基于双离合器的插电式MPV混合动力系统匹配技术研究
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摘要
汽车工业对原油的消耗及废气排放对环境的污染已成为制约现代工业发展的重要障碍。降低能源消耗,减少汽车废气排放,对汽车节能与减排技术进行研究,这些工作具有重要的战略现实意义。通过对汽车工业环保与节能技术的大量研究,结果显示,混合动力汽车(HEV)是目前最具有商品化、产业化前景的量产环保车型之一,得到了大量的关注。而插电式混合动力汽车(PHEV),通过采用大容量电池来提升混合动力汽车(HEV)的性能,进一步提升了人们的关注度。本文中,重点对某企业采用双离合器的插电式混合动力MPV进行探讨。
全文主要分7个部分：
1.基于混合动力汽车的节能机理、各零部件的节能贡献率和节能潜力,分析混合动力汽车的节能途径。研究与分析国内外混合动力汽车的研发趋势和政府扶持政策,确定混合动力汽车的研发方向。另外对目前混合动力的开发流程、开发工具、优化方法和试验设备进行讨论。
2.针对对不同类型、不同结构形式的混合动力汽车各自优缺点,分析并最终确定采用双离合器的插电式混合动力驱动系统方案。该方案中,电机位于两个离合器之间,解决了混合动力MPV跛行回家、安全性、换挡性能和制动能量回收等问题。
3.对混合动力汽车关键零部件对比分析,结合关键部件的发展趋势及企业目前技术水平,确定混合动力汽车的零部件类型。另外根据并联式混合动力汽车混合度的设计方法合理确定整车的混合度。
4.基于汽车关键部件的试验数据,采用理论建模与试验建模相结合的建模方式,在Matlab/Simulink环境下建立了双离合器的插电式混合动力MPV关键部件模型,它为MPV控制策略的研发提供必要的仿真平台。
5.插电式双离合器混合动力MPV的控制策略对整车的燃油经济性有巨大的影响,所以根据道路状况及电池状态对燃油经济性的影响,把发动机的工作区域划分成三个部分。本文重点探讨了整车动力驱动系统基本控制逻辑,如发动机的ON/OFF控制逻辑,纯电动模式与混合动力模式之间的模式切换及扭矩分配,另外变速器升降挡逻辑,再生制动模式与机械制动模式的切换及扭矩分配,以及电机和发动机的冷却系统管理策略。通过对插电式混合动力MPV的能量流动进行规划,合理分配发动机的扭矩,控制并使其工作在最佳效率区,为整车控制器控制策略参数的优化设计打下坚实的基础。
6.对混合动力汽车的控制策略参数进行全局优化设计。传统优化方法与专家经验在实际应用中面临开发成本高,优化时间长,局部最优等问题,所以本文采用试验设计——近似模型——优化设计的方法对混合动力汽车的控制策略参数进行优化。首先采用试验设计(DOE)对控制策略中10个试验因子进行敏感度分析,10个试验因子分别为A(起机SOC限值：SOC值低于该值时,发动机将起动工作),B(停机SOC限值：当SOC值高于该值时,发动机将起动工作),C(发动机起动保持时间限值：当发动机工作时,发动机持续工作的最短时间),D(发动机停机保持时间限值：发动机停机时,发动机保持停机状态的最短时间),E(发动机预起动时间限值：在发动机起动之前,车轮需求扭矩必须大于某一值的时间限值),F(发动机预停机时间限值：在发动机停机之前,车轮需求扭矩必须小于某一值的时间限值),G(发动机预起动最小功率限值：使发动机起动的最小功率需求),H(发动机预停机最大功率限值：使发动机停机时的最大功率需求),I(允许能量回收动力电池荷电状态限值：当SOC低于该值时,允许动力电池进行能量回收工作),J(禁止能量回收动力电池荷电状态限值：当SOC高于该值时,禁止动力电池进行能量回收工作)。选取混合动力整车的燃油经济性作为试验指标,试验因子的水平数采用101水平。通过对采用优化拉丁超立方抽样方法对试验因子进行主效应与交互效应分析,找到影响试验指标的主要因素。
通过对近似模型构造方法的分析,采用Kriging建模方法,根据DOE试验中输入与输出的关系建立近似模型,避免高强度仿真计算,减少迭代时间,预估输入输出参数之间的响应关系。随意选取任意5个试验点进行对比,结果显示仿真试验得出的整车百公里油耗结果与近似模型得出的结果误差一般低于5%,检验了近似模型直接代替仿真试验是可行的。
基于近似模型,本文利用利用全局优化算法(多岛遗传算法)对试验因子进行全局寻优,证明了采用试验设计——近似模型——优化设计的可行性和有效性。
7.根据全局优化算法的优化结果进行仿真分析。其中分析用发动机,离合器、电机和电池等参数均为台架试验值,另将分析用10×NEDC循环工况分成加速、减速和稳态三种工作状态,分别分析了不同状态下发动机、电动机的扭矩、转速、功率和效率分布以及动力电池的电流、电压、功率和效率分布。另外计算了插电式混合动力MPV在50×ECE,100×ECE,20×EUDC,10×NEDC,1×FTP,20×Japan1015,10×UDDS和10×US06等循环工况下整车的燃油经济性。最后对功能样车的纯电动和制动能量回收等基本功能进行了实车检验。
最后对全文进行总结,指出插电式混合动力MPV开发中可供参考的工程应用方法及思路,同时对有待深入研究的不足进行描述。
Current energy and environmental issues as a constraint to the development of modern industry are the important factors, and the automobile industry is the major factor of the environmental pollution and energy consumption. Decreasing energy consumption, reducing vehicle exhaust pollution on our environment, energy-saving and emission reduction of motor vehicle research, such works have important strategic significance. Through a large number of different countries'studies of the national environmental protection and energy saving technology to the automotive industry, the results show that hybrid electric vehicle (HEV) is the most industrial, commercial prospects for mass production of environmentally friendly cars, and which has gotten a lot of attention. The plug-in hybrid electric vehicle (PHEV), using of high-capacity battery to improve hybrid electric vehicle's (HEV) performance, further enhance the degree of people's attention. In this dissertation, a company's plug-in hybrid MPV is discussed.
