用于拍瓦級脈沖驅動源的整體徑向傳輸線的研究

第1章引言
1.1傳輸線簡介
1.2傳輸線按結構分類
1.2.1同軸傳輸線
1.2.2平行板傳輸線
1.3傳輸線按沿線特性阻抗分類
1.4非均勻傳輸線的應用
1.5高功率脈沖技術領域中的傳輸線
1.6整體徑向傳輸線的研究方法和研究現狀
1.6.1解析分析研究
1.6.2電路仿真研究
1.6.3電磁場仿真研究
1.6.4實驗研究
1.7主要工作
第2章非均勻傳輸線傳輸特性的電路仿真研究
2.1模型建立
2.2分析方法
2.3仿真結果
2.4對仿真結果的進一步分析
2.5本章小結
第3章非均勻傳輸線傳輸特性的解析分析研究
3.1解析求解
3.1.1模型建立
3.1.2輸出電壓的解析求解
3.1.3解析求解與電路仿真的結果對比
3.2理論分析
3.2.1輸出電壓的影響因素
3.2.2首達波特性
3.2.3脈沖壓縮特性
3.2.4高通特性
3.2.5峰值特性
3.2.6平頂下降特性
3.3圖形用戶界面
3.4本章小結
第4章非均勻傳輸線傳輸特性的三維電磁場仿真研究
4.1同軸非均勻傳輸線的三維電磁場仿真研究
4.1.1模型建立
4.1.2結果與討論
4.2整體徑向非均勻傳輸線的三維電磁場仿真研究
4.2.1模型建立
4.2.2結果與討論
4.3本章小結
第5章小型整體徑向傳輸線的實驗研究
5.1小型整體徑向傳輸線的實驗裝置設計
5.1.1單路高電壓納秒矩形波脈沖發(fā)生器
5.1.2電阻分壓器
5.1.321路分路器
5.1.4整體徑向傳輸線及其負載
5.2實驗結果與討論
5.2.1正常情形
5.2.2不同數目輸入端口情形
5.2.3故障情形
5.3本章小結第6章結論參考文獻在學期間發(fā)表的學術論文致謝Contents用于拍瓦級脈沖驅動源的整體徑向傳輸線的研究
Contents
Chapter 1Introduction
1.1Background
1.2Review of Evaluation Methods of Intelligent Driving 
Systems
1.2.1Brief Introduction of Relevant Evaluation 
Methods
1.2.2Classification Analysis and Comparison
1.3Research Status of Intelligent Driving System Identification
1.3.1Key Parameters Estimation
1.3.2Control Logic Identification
1.4Research Status of Evaluation Index
1.4.1Evaluation Index about Intelligence
1.4.2Evaluation Index about Safety Benefit
1.5Research Topics in This Book
Chapter 2Research Framework of Safety Benefit Evaluation 
Methodology
2.1Design of Safety Benefit Evaluation Process
2.1.1Basic Data Source
2.1.2Monte Carlo Simulation
2.1.3Safety Benefit Calculation
2.2Involved Key Techniques
Chapter 3Intelligent Driving System Identification Method Based 
on Vehicle Operation Data
3.1The Goal of Intelligent Driving System Identification
3.2Key Parameters Estimation Based on Frequency Response 
Characteristics
3.2.1Tire Stiffness Estimation Based on Frequency 
Response of the Steering System
3.2.2Time Delay Coefficient Estimation Based on 
Frequency Response of the Driving System
3.2.3Vehicle Mass Estimation Based on Vehicle 
Longitudinal Frequency Response Characteristics
3.2.4Summary of This Section
3.3Control Logic Identification Based on Machine Learning
3.3.1Intrinsic Nature of Control Logic Identification
3.3.2Control Logic Identification Based on Neural 
Network
3.4Summary of This Chapter
Chapter 4Occupant Injury Risk Estimation Based on Accident Data
4.1Research Scheme of Occupant Injury Risk Estimation
4.2Feasibility Verification of Vehicle Deformation Depth as 
Occupant Injury Evaluation Index
4.2.1Verification Based on GIDAS Data
4.2.2Verification Based on NASSCDS Data
4.3Occupant Injury Risk Estimation Based on Vehicle 
Deformation Depth
4.3.1Injury Risk Model Based on Vehicle Deformation 
Depth
4.3.2Vehicle Deformation Depth Estimation Based 
on Crash Energy
4.3.3Occupant Injury Risk Calculation Using Crash 
Simulation Software
4.4Summary of This Chapter
Chapter 5Safety Benefit Evaluation Methodology of Intelligent 
Driving Systems Based on Multisource Data Mining
5.1Overall Requirements for Safety Benefit Evaluation Methods
5.2Framework of Safety Benefit Evaluation Method Based 
on MultiSource Data Mining
5.3Key Techniques of Building Traffic Model
5.3.1Random Leading Vehicle Model
5.3.2Random Following Vehicle Model
5.3.3Subject Vehicle Model
5.4Key Techniques of Simulation Process
5.4.1CarSimSimulink Simulation Module
5.4.2PC CrashRateEFFECT Simulation Module
5.5Key Techniques of Injury Risk Estimation Process
5.5.1Calculation Method of Average Occupant Risk Per 
Mileage
5.5.2Deformation Length Estimation Based on Vehicle 
Collision Position Coordinates
5.6Summary of This Chapter
Chapter 6Verification and Application of the Proposed Methods
6.1Verification of Intelligent Driving System Identification 
Methods
6.1.1Verification of Key Parameters Estimation Methods
6.1.2Verification of the Control Logic Identification 
Method
6.2Verification of the Occupant Injury Risk Estimation Method
6.2.1Regression Relation Between Injury Risk and ΔV
6.2.2Comparison of the Occupant Injury Risk 
Estimation Methods with Deformation Depth 
and ΔV
6.3Application of the Proposed Safety Benefit Evaluation 
Methodology
6.3.1Safety Benefit Evaluation Using Accident 
Reconstruction Database
6.3.2Safety Benefit Evaluation Based on Random 
Traffic Scenarios
6.4Summary of This Chapter
Chapter 7Conclusions