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研究生(外文):lingyuan, Hsu
論文名稱(外文):Vehicle rollover prediction system using states observers
指導教授(外文):tsunglin, Chen
外文關鍵詞:vehicle rolloverstates observerdynamics estimationdynamics predictionfull-car modelroad conditioncovariance matrixswitching computation schemeseparated yaw-roll model
  • 被引用被引用:2
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此預測系統的挑戰之一為如何建立以完整車輛模型(高階、高度非線性系統)為基礎之狀態觀察器。我們提出一適用於非線性系統之新型觀察矩陣,藉由此觀察矩陣來簡化完整車輛模型,並拆解成兩個低階子模型:側傾、橫擺子模型。如此一來,即可針對兩低階子模型分別建立狀態觀察器,再經由相似於傳統ADI(Alternative Direction Implicit)之切換式數值演算法,來進行車輛即時動態估測。由本論文中的ADI-like切換式演算機制之收斂穩定度分析中可知,此演算機制能成功的使兩個從複雜系統中解析出之子系統,近似於原複雜系統之動態行為。
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 i
Abstract ii
Acknowledgement iii
Contents iv
List of Tables vi
List of Figures vii
Mathematical Notations viii
Chapter 1 Introduction 1
1.1 Motivations and Objectives 1
1.2 Previous Research Survey 2
1.2.1 Dynamic Modeling of Full-State Vehicle 2
1.2.2 Prediction Method in Vehicle Rollover 2
1.2.3 Neglect of the Vehicle Pitch Motion 3
1.2.4 Numerical Algorithm in Switching Scheme 3
1.3 Construction of this Vehicle Rollover Prediction System 4
1.4 Outline of this Thesis 4
Chapter 2 Full-Car Model 6
2.1 Dynamic Frames of the Vehicle 7
2.1.1 Euler Transformation 7
2.2 Sprung Mass System 10
2.2.1 Vehicle Rotational Motion 10
2.2.2 Vehicle Translational Motion 17
2.3 Unsprung Mass System 19
2.3.1 Wheel Steering System 19
2.3.2 Suspension Force 20
2.3.3 Nonlinear Tire Model 22
2.3.4 Wheel Dynamics 24
2.4 Road Condition 25
2.5 Summary 27
2.6 Full-Car Model Validation 28
2.7 Conclusions 28
Chapter 3 System Observability of Full-Car Model 30
3.1 Nonlinear Observability Matrix 30
3.2 Novel Observability Matrix along a Trajectory 31
3.3 Negligence of Pitch Motions 31
3.4 Integrated Yaw-Roll Model 32
Chapter 4 Vehicle Rollover Prediction System 34
4.1 Separated Yaw-Roll Model 34
4.1.1 Vehicle Yaw Model 35
4.1.2 Vehicle Roll Model 36
4.1.3 Separated Yaw-Roll Model Validation 39
4.2 Switching Observer Scheme 39
4.2.1 Error Source 40
4.2.2 Preliminaries for the Stability Analysis of Switching Computation Scheme 40
4.2.3 Stability Analysis for “Explicit Euler Method” Approximation 41
4.2.4 Stability Analysis for “Runge-Kutta Method” Approximation 44
4.3 Sensor Selections 48
4.3.1 Sensors for Yaw Model 49
4.3.2 Sensors for Roll Model 51
4.4 Nonlinear Observer Algorithm 51
4.5 Block Diagram for the Prediction System 52
Chapter 5 Simulation and Results 53
5.1 Case I 54
5.2 Case II 54
5.3 Case III 54
5.4 Case IV 57
5.5 Case V 57
5.6 Conclusions 59
Chapter 6 Conclusions and Future Works 60
6.1 Conclusions 60
6.2 Future Works 62
Reference 64
Appendix 67
A. The Separation of the Integrated Yaw-Roll Model from Euler Transformation 67
B. Parameters of the Full-Car Model 67
B.1 Vehicle Inertial and Geometric Parameters 68
B.2 Suspension Coefficients 68
B.3 Tire Geometric and Experiential Parameters 69
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