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Vehicle dynamics estimation using Kalman filtering [[electronic resource] ] : experimental validation / / Moustapha Doumiati ... [et al.] ; series editor, Bernard Dubuisson
Vehicle dynamics estimation using Kalman filtering [[electronic resource] ] : experimental validation / / Moustapha Doumiati ... [et al.] ; series editor, Bernard Dubuisson
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (263 p.)
Disciplina 629.8312
Altri autori (Persone) DoumiatiMoustapha
DubuissonBernard
Collana Automation - control and industrial engineering series
Soggetto topico Motor vehicles - Dynamics
Kalman filtering
ISBN 1-118-57898-8
1-118-57899-6
1-299-18669-6
1-118-57900-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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 force 1.2.2.2. 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 model 1.4.3. 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 estimation 2.7.1. 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 estimation 3.5. 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
3.10.3.2. Circle-braking test
Record Nr. UNINA-9910141503703321
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Vehicle dynamics estimation using Kalman filtering : experimental validation / / Moustapha Doumiati ... [et al.] ; series editor, Bernard Dubuisson
Vehicle dynamics estimation using Kalman filtering : experimental validation / / Moustapha Doumiati ... [et al.] ; series editor, Bernard Dubuisson
Edizione [1st ed.]
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (263 p.)
Disciplina 629.8312
Altri autori (Persone) DoumiatiMoustapha
DubuissonBernard
Collana Automation - control and industrial engineering series
Soggetto topico Motor vehicles - Dynamics
Kalman filtering
ISBN 1-118-57898-8
1-118-57899-6
1-299-18669-6
1-118-57900-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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 force 1.2.2.2. 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 model 1.4.3. 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 estimation 2.7.1. 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 estimation 3.5. 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
3.10.3.2. Circle-braking test
Record Nr. UNINA-9910828876303321
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui