《混合動力履帶車輛機電複合傳動系統最佳化設計方法》是清華大學出版社2022年出版的書籍。
基本介紹
- 中文名:混合動力履帶車輛機電複合傳動系統最佳化設計方法
- 作者:秦兆博
- 出版社:清華大學出版社
- 定價:119
- ISBN:9787302600718
內容簡介,圖書目錄,
內容簡介
混合動力技術在逐漸發展並日臻成熟,而履帶車輛已經在建築工業、農業、航空航天和軍事等領域廣泛套用,發揮著舉足輕重的作用。針對混合動力車輛的傳動系統設計一直是系統供應商、整車廠、工程車輛行業、國家部委等多個層面的研究熱點。《混合動力履帶車輛機電複合傳動系統最佳化設計方法》是一部闡述混合動力履帶車輛傳統系統設計方法的研究型論文。該書針對動力學建模、能量管理策略、參數最佳化等課題,從混合動力履帶車輛的凳阿厚新型拓撲構型設計、性能最佳化設計、優選方法等角度介紹了該領域核心問題,形成了系統設計解決方案。 本書可作為混合動力汽車領域研究人員的參考讀物。
圖書目錄
第1章引言
1.1概述
1.2混合動力履帶車輛傳動系統的研究現狀
1.3混合動力車輛傳動系統最佳化設計研究現狀
1.3.1拓撲構型最佳化
1.3.2能量管理策略
1.3.3參數匹配最佳化
1.4本書研究內容
第2章混合動力履帶車輛機電複合傳鞏厚備臭動系統構型總體設計
2.1多模式機電複合傳動系統構型
2.2傳動系統構型的最佳化設計方法
2.2.1多模式機電複合傳動系統拓撲構型最佳化
2.2.2近優能量管理策略
2.2.3融合參數匹配的疊代最佳化
2.3技術難點與重點
第3章混合動力履帶車輛的建模
3.1混合動力履帶車輛動力學模型
3.1.1整車動力學模型
3.1.2動力總成模型
3.2行星齒輪傳動系統的自動建模方法
3.2.1構型特徵矩陣D的生成
3.2.2變換矩陣N的建立
3.2.3特徵矩陣A的推導
3.2.4系統動力學特徵矩陣A*的提取
3.3混合動力履帶車輛運動學模型與員達戰頸滑動參數估計
3.3.1基於瞬時轉向中心的履帶車輛運動學模型
3.3.2基於前向軌跡預測補償的雙層自適應無跡卡爾曼
濾波滑動參數估計
3.4本章小結
第4章多模式機電複合傳動系統的構型分析與篩選
4.1多模式機電複合傳動系統的拓撲構型分析
4.1.1無離合器的傳動系統工作模式分類
4.1.2添加離合器的多模式傳動系統拓撲嘗兆艱構型
4.2多模式機電複合傳動系統的特性篩選
4.2.1基於作業需求的構型篩選
4.2.2基驗跨邀於基礎功能的構型篩選
4.2.3基於綜合性能的構型篩選
4.3本章小結
第5章混合動力履帶車輛的能量管理策略
5.1基於確定性動態規劃的全局能量管理策略
5.1.1動態規劃最優控制問題的建立
5.1.2動態規劃的最佳化結果
5.2基於功率流效率評價的近優能量管理策略
5.2.1近優能量管理策略的基本原理
5.2.2工作區域離散化
5.2.3不同模式的功率流效率計算
5.2.4基於SOC分析的功率流效率修正
5.2.5模式切換策略
5.3基於BP神經網路最佳化的實時能量管理策略
5.4本章小結
第6章機電複合傳動系統構型的最優設計
6.1傳動系統構型最優設計的總體方案
6.2融合參數匹配的遞立灶鍵進疊代最佳化方法
6.2.1基於敏感度分析的參數範圍確定
6.2.2基於NSGAⅡ的多目標最佳化算法
6.2.3基於均勻臘去設計的混沌增強加速粒子群最佳化算法
6.2.4基於蒙特卡羅分析的啟發式算法對比
6.3本章小結
第7章機電複合傳動系統構型最優設計的驗證
7.1傳動系統拓撲構型設計的驗證
7.1.1基於雙排行星傳動的多模式拓撲構型最佳化驗證
7.1.2基於三排行星傳動的多模式拓撲構型最佳化驗證
7.2融合參數匹配的遞進疊代最佳化方法驗證
7.2.1基於NSGAⅡ的多目標最佳化方法驗證
7.2.2基於UDCAPSO的最佳化方法驗證
7.2.3最優傳動系統構型方案的綜合性能仿真驗證
7.3傳動系統構型的硬體在環試驗驗證
7.3.1基於Simulink的整車仿真模型建立
7.3.2硬體在環試驗系統搭建
7.3.3試驗結果分析
7.4本章小結
第8章結論
參考文獻
發表的學術論文
致謝
Contents
Contents
Chapter 1Preface1
1.1Introduction1
1.2Research Status of Hybrid Tracked Vehicle Powertrain3
1.3Optimization Research Status of Hybrid Trakced Vehicle
Powertrain10
1.3.1Topology Optimization12
1.3.2Energy Management Strategy14
1.3.3Parameter Optimization19
1.4Research Contents21
Chapter 2Overall Configuration Design of Hybrid Tracked
Vehicles ElectroMechanical Powertrain25
2.1Configuration of the Novel MultiMode ElectroMechanical
Powertrain25
2.2Configuration Design Optimization28
2.2.1Topology Optimization of MultiMode ElectroMechanical
Powertrain30
2.2.2NearOptimal Energy Management Strategy31
2.2.3SizeIntegrated Iterative Optimization31
2.3Technical Difficulties34
Chapter 3Modelling of the Hybrid Tracked Vehicle36
3.1Dynamics Model of the Hybrid Tracked Vehicle36
3.1.1Vehicle Dynamics Model38
3.1.2Powertrain Model42
