# 臺灣博碩士論文加值系統

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 In this thesis, we present a vehicle rollover prediction method, which employs the “full-car model” accompanied with road conditions and states observer techniques, to predict vehicle dynamics and declare a rollover happening by the vehicle roll angle in future time. This prediction method presents a strong evidence for a rollover occurrence, and the methodology can be widely applied to vehicles with different dynamic characteristics.Based on the novel observability matrix proposed in this thesis, the “full-car model” is broken down into two subsystems. Two states observers are constructed for each subsystem respectively and do the switching scheme for the vehicle states estimation, which the approach is similar to the conventional alternative direction implicit method (ADI). The proposed ADI-like computation scheme enables a states observer design for a highly nonlinear and high order dynamic system.Simulation results indicate that, with the following three sensors: longitudinal velocity sensor, lateral accelerometer and suspension displacement sensor, we are able to predict a vehicle rollover occurrence correctly, which is initiated by a quick wheels maneuvering on a slope.
 摘　要 iAbstract iiAcknowledgement iiiContents ivList of Tables viList of Figures viiMathematical Notations viiiChapter 1 Introduction 11.1 Motivations and Objectives 11.2 Previous Research Survey 21.2.1 Dynamic Modeling of Full-State Vehicle 21.2.2 Prediction Method in Vehicle Rollover 21.2.3 Neglect of the Vehicle Pitch Motion 31.2.4 Numerical Algorithm in Switching Scheme 31.3 Construction of this Vehicle Rollover Prediction System 41.4 Outline of this Thesis 4Chapter 2 Full-Car Model 62.1 Dynamic Frames of the Vehicle 72.1.1 Euler Transformation 72.2 Sprung Mass System 102.2.1 Vehicle Rotational Motion 102.2.2 Vehicle Translational Motion 172.3 Unsprung Mass System 192.3.1 Wheel Steering System 192.3.2 Suspension Force 202.3.3 Nonlinear Tire Model 222.3.4 Wheel Dynamics 242.4 Road Condition 252.5 Summary 272.6 Full-Car Model Validation 282.7 Conclusions 28Chapter 3 System Observability of Full-Car Model 303.1 Nonlinear Observability Matrix 303.2 Novel Observability Matrix along a Trajectory 313.3 Negligence of Pitch Motions 313.4 Integrated Yaw-Roll Model 32Chapter 4 Vehicle Rollover Prediction System 344.1 Separated Yaw-Roll Model 344.1.1 Vehicle Yaw Model 354.1.2 Vehicle Roll Model 364.1.3 Separated Yaw-Roll Model Validation 394.2 Switching Observer Scheme 394.2.1 Error Source 404.2.2 Preliminaries for the Stability Analysis of Switching Computation Scheme 404.2.3 Stability Analysis for “Explicit Euler Method” Approximation 414.2.4 Stability Analysis for “Runge-Kutta Method” Approximation 444.3 Sensor Selections 484.3.1 Sensors for Yaw Model 494.3.2 Sensors for Roll Model 514.4 Nonlinear Observer Algorithm 514.5 Block Diagram for the Prediction System 52Chapter 5 Simulation and Results 535.1 Case I 545.2 Case II 545.3 Case III 545.4 Case IV 575.5 Case V 575.6 Conclusions 59Chapter 6 Conclusions and Future Works 606.1 Conclusions 606.2 Future Works 62Reference 64Appendix 67A. The Separation of the Integrated Yaw-Roll Model from Euler Transformation 67B. Parameters of the Full-Car Model 67B.1 Vehicle Inertial and Geometric Parameters 68B.2 Suspension Coefficients 68B.3 Tire Geometric and Experiential Parameters 69
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