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Book Description

This book studies the design optimization, state estimation, and advanced control methods for cyber-physical vehicle systems (CPVS) and their applications in real-world automotive systems.

First, in Chapter 1, key challenges and state-of-the-art of vehicle design and control in the context of cyber-physical systems are introduced. In Chapter 2, a cyber-physical system (CPS) based framework is proposed for high-level co-design optimization of the plant and controller parameters for CPVS, in view of vehicle's dynamic performance, drivability, and energy along with different driving styles. System description, requirements, constraints, optimization objectives, and methodology are investigated. In Chapter 3, an Artificial-Neural-Network-based estimation method is studied for accurate state estimation of CPVS. In Chapter 4, a high-precision controller is designed for a safety-critical CPVS. The detailed control synthesis and experimental validation are presented. The application results presented throughout the book validate the feasibility and effectiveness of the proposed theoretical methods of design, estimation, control, and optimization for cyber physical vehicle systems.

Table of Contents

  1. Preface
  2. Introductions
  3. Co-Design Optimization for Cyber-Physical Vehicle System
    1. Problem Formulation
      1. Hierarchical Optimization Methodology
      2. System Description
      3. Driving Event
      4. Driving Style Recognition
      5. Requirements for the Design and Optimization of CPVS
      6. Constraints for Vehicle Design and Optimization
    2. System Modeling and Validation
      1. Electric Powertrain system
      2. Blended Brake System
      3. Dynamic Model of the Vehicle and Tyre
      4. Experimental Validation
    3. Controller Design for Different Driving Styles
      1. High-Level Controller Architecture
      2. Low-Level Controller for Different Driving Styles
    4. Driving-Style-Based Performance Exploration and Parameter Optimization
      1. Design Space Exploration
      2. Performance Exploration Methodology
      3. Driving-Style-Oriented Multi-Objective Optimization
    5. Optimization Results and Analysis
      1. Optimization Results for the Aggressive Driving Style
      2. Optimization Results of the Moderate Driving Style
      3. Optimization Results of the Conservative Driving Style
      4. Comparison and Discussion
  4. State Estimation of Cyber-Physical Vehicle Systems
    1. Multilayer Artificial Neural Networks Architecture
      1. System Architecture
      2. Multilayer Feed-Forward Neural Network
    2. Standard Backpropagation Algorithm
    3. Levenberg–Marquardt Backpropagation
    4. Experimental Testing and Data Collection
      1. Testing Vehicle and Scenario
      2. Data Collection and Processing
      3. Feature Selection and Model Training
    5. Experiment Results and Discussions
      1. Results of the ANN-Based Braking Pressure Estimation
      2. Importance Analysis of the Selected Features
      3. Comparison of Estimation Results with Different Learning Methods
  5. Controller Design of Cyber-Physical Vehicle Systems
    1. Description of the Newly Proposed BBW System
    2. Control Algorithm Design for Hydraulic Pump-Based Pressure Modulation
    3. Control Algorithm Design for Closed-Loop Pressure-Difference-Limiting Modulation
      1. Linear Modulation of On/Off Valve
      2. Closed-Loop Pressure-Difference-Limiting Control
    4. Hardware-in-the-Loop Test Results
      1. Comparison of HPBPM and CLPDL Control
      2. Brake Blending Algorithm Based on CLPDL Modulation
  6. Conclusions
  7. References (1/2)
  8. References (2/2)
  9. Authors' Biographies
  10. Blank Page (1/2)
  11. Blank Page (2/2)
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