3.2Automated Modelling of Planetary Gear Powertrain45
3.2.1Generation of Configuration Characteristic Matrix D45
3.2.2Generation of Transformation Matrix N48
3.2.3Derivation of Characteristics Matrix A50
3.2.4Extraction of System Dynamics Characteristic
Matrix A*51
3.3Kinematics Model of the Hybrid Tracked Vehicle and Sliding
Parameter Estimation54
3.3.1Kinematics Model of the Hybrid Tracked Vehicle
Based on Instantaneous Steering Center54
3.3.2TwoLayer Adaptive Unscented Kalman Filtersliding
Parameter Estimation Based on Forward Trajectory
Prediction Conpensation56
3.4Chapter Summary69
Chapter 4Configuration Analysis and Screening of MultiMode
ElectroMechanical Powertrain71
4.1Configuration Analysis of MultiMode ElectroMechanical
Powertrain71
4.1.1Working Mode Classification of Powertrain Without
Clutches71
4.1.2Topology Configuration of Powertrain with Clutches79
4.2Characteristics Screening of MultiMode ElectroMechanical
Powertrain82
4.2.1Configuration Screening Based on Working
Requirements82
4.2.2Configuration Screening Based on Basic Functions89
4.2.3Configuration Screening Based on Overall
Performance90
4.3Chapter Summary98
Chapter 5Energy Management Strategy of Hybrid Tracked Vehicles100
5.1Energy Management Strategy Based on Deterministic
Dynamic Programming100
5.1.1Optimal Control Problem Based on Dynamic
Programming101
5.1.2Optimization Result of Dynamic Programming103
5.2NearOptimal EfficiencyBased Evaluation RealTime Control
Strategy108
5.2.1Basic Principle of NearOptimal Energy Management
Strategy109
5.2.2Working Zone Discretization111
5.2.3Power Efficiency Calculation of Different Modes113
5.2.4Power Effeicincy Revision Based on SOC Analysis116
5.2.5Mode Shift Strategy126
5.3RealTime Energy Management Strategy Based on BP Neural
Network Optimization129
5.4Chapter Summary137
Chapter 6Optimal Design of ElectroMechanical Powertrain139
6.1Overall Scheme of Optimal Powertrain Configuration
Design139
6.2SizeIntegrated Iterative Optimization Method141
6.2.1Parameter Range Determination Based on Sensitivity
Analysis144
6.2.2MultiObjective Optimization Algorithm Based on
NSGAⅡ146
6.2.3ChaosEnhanced Accelerated PSO Algorithm Based
on Uniform Design146
6.2.4Heuristic Algorithm Comparison Based on Monte
Carlo Analysis153
6.3Chapter Summary154
Chapter 7Verification of Optimal ElectroMechanical Configuration
Design155
7.1Verification of Topology Configuration Design155
7.1.1MultiMode Topology Optimization Verification
Based on Two Planetary Gears155
7.1.2MultiMode Topology Optimization Verification
Based on Three Planetary Gears165