This dissertation is divided into seven parts.
1. Based on the mechanism of energy saving of the hybrid electric vehicle, the contribution and potential of the energy-saving of the crucial parts, the writer analyses the energy-saving way of the HEV. Through research and analyze domestic and international research and development trends and government support policies of the hybrid electric vehicles, the direction of the development of hybrid vehicles is determined. The current hybrid development process, development tools, optimization methods and test equipment are also discussed in this dissertation.
2. The advantages and disadvantages of the hybrid electric vehicles with different types and different structural forms are analyzed, ultimately the power train of the plug-in hybrid electric drive system with two clutches is chosen as the finally power train. In this power train configuration, the electric motor is located between the two clutches, and this configuration solves the problems of the vehicle's function which includes hybrid vehicle limp home, security, shift performance and brake energy recovery and other issues.
3. Comparing and analyzing the critical components of the Hybrid electric vehicle, the type of vehicle's components are chosen combined with the development trend of critical components and current technology. The design method of DOH (degree of hybridization) is introduced and an idea DOH is chosen base on the crucial part's parameters.
4. Based on bench test data of crucial components, in the Matlab/Simulink environment, the Pre-transmission parallel configuration with two clutches (before and after electric machine) model is established using the model building method which combins theoretical analysis and bench test data, which provides a necessary simulation platform for the research and development of the control strategy.
5. Control strategies of plug-in hybrid electric MPV with two clutches (before and after electric machine) has a huge impact on vehicle's fuel economy, so this strategy operates the engine in one of three regions depending on the combined power requirement needed by the road and the battery. This dissertation mainly discusses the basic control logic of the propelling systems, such as the engine ON/OFF control logic, the modes switching and torque distribution between pure electric mode and hybrid mode, down and up logic of transmission, the modes switching and torque distribution between regenerative braking mode and the mechanical braking torque, and the strategy of cooling systems of electric motor and engine. Through planning the energy flow of the plug-in hybrid electric MPV, rationally distributing the engine torque and controlling the engine work in the high efficiency area, all these works found a solid foundation for parameters optimization of vehicle control strategy.
