秦兆博,湖南大学副研究员,先后在清华大学获得学士(2013)、博士(2018)学位,获得清华大学和北京市优秀博士毕业生称号、清华大学优秀博士论文。2018年至今在湖南大学机械与运载工程学院任教。研究方向覆盖新能源汽车、车辆动力学与控制、智能驾驶、自动驾驶系统等。近五年来,主持或作为主要完成人参与10余项横纵向科研项目;发表期刊与会议论文20篇(第一/通讯作者10余篇,Google学术引用80余次);获得中国发明专利10项;主要学术兼职包括Vehicle System Dynamics、Applied Energy、IEEE Access等学术组织的评审专家。
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