Vehicle Dynamics: Fundamentals and Ultimate Trends

Description

This book examines the fundamentals of vehicle dynamics, as well as the recent trends in the field, such as torque vectoring control, vehicle state estimation, and autonomous vehicles. It investigates the most pressing problems that vehicle dynamics engineers have been facing nowadays, and the challenges of autonomous vehicles in terms of perception, path planning, and analysis of the road environment. The book will serve as a useful tool for graduate students and researchers in vehicle dynamics and control. Preface Contents Fundamentals on Vehicle and Tyre Modelling 1 Global Vehicle Modeling 1.1 Vehicle Dynamics 1.2 Dynamic Torsor Calculation 1.3 Exterior Forces Torsor Calculation 1.4 The Sprung Mass Dynamics 1.5 Model Simplification and Validation 2 Tire Modeling 2.1 Tire Physical Fundamentals 2.2 Tire Behavioural Models 2.3 Tire Models Linearization 2.4 Dynamic Saturation 2.5 Simulation of the Linearized Models 2.6 Tire Models Comparison 2.7 Validation and Relevance of Linearized Tire Models References Tyre Mechanics and Thermal Effects on Tyre Behaviour 1 Introduction to the Tyre 2 Tyre Structure 3 Mechanics of Tyres 4 Tyre Role in Vehicle Dynamics 5 Tyre Working Conditions Effects 6 Tyre Thermal Modelling in Vehicle Dynamics and Driving Simulations 7 Tyre Wear Modelling References Torque Vectoring Control for Enhancing Vehicle Safety and Energy Efficiency 1 Introduction 2 Torque Vectoring Control Framework 3 Reference Generator: rref, (βref) 3.1 Fundamentals on the Design of rref 3.2 Design of the Full Vehicle Cornering Response and Driving Modes 3.3 Concurrent Yaw Rate and Sideslip Angle Control 4 High Level Controller: Ttot, Mz 4.1 Calculation of Ttot 4.2 Calculation of Mz 4.3 Experimental Results and Further Remarks 5 Low Level Controller: Tij 5.1 Relationships Among Ttot, Mz and Tij 5.2 Computation of σ 5.3 An Alternative for Mz: The Energy Efficiency Mode 5.4 Experimental Results and Further Remarks References State and Parameter Estimation for Vehicle Dynamics 1 Introduction 1.1 Sensors in Vehicles 1.2 Engineering Rules to Extract Quantities of Interest 1.3 Sensor Fusion 1.4 Example: Longitudinal Vehicle Velocity 1.5 Summary 2 General Observer and Estimation Methods 2.1 Physics Driven Observer and Estimation Schemes 2.2 Kinematic Versus Dynamic Models for Estimation 2.3 Observability for Reliable State Observations and Estimates 2.4 Conclusion 3 Kalman Filter Based State Estimators for Vehicle Dynamics 3.1 Reference Data Description 3.2 Decoupled Vehicle State Estimation: Longitudinal Vehicle States 3.3 Lateral Vehicle State Estimation 4 Kalman Filter Based Estimators for Vehicle Dynamics with Unknown Tire Models 4.1 Coupled State/Input and State/Parameter Estimation 4.2 Lateral State/Force Estimation 4.3 Lateral State/Tire Parameter Estimation 4.4 Post-processing for Tire Model Extraction 5 Conclusion References Automated Driving Vehicles 1 Introduction 1.1 The Role of the Driver 1.2 Advanced Driver Assistance Systems and Automated Driving Systems 1.3 Concluding Remarks 2 Sensor Fusion 2.1 Sensor Fusion Configuration 2.2 Model-Based Approach 2.3 Data-Driven Approach 2.4 Safeguarding Sensor Fusion 3 Motion Planning for Autonomous Driving 3.1 Decision and Motion Planning for Autonomous Vehicles 3.2 Safe Driving Envelope Decision and Motion Optimization 3.3 Conclusion and Future Works 4 Automatic Steering Control for Autonomous Vehicle Path Tracking 4.1 Path Tracking Algorithm 4.2 Torque Controller 4.3 Vehicle Test Results: Automatic Steering Control 4.4 Stability Analysis 4.5 Conclusion 5 Speed and Clearance Control Algorithm for Autonomous Vehicle Longitudinal Control 5.1 Vehicle Model for Longitudinal Control 5.2 High Level Control: Desired Acceleration Design 5.3 Low Level Control: Determine Actuator Inputs 5.4 Simulation Study 5.5 Conclusion 6 Verification and Validation 6.1 Scenario-Based Approach 6.2 Accelerated Evaluation 6.3 The Case Study: Automatic Emergency Braking System References