6. The parameters of control strategy of the plug-in hybrid electric MPV are optimized under the global optimization algorithm. Traditional optimization methods and expertise are confronted with the problem such as high cost, long time and local optimization, so Design Of Experiment (DOE)—Approximate Model—Optimization Algorithm is chosen as the optimization method in this dissertation. First, sensitivity analysis of ten crucial variables of the control strategy is done using DOE method, The Design Variables used in the control strategy are A (SOC below which the engine is turned on), B (SOC above which the engine is turned off), C (Once on, Minimum time for the engine to stay on), D (Once off, Minimum time for the engine to stay off), E (The wheel torque must be above wh_trq_above_turn_on for this amount of time before the engine turns on), F (The wheel torque must be below wh_trq_below_turn off for this amount of time before the engine turns off), G (min power for the engine to turn on), H (max power for the engine to turn off), I (Charging is forbidden if the SOC is above this value), and J (Charging is allowed if the SOC is below this value). The hybrid electric vehicle's fuel economy is selected as the test target, and to explore the design space and identify significant design variables, a101-level DOE study is carried out using Optimal Latin Hypercube method, and the main factors are gotten from main effect and interactive effect calculations.
Then, through analyzing the construction methods of the approximate model, one Approximate Model is established base on the input and output relationship using Kriging model method, which avoids the high strength simulation, reduce the iterative time. Five points are used to analysis the tolerance between PSAT simulation and Approximate Model, the results show that the tolerances between the PSAT simulation test and the Approximate Model simulation are less than5%, it is clearly seen that the Approximate Model can substitute the direct simulation test commendably.
Finally, global optimization algorithm (multi-island genetic algorithm) is used to find the optimum using the Approximate Model in this dissertation, it is proved that Design Of Experiment (DOE)—Approximate Model—Optimization Algorithm is the feasible and effective optimum design method.
7. Based on global optimization results, the simulations of the plug-in hybrid electric MPV are carried out under the drive cycle50×ECE,100×ECE,20×EUDC,10×NEDC,1×FTP,20×Japan1015,10×UDDS and10×US06. Finally, the MPV's basic functions such as pure electric propelling and regenerative braking are validated.
The simulations of the plug-in hybrid electric MPV are carried out based on optimization results. The parameters of the engine, transmission, motor and battery used in the simulations are bench test values. The10×NEDC driving cycle is divided into three vehicle modes which are celeration, deceleration and steady state. Percentage of the torque, speed, power and efficiency of the engine and motor,and the Percentage of battery current, voltage, power and efficiency are analyzed under the three vehicle modes. Fuel economy of the plug-in hybrid MPV are also calculated under the50×ECE,100×ECE,20×EUDC,10×NEDC,1×FTP,20×Japan1015,10x UDDS and10x US06drive cycle. Finally, the real MPV's basic functions such as pure electric propelling and regenerative braking are validated.
Summary of this thesis points out the engineering methods and ideas which can be used for reference in plug-in hybrid electric MPV design, and the shortages of this thesis needing for further study are also described.