7.2SizeIntegrated Iterative Optimization Method Verification176
7.2.1MultiObjective Optimization Algorithm Verification
Based on NSGAⅡ176
7.2.2Optimization Algorithm Verification Based on
UDCAPSO179
7.2.3Overall Performance Simulation Verification of the
Optimal Design181
7.3HardwareinLoop Experiment of the Powertrain
Configuration187
7.3.1Vehicle Simulation Model Based on Simulink187
7.3.2Establishment of HardwareinLoop Model189
7.3.3Experiment Result Analysis192
7.4Chapter Summary210
Chapter 8Conclusion211
References214
Publications226
Acknowledgements228
5.1.2動態規劃的最佳化結果
5.2基於功率流效率評價的近優能量管理策略
5.2.1近優能量管理策略的基本原理
5.2.2工作區域離散化
5.2.3不同模式的功率流效率計算
5.2.4基於SOC分析的功率流效率修正
5.2.5模式切換策略
5.3基於BP神經網路最佳化的實時能量管理策略
5.4本章小結
第6章機電複合傳動系統構型的最優設計
6.1傳動系統構型最優設計的總體方案
6.2融合參數匹配的遞進疊代最佳化方法
6.2.1基於敏感度分析的參數範圍確定
6.2.2基於NSGAⅡ的多目標最佳化算法
6.2.3基於均勻設計的混沌增強加速粒子群最佳化算法
6.2.4基於蒙特卡羅分析的啟發式算法對比
6.3本章小結
第7章機電複合傳動系統構型最優設計的驗證
7.1傳動系統拓撲構型設計的驗證
7.1.1基於雙排行星傳動的多模式拓撲構型最佳化驗證
7.1.2基於三排行星傳動的多模式拓撲構型最佳化驗證
7.2融合參數匹配的遞進疊代最佳化方法驗證
7.2.1基於NSGAⅡ的多目標最佳化方法驗證
7.2.2基於UDCAPSO的最佳化方法驗證
7.2.3最優傳動系統構型方案的綜合性能仿真驗證
7.3傳動系統構型的硬體在環試驗驗證
7.3.1基於Simulink的整車仿真模型建立
7.3.2硬體在環試驗系統搭建
7.3.3試驗結果分析
7.4本章小結
第8章結論
參考文獻
發表的學術論文
致謝
Contents
Contents
Chapter 1Preface1
1.1Introduction1
1.2Research Status of Hybrid Tracked Vehicle Powertrain3
1.3Optimization Research Status of Hybrid Trakced Vehicle
Powertrain10
1.3.1Topology Optimization12
1.3.2Energy Management Strategy14
1.3.3Parameter Optimization19
1.4Research Contents21
Chapter 2Overall Configuration Design of Hybrid Tracked
Vehicles ElectroMechanical Powertrain25
2.1Configuration of the Novel MultiMode ElectroMechanical
Powertrain25
2.2Configuration Design Optimization28
2.2.1Topology Optimization of MultiMode ElectroMechanical
Powertrain30
2.2.2NearOptimal Energy Management Strategy31
2.2.3SizeIntegrated Iterative Optimization31
2.3Technical Difficulties34
Chapter 3Modelling of the Hybrid Tracked Vehicle36
3.1Dynamics Model of the Hybrid Tracked Vehicle36
3.1.1Vehicle Dynamics Model38
3.1.2Powertrain Model42
3.2Automated Modelling of Planetary Gear Powertrain45
3.2.1Generation of Configuration Characteristic Matrix D45
3.2.2Generation of Transformation Matrix N48
3.2.3Derivation of Characteristics Matrix A50
3.2.4Extraction of System Dynamics Characteristic
Matrix A*51
3.3Kinematics Model of the Hybrid Tracked Vehicle and Sliding
Parameter Estimation54
3.3.1Kinematics Model of the Hybrid Tracked Vehicle
Based on Instantaneous Steering Center54
3.3.2TwoLayer Adaptive Unscented Kalman Filtersliding
Parameter Estimation Based on Forward Trajectory
Prediction Conpensation56
