The Intelligent Environment Friendly Vehicle: Concept, Architecture and Implementation

Preface
Contents
1 Introduction to i-EFV
1.1 Introduction
1.2 Concept and Connotation of i-EFV
1.3 System Characteristics of i-EFV
1.4 New Architecture of i-EFV
1.4.1 Intelligent Information Exchange System
1.4.2 Clean Energy Powertrain
1.4.3 Electronically-Controlled Chassis System
1.5 Typical System Application of i-EFV
1.5.1 i-HEV Based on the Exchange of Driving Environment Information
1.5.2 i-BEV Based on Vehicle-Infrastructure-Network Interaction
References
2 Key Challenges and Key Technology Systems of i-EFV
2.1 Pain Points of i-EFV
2.2 Key Scientific Issues Involved in i-EFV
2.2.1 Coupling Mechanism of Multi-physical-Process of the i-EFV’s Complex Electromechanical System
2.2.2 Modeling and Collaborative Control of the “Human-Vehicle-Infrastructure” Generalized Mechanical Dynamics System
2.3 Key Technical Systems [2, 3] of i-EFV
2.3.1 Structure Sharing
2.3.2 Information Fusion
2.3.3 Control Collaboration
References
3 Structure Sharing Technology for i-EFV
3.1 Overview of Structure Sharing Optimization and Integration Technology
3.1.1 Concept of Structure Sharing Integration
3.1.2 Connotation of Structure Sharing Integration
3.2 Structure Sharing Technology Applied in the Vehicle System
3.2.1 Structure Sharing of a Multi-sensor System
3.2.2 Structure Sharing of Vehicle Control
3.2.3 Structure Sharing of Actuation System
3.2.4 System Functional Safety Design Under Structure Sharing
3.3 Architecture Design for the Integrated Intelligent Driving System Based on Structure Sharing
3.3.1 Architecture Design Principles and Overall Composition
3.3.2 Architecture Design for Sensor Information Sharing
3.3.3 Architecture Design for Controller Resource Sharing
3.3.4 Architecture Design for Actuator Operation Co-management
3.4 Analysis on Features of Integrated Structure Sharing of the Intelligent Driving System
3.4.1 Evaluation Indicator and Calculation Model
3.4.2 Comparative Analysis with Functional Superposition Integration
3.4.3 Feature Summary of the Integrated Structure Sharing Architecture
3.5 Optimal Configuration of Onboard Environment Perception Sensors Based on Structure Sharing
3.5.1 Modeling the Onboard Multi-sensor System
3.5.2 Sensor configuration’s Multi-dimensional Evaluation Indicator System
3.5.3 Establishing the Sensor Configuration Optimization Problem
3.5.4 Multi-objective Optimization Solution Algorithm
3.6 Structure Sharing Technology for i-EFV Driving/Braking System
3.6.1 Structure Sharing Technology Based on Hybrid Driving System
3.6.2 Structure Sharing Technology of Braking System Based on Motor Braking and Electronically-Controlled Hydraulic Braking
References
4 Information Fusion Technologies for i-EFV
4.1 Multi-sensor Information Fusion Technology and Research State
4.2 Information Fusion System Architecture of i-EFV
4.2.1 Object Information Identification
4.2.2 “Human-Vehicle-Infrastructure” Feature Extraction
4.2.3 Vehicle State Expectation
4.2.4 Key Technologies for Multi-source Information Fusion System
4.3 Traffic Environment and Vehicle State Sensing Technology Based on Information Fusion
4.4 Spatial Synchronization of Multi-source Sensor Information
4.4.1 Establishing the Relationship of Multi-coordinate System Fusion
4.4.2 Improved Equation for Conversion Between the Coordinates of Image Coordinate System and the Camera’s Coordinate System
4.4.3 Spatial Synchronization Calibration Method for Sensors
4.4.4 Experimental Verification of the Spatial Synchronization Method
4.5 Detection Object Fusion Decision Based on Multi-source Information
4.6 Establishing the Set of Vehicle Parameter Features Based on Information Fusion
4.7 Extraction and Processing of Vehicle Feature Data Based on Information Fusion
4.7.1 Monocular Vision Ranging
4.7.2 DCF Correction for In-Lane Probability
4.7.3 Predictive Tracking Using Kalman Filtering
References
5 Cooperative Control Technologies for i-EFV
5.1 Integrated and Coordinated Vehicle Chassis Control System
5.2 Coorperative Control Methods for Vehicle Chassis System Based on Top-Level Design
5.3 i-EFV Coordinated Control System Based on Top-Level Design
5.3.1 Architecture of i-EFV’s Hierarchical Coordinated Control System
5.3.2 Integrated Control of i-EFV Multi-objective and Multi-system Synergy
5.4 Typical Applications of i-EFV Coordinated Control Technology
5.4.1 Intelligent-Assisted Driving Coordinated Control Technology for HEVs
5.4.2 Hybrid Multi-system Energy Management and Coordinated Control Technology
5.4.3 Technologies for the Coordinated Control of Longitudinal-Lateral-Vertical Tyre Force for Distributed Electric-Drive Vehicle