全文主要分7个部分：
1.基于混合动力汽车的节能机理、各零部件的节能贡献率和节能潜力,分析混合动力汽车的节能途径。研究与分析国内外混合动力汽车的研发趋势和政府扶持政策,确定混合动力汽车的研发方向。另外对目前混合动力的开发流程、开发工具、优化方法和试验设备进行讨论。
2.针对对不同类型、不同结构形式的混合动力汽车各自优缺点,分析并最终确定采用双离合器的插电式混合动力驱动系统方案。该方案中,电机位于两个离合器之间,解决了混合动力MPV跛行回家、安全性、换挡性能和制动能量回收等问题。
3.对混合动力汽车关键零部件对比分析,结合关键部件的发展趋势及企业目前技术水平,确定混合动力汽车的零部件类型。另外根据并联式混合动力汽车混合度的设计方法合理确定整车的混合度。
4.基于汽车关键部件的试验数据,采用理论建模与试验建模相结合的建模方式,在Matlab/Simulink环境下建立了双离合器的插电式混合动力MPV关键部件模型,它为MPV控制策略的研发提供必要的仿真平台。
5.插电式双离合器混合动力MPV的控制策略对整车的燃油经济性有巨大的影响,所以根据道路状况及电池状态对燃油经济性的影响,把发动机的工作区域划分成三个部分。本文重点探讨了整车动力驱动系统基本控制逻辑,如发动机的ON/OFF控制逻辑,纯电动模式与混合动力模式之间的模式切换及扭矩分配,另外变速器升降挡逻辑,再生制动模式与机械制动模式的切换及扭矩分配,以及电机和发动机的冷却系统管理策略。通过对插电式混合动力MPV的能量流动进行规划,合理分配发动机的扭矩,控制并使其工作在最佳效率区,为整车控制器控制策略参数的优化设计打下坚实的基础。
6.对混合动力汽车的控制策略参数进行全局优化设计。传统优化方法与专家经验在实际应用中面临开发成本高,优化时间长,局部最优等问题,所以本文采用试验设计——近似模型——优化设计的方法对混合动力汽车的控制策略参数进行优化。首先采用试验设计(DOE)对控制策略中10个试验因子进行敏感度分析,10个试验因子分别为A(起机SOC限值：SOC值低于该值时,发动机将起动工作),B(停机SOC限值：当SOC值高于该值时,发动机将起动工作),C(发动机起动保持时间限值：当发动机工作时,发动机持续工作的最短时间),D(发动机停机保持时间限值：发动机停机时,发动机保持停机状态的最短时间),E(发动机预起动时间限值：在发动机起动之前,车轮需求扭矩必须大于某一值的时间限值),F(发动机预停机时间限值：在发动机停机之前,车轮需求扭矩必须小于某一值的时间限值),G(发动机预起动最小功率限值：使发动机起动的最小功率需求),H(发动机预停机最大功率限值：使发动机停机时的最大功率需求),I(允许能量回收动力电池荷电状态限值：当SOC低于该值时,允许动力电池进行能量回收工作),J(禁止能量回收动力电池荷电状态限值：当SOC高于该值时,禁止动力电池进行能量回收工作)。选取混合动力整车的燃油经济性作为试验指标,试验因子的水平数采用101水平。通过对采用优化拉丁超立方抽样方法对试验因子进行主效应与交互效应分析,找到影响试验指标的主要因素。
通过对近似模型构造方法的分析,采用Kriging建模方法,根据DOE试验中输入与输出的关系建立近似模型,避免高强度仿真计算,减少迭代时间,预估输入输出参数之间的响应关系。随意选取任意5个试验点进行对比,结果显示仿真试验得出的整车百公里油耗结果与近似模型得出的结果误差一般低于5%,检验了近似模型直接代替仿真试验是可行的。
基于近似模型,本文利用利用全局优化算法(多岛遗传算法)对试验因子进行全局寻优,证明了采用试验设计——近似模型——优化设计的可行性和有效性。
7.根据全局优化算法的优化结果进行仿真分析。其中分析用发动机,离合器、电机和电池等参数均为台架试验值,另将分析用10×NEDC循环工况分成加速、减速和稳态三种工作状态,分别分析了不同状态下发动机、电动机的扭矩、转速、功率和效率分布以及动力电池的电流、电压、功率和效率分布。另外计算了插电式混合动力MPV在50×ECE,100×ECE,20×EUDC,10×NEDC,1×FTP,20×Japan1015,10×UDDS和10×US06等循环工况下整车的燃油经济性。最后对功能样车的纯电动和制动能量回收等基本功能进行了实车检验。
最后对全文进行总结,指出插电式混合动力MPV开发中可供参考的工程应用方法及思路,同时对有待深入研究的不足进行描述。
Current energy and environmental issues as a constraint to the development of modern industry are the important factors, and the automobile industry is the major factor of the environmental pollution and energy consumption. Decreasing energy consumption, reducing vehicle exhaust pollution on our environment, energy-saving and emission reduction of motor vehicle research, such works have important strategic significance. Through a large number of different countries'studies of the national environmental protection and energy saving technology to the automotive industry, the results show that hybrid electric vehicle (HEV) is the most industrial, commercial prospects for mass production of environmentally friendly cars, and which has gotten a lot of attention. The plug-in hybrid electric vehicle (PHEV), using of high-capacity battery to improve hybrid electric vehicle's (HEV) performance, further enhance the degree of people's attention. In this dissertation, a company's plug-in hybrid MPV is discussed.