3.4Chapter Summary69
Chapter 4Configuration Analysis and Screening of MultiMode
ElectroMechanical Powertrain71
4.1Configuration Analysis of MultiMode ElectroMechanical
Powertrain71
4.1.1Working Mode Classification of Powertrain Without
Clutches71
4.1.2Topology Configuration of Powertrain with Clutches79
4.2Characteristics Screening of MultiMode ElectroMechanical
Powertrain82
4.2.1Configuration Screening Based on Working
Requirements82
4.2.2Configuration Screening Based on Basic Functions89
4.2.3Configuration Screening Based on Overall
Performance90
4.3Chapter Summary98
Chapter 5Energy Management Strategy of Hybrid Tracked Vehicles100
5.1Energy Management Strategy Based on Deterministic
Dynamic Programming100
5.1.1Optimal Control Problem Based on Dynamic
Programming101
5.1.2Optimization Result of Dynamic Programming103
5.2NearOptimal EfficiencyBased Evaluation RealTime Control
Strategy108
5.2.1Basic Principle of NearOptimal Energy Management
Strategy109
5.2.2Working Zone Discretization111
5.2.3Power Efficiency Calculation of Different Modes113
5.2.4Power Effeicincy Revision Based on SOC Analysis116
5.2.5Mode Shift Strategy126
5.3RealTime Energy Management Strategy Based on BP Neural
Network Optimization129
5.4Chapter Summary137
Chapter 6Optimal Design of ElectroMechanical Powertrain139
6.1Overall Scheme of Optimal Powertrain Configuration
Design139
6.2SizeIntegrated Iterative Optimization Method141
6.2.1Parameter Range Determination Based on Sensitivity
Analysis144
6.2.2MultiObjective Optimization Algorithm Based on
NSGAⅡ146
6.2.3ChaosEnhanced Accelerated PSO Algorithm Based
on Uniform Design146
6.2.4Heuristic Algorithm Comparison Based on Monte
Carlo Analysis153
6.3Chapter Summary154
Chapter 7Verification of Optimal ElectroMechanical Configuration
Design155
7.1Verification of Topology Configuration Design155
7.1.1MultiMode Topology Optimization Verification
Based on Two Planetary Gears155
7.1.2MultiMode Topology Optimization Verification
Based on Three Planetary Gears165
7.2SizeIntegrated Iterative Optimization Method Verification176
7.2.1MultiObjective Optimization Algorithm Verification
Based on NSGAⅡ176
7.2.2Optimization Algorithm Verification Based on
UDCAPSO179
7.2.3Overall Performance Simulation Verification of the
Optimal Design181
7.3HardwareinLoop Experiment of the Powertrain
Configuration187
7.3.1Vehicle Simulation Model Based on Simulink187
7.3.2Establishment of HardwareinLoop Model189
7.3.3Experiment Result Analysis192
7.4Chapter Summary210
Chapter 8Conclusion211
References214
Publications226
Acknowledgements228