; 3.3.1. Lateral acceleration calculation; 3.3.2. Roll angle calculation; 3.3.3. Limitation of the open-loop model
3.4. Observer design for vertical forces estimation3.5. Vertical forces estimation; 3.5.1. Observer OFzE design; 3.5.2. Observer OFzL formulation; 3.6. Analysis concerning the two-part estimation strategy; 3.7. Models observability analysis; 3.8. Determining the vehicle's mass; 3.8.1. Experimental validation of the vehicle's weight identification method; 3.9. Detection of rollover avoidance: LTR evaluation; 3.10. Experimental validation; 3.10.1. Regulation of observers; 3.10.2. Evaluation of observers; 3.10.3. Road experimental results; 3.10.3.1. Starting-slalom-braking test
Summary 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. I
Bibliography Includes bibliographical references (pages 227-235) and index
Notes Print version record
Subject Kalman filtering.
Motor vehicles -- Dynamics.
Motor vehicles -- Stability.
Form Electronic book
Author Doumiati, Moustapha, 1983-
ISBN 1118578988 (electronic bk.)
1118578996 (electronic bk.)
1118579003
9781118578988 (electronic bk.)
9781118578995 (electronic bk.)
9781118579008