This dissertation is divided into seven parts.
1. Based on the mechanism of energy saving of the hybrid electric vehicle, the contribution and potential of the energy-saving of the crucial parts, the writer analyses the energy-saving way of the HEV. Through research and analyze domestic and international research and development trends and government support policies of the hybrid electric vehicles, the direction of the development of hybrid vehicles is determined. The current hybrid development process, development tools, optimization methods and test equipment are also discussed in this dissertation.
2. The advantages and disadvantages of the hybrid electric vehicles with different types and different structural forms are analyzed, ultimately the power train of the plug-in hybrid electric drive system with two clutches is chosen as the finally power train. In this power train configuration, the electric motor is located between the two clutches, and this configuration solves the problems of the vehicle's function which includes hybrid vehicle limp home, security, shift performance and brake energy recovery and other issues.
3. Comparing and analyzing the critical components of the Hybrid electric vehicle, the type of vehicle's components are chosen combined with the development trend of critical components and current technology. The design method of DOH (degree of hybridization) is introduced and an idea DOH is chosen base on the crucial part's parameters.
4. Based on bench test data of crucial components, in the Matlab/Simulink environment, the Pre-transmission parallel configuration with two clutches (before and after electric machine) model is established using the model building method which combins theoretical analysis and bench test data, which provides a necessary simulation platform for the research and development of the control strategy.
5. Control strategies of plug-in hybrid electric MPV with two clutches (before and after electric machine) has a huge impact on vehicle's fuel economy, so this strategy operates the engine in one of three regions depending on the combined power requirement needed by the road and the battery. This dissertation mainly discusses the basic control logic of the propelling systems, such as the engine ON/OFF control logic, the modes switching and torque distribution between pure electric mode and hybrid mode, down and up logic of transmission, the modes switching and torque distribution between regenerative braking mode and the mechanical braking torque, and the strategy of cooling systems of electric motor and engine. Through planning the energy flow of the plug-in hybrid electric MPV, rationally distributing the engine torque and controlling the engine work in the high efficiency area, all these works found a solid foundation for parameters optimization of vehicle control strategy.
6. The parameters of control strategy of the plug-in hybrid electric MPV are optimized under the global optimization algorithm. Traditional optimization methods and expertise are confronted with the problem such as high cost, long time and local optimization, so Design Of Experiment (DOE)—Approximate Model—Optimization Algorithm is chosen as the optimization method in this dissertation. First, sensitivity analysis of ten crucial variables of the control strategy is done using DOE method, The Design Variables used in the control strategy are A (SOC below which the engine is turned on), B (SOC above which the engine is turned off), C (Once on, Minimum time for the engine to stay on), D (Once off, Minimum time for the engine to stay off), E (The wheel torque must be above wh_trq_above_turn_on for this amount of time before the engine turns on), F (The wheel torque must be below wh_trq_below_turn off for this amount of time before the engine turns off), G (min power for the engine to turn on), H (max power for the engine to turn off), I (Charging is forbidden if the SOC is above this value), and J (Charging is allowed if the SOC is below this value). The hybrid electric vehicle's fuel economy is selected as the test target, and to explore the design space and identify significant design variables, a101-level DOE study is carried out using Optimal Latin Hypercube method, and the main factors are gotten from main effect and interactive effect calculations.
