第1章引言 1.1傳輸線(xiàn)簡(jiǎn)介 1.2傳輸線(xiàn)按結(jié)構(gòu)分類(lèi) 1.2.1同軸傳輸線(xiàn) 1.2.2平行板傳輸線(xiàn) 1.3傳輸線(xiàn)按沿線(xiàn)特性阻抗分類(lèi) 1.4非均勻傳輸線(xiàn)的應(yīng)用 1.5高功率脈沖技術(shù)領(lǐng)域中的傳輸線(xiàn) 1.6整體徑向傳輸線(xiàn)的研究方法和研究現(xiàn)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(chǎng)仿真研究 1.6.4實(shí)驗(yàn)研究 1.7主要工作 第2章非均勻傳輸線(xiàn)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(jié)果 2.4對(duì)仿真結(jié)果的進(jìn)一步分析 2.5本章小結(jié) 第3章非均勻傳輸線(xiàn)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(jié)果對(duì)比 3.2理論分析 3.2.1輸出電壓的影響因素 3.2.2首達(dá)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(hù)界面 3.4本章小結(jié) 第4章非均勻傳輸線(xiàn)傳輸特性的三維電磁場(chǎng)仿真研究 4.1同軸非均勻傳輸線(xiàn)的三維電磁場(chǎng)仿真研究 4.1.1模型建立 4.1.2結(jié)果與討論 4.2整體徑向非均勻傳輸線(xiàn)的三維電磁場(chǎng)仿真研究 4.2.1模型建立 4.2.2結(jié)果與討論 4.3本章小結(jié) 第5章小型整體徑向傳輸線(xiàn)的實(shí)驗(yàn)研究 5.1小型整體徑向傳輸線(xiàn)的實(shí)驗(yàn)裝置設(shè)計(jì) 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(xiàn)及其負(fù)載 5.2實(shí)驗(yàn)結(jié)果與討論 5.2.1正常情形 5.2.2不同數(shù)目輸入端口情形 5.2.3故障情形 5.3本章小結(jié)第6章結(jié)論參考文獻(xiàn)在學(xué)期間發(fā)表的學(xué)術(shù)論文致謝Contents用于拍瓦級(jí)脈沖驅(qū)動(dòng)源的整體徑向傳輸線(xiàn)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 NASSCDS 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 MultiSource 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 5.4.1CarSimSimulink Simulation Module 5.4.2PC CrashRateEFFECT 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