References
6 Implementation of Intelligent Electric Vehicle Energy-Efficiency Control Based on Structure Sharing
6.1 Overall Architecture of Intelligent Energy-Efficiency Control System
6.1.1 Principles of Control System Design
6.1.2 Control System Architecture
6.2 Scenario Analysis-Based Energy-Efficiency Mode Decision and Switching
6.2.1 Driving Scenario Classification Based on Safety Situation Assessment
6.2.2 Scenario Change-Based Mode Switching Control
6.2.3 Driving Intentions-Based System Turn-On Control
6.3 Optimal Control of Drive Motor Torque in Different Modes
6.3.1 Rules for Drive Motor Torque Optimization in Different Modes
6.3.2 MPC-Based Longitudinal Car-Following Motion Control Algorithm
6.3.3 Extraction and Fitting of the Motor Torque Optimization Coefficient Table
6.4 Simulation Analysis of EV Intelligent Energy-Efficiency Control
6.4.1 Simulation Platform Design
6.4.2 Simulation Plan Design
6.4.3 Simulation Analysis of Vehicle Energy-Efficiency Control Effects
6.5 Experimental Study of Energy-Efficiency Control of Intelligent Electric Vehicles Based on Structure Sharing
6.5.1 Design of Experiment Plan
6.5.2 Experimental Analysis of Energy-Efficiency Control of Vehicles in Congested Urban Road Conditions
6.5.3 Experimental Analysis of Energy-Saving Control of Vehicles in General Urban Road Conditions
6.5.4 Comparison of Experimental Results of Energy-Efficiency Control of Vehicles in Different Urban Road Conditions
References
7 Implementation of i-HEV ACC Based on Control Collaboration
7.1 Structure of the i-HEV ACC Control System
7.2 Technical Difficulties and Key Points of i-HEV ACC
7.3 Key Technologies of the i-HEV ACC System
7.3.1 Multi-objective Steady-State Optimization
7.3.2 Multi-system Dynamic Coordination
7.3.3 Estimation of Battery’s Equivalent Fuel Consumption Factor
7.4 Simulation Analysis of i-HEV ACC
7.4.1 The Forward Simulation Platform Structure Design
7.4.2 Forward Simulation Platform Model
7.4.3 Verification of Forward Simulation Platform
7.4.4 Simulation Contrast of Working Scenarios
7.4.5 Evaluation Indicators for Simulation and Contrast
7.4.6 Simulation Contrast Strategy and Contrast Method
7.4.7 Analysis of i-HEV ACC Versus IV ACC Simulation Contrast Results
7.4.8 Analysis of i-HEV ACC Versus HEV Simulation Contrast Results
7.4.9 Analysis of i-HEV ACC Versus Simple-Superposition HEV ACC Simulation Contrast Results
7.5 Experimental Study of i-HEV ACC
7.5.1 Experiment Platform Design of i-HEV
7.5.2 Developing the i-HEV Control System RCP
7.5.3 Designing the Hardware Platform of i-HEV
7.5.4 Experimental Verification Scheme for the Comprehensive Performance of i-HEV ACC
7.5.5 Contrast Experiment Schemes Based on i-HEV ACC Driving Cycles
7.5.6 Analysis of the Experiment Results in the Scenario of Sharp Acceleration/Deceleration of the Preceding Vehicle
7.5.7 Analysis of Driving Cycle Contrast Experiment Results
References
8 Implementation of Intelligent EV Charging/ Battery-Swapping Scheduling Based on Multi-source Information Fusion
8.1 Studies on the Charging/Battery-Swapping Schedule of EVs
8.1.1 Designing the Process of EV Charging/Battery-Swapping
8.1.2 Judgement of Charging/Battery-Swapping Demand and Driver’s Decision-Making
8.1.3 EV Charging Scheduling Strategy
8.1.4 EV Battery-Swapping Scheduling Strategy
8.2 Establishing the Simulation Platform for EV Charging/Battery-Swapping Scheduling
8.2.1 General Design of the Simulation Platform
8.2.2 Establishing the EV Model
8.2.3 Establishing the Charging/Battery-Swapping Station Model
8.2.4 Road Traffic Network Model and Power Grid Model
8.3 Simulation Verification of the EV Charging/Battery-Swapping Scheduling Strategy
8.3.1 Designing the Simulation Scheme
8.3.2 Analysis of the Simulation Result on the Traffic Side
8.3.3 Analysis of the Simulation Result on the Power Grid Side
References
9 Intelligent Travel Planning for Electric Vehicles Based on Multi-network Fusion and CVIS
9.1 Application Background
9.2 Overall Design of Travel Planning and Energy-Efficiency Control System for Connected Electric Vehicles
9.2.1 Systematic Architecture Design
9.2.2 Design of Travel Planning for EVs
9.2.3 Intelligent Energy-Efficiency Control of EVs
9.2.4 Intelligent Energy-Efficiency Control of EV Fleets
9.2.5 Technical Difficulties and Key Points
9.3 Multi-objective Travel Planning Method for Connected Electric Vehicles
9.3.1 Systematic Model of Travel Planning Method
9.3.2 Definition of Travel Objectives and Constraints
9.3.3 A Temperal Multi-objective Ant Colony Optimization Algorithm is Used to Solve Problems
9.3.4 Simulation Analysis of Travel Planning Algorithm
References