Then, through analyzing the construction methods of the approximate model, one Approximate Model is established base on the input and output relationship using Kriging model method, which avoids the high strength simulation, reduce the iterative time. Five points are used to analysis the tolerance between PSAT simulation and Approximate Model, the results show that the tolerances between the PSAT simulation test and the Approximate Model simulation are less than5%, it is clearly seen that the Approximate Model can substitute the direct simulation test commendably.
Finally, global optimization algorithm (multi-island genetic algorithm) is used to find the optimum using the Approximate Model in this dissertation, it is proved that Design Of Experiment (DOE)—Approximate Model—Optimization Algorithm is the feasible and effective optimum design method.
7. Based on global optimization results, the simulations of the plug-in hybrid electric MPV are carried out under the drive cycle50×ECE,100×ECE,20×EUDC,10×NEDC,1×FTP,20×Japan1015,10×UDDS and10×US06. Finally, the MPV's basic functions such as pure electric propelling and regenerative braking are validated.
The simulations of the plug-in hybrid electric MPV are carried out based on optimization results. The parameters of the engine, transmission, motor and battery used in the simulations are bench test values. The10×NEDC driving cycle is divided into three vehicle modes which are celeration, deceleration and steady state. Percentage of the torque, speed, power and efficiency of the engine and motor,and the Percentage of battery current, voltage, power and efficiency are analyzed under the three vehicle modes. Fuel economy of the plug-in hybrid MPV are also calculated under the50×ECE,100×ECE,20×EUDC,10×NEDC,1×FTP,20×Japan1015,10x UDDS and10x US06drive cycle. Finally, the real MPV's basic functions such as pure electric propelling and regenerative braking are validated.
Summary of this thesis points out the engineering methods and ideas which can be used for reference in plug-in hybrid electric MPV design, and the shortages of this thesis needing for further study are also described.
引文
[1]郑娟.数据预测：2010年石油进口依存度将突破50%.证券日报,2005-02-16
[2]刘晖.2009年中国进口石油量占总消耗量的51%.http://www.hhciq.com, 2010-01-27
[3]蒋洪林.09年汽车销1 364.5万辆,乘用车1033.1万辆.http://news.bitauto.com, 2010-01-11
[4]夏青.2010年汽车销售量将上升15%.证券日报,2009-12-29
[5]网易财经.2012年北京或实行国V汽车排放标准.http://money.163.com, 2010-02-20
[6]余志生.汽车理论.第四版.北京：机械工业出版社,2002
[7]C. P. Mudannayake, M. F. Rahman. An Integrated Starter Alternator for the 42V PowerNet. Proc.2003 IEEE Power Electronics and Drive Systems,2003,1: 648-653
[8]William CAI. Comparison and Review of Electric Machines for Integrated Starter Alternator Applications. In:39th IAS Annual Meeting, Conference Record of the 2004 IEEE, Industry Applications Conference, IEEE.2004,1: 386-393
[9]Wolfgang Reik, Dierk Reitz, Martin Vornehm, etal.混合动力技术—艰难的选择.舍弗勒科技日,2007,5：116-129
[10]许鸿德,谭浩鹏.欧洲车厂的节能之路：stop-start系统卷土重来.汽车杂志,2008,1：154-157
[11]Bolko Schuseil, Hermann Stief, Zhou Peng.皮带与链传动系统解决方案.舍弗勒科技日,2007,5：22-31
[12]叶先军,赵韩,张炳力等.BSG混合动力轿车动力系统参数设计及试验研究.汽车技术,2008,6：24-27
[13]Andreas Malikopoulos, Zoran Filipi. Dennis Assanis. Simulation of an Integra-ted Starter Alternator (ISA) System for the HMMWV. SAE Paper,2006-01-0442
[14]李振磊,林逸,龚旭.基于Start-Stop技术的微混轿车仿真及试验研究.中国机械工程,2010,21(1)：110-114
[15]陈清泉,孙逢春,祝嘉光.现代电动汽车技术.第一版.北京：北京理工大学出版社,2002
[16]卢山,高峰,史广奎.并联型混合动力汽午的仿真研究.机电工程技术,2005, 34(5)：59-61
[17]何洪文.混合动力车辆驱动系研究和控制策略分析：[北京理工大学博士学位论文].北京：北京理工大学,2003
[18]初亮.混合动力总成的控制算法和参数匹配研究：[吉林大学博士学位论文].长春：吉林大学,2002
[19]刘明辉.混合动力客车整车控制策略及总成参数匹配研究：[吉林大学博士学位论文].长春：吉林大学,2005
[20]曾小华.混合动力客车节能机理与参数设计方法研究：[吉林大学博士学位论文].长春：吉林大学,2005
[21]邵海岳.混合动力汽车驱动系统设计及控制策略优化：[湖南大学硕士学位论文].长沙：湖南大学,2004
[22]Powertrain System Analysis Toolkit (PSAT) Users'Guide. Argonne National Labroarory,2007
[23]吴森,找世科.串联式混合动力电动汽车经济性研究.武汉理工大学学报,2005,27(1)：111-115
[24]刘明辉,赵子亮,李骏.混合动力汽车节油机理研究.汽车技术,2005,5：11-13
[25]黄妙华,喻厚宇.影响并联混合动力电动汽车发动机在高效区工作的因素.汽车工程,2005,27(1)：11-15
[26]吴森,赵世科.串联式混合动力电动汽车经济性研究.武汉理工大学学报,2005,27(1)：111-115
[27]Wakefield, Ernest H. History of the Electric Automobile Hybrid Electric Vehicles. Warrendale, PA:Society of Automotive Engineers,1998,354
[28]Sharer, P, Rousseau, A, Nelson, P., Pagerit, S.. Vehicle Simulation Results for PHEV Battery Requirements. In:22th International Electric Vehicle Symposium (EVS22). Yokohama,2006
[29]Karbowski, D., Rousseau, A, Pagerit, S., Sharer, P.. Plug-in Vehicle Control Strategy:From Global Optimization to Real Time Application. In: 22th International Electric Vehicle Symposium (EVS22). Yokohama,2006
[30]Rousseau, A. Pagerit, S., Gao, D.. Plug-in Hybrid Electric Vehicle Control Strategy Parameter Optimization. In:23rd International Electric Vehicle Symposium (EVS23). Anaheim, CA,2007
[31]Nelson, P., Amine, K., Rousseau, A., Yomoto, H.. Advanced Lithium-ion Batteries for Plug-in Hybrid-Electric Vehicles. In: 23rd International Electric Vehicle Symposium (EVS23). Anaheim, CA,2007
[32]A. Moawad, G. Singh, S. Hagspiel, M. Fellah, A. Rousseau. Real World Drive Cycles on PHEV Fuel Efficiency and Cost for Different Powertrain and Battery Characteristics. In:24rd International Electric Vehicle Symposium (EVS24). Norway,2009
[33]陈晓东,高世杰.混合动力汽车发展所面临的挑战.汽车工业研究,2001,6：16-20
[34]陈清泉,孙逢春.电动汽车的现状和发展趋势.科技导报,2005,23(4)：24-28
[35]徐阳,吴森.发展混合动力技术推动电动汽车产业化进程.武汉理工大学学报,2005,27(3)：56-59
[36]孙逢春.电动汽车发展现状及趋势.科学中国人,2005,8：44-47
[37]陈小复.美国插电式混合动力车项目.上海汽车,2009,1：9-13
[38]网易汽车.国外混合动力汽车发展现状分析.http://auto.163.com,2010-04-09
[39]周荣.国内外电动汽车发展现状和趋势.http://auto.163.com,2010-04-09
[40]Mercedes-Benz S400 Blue HYBRID:The CO2 champion in the luxury class, with an efficient hybrid drive system and lithiumion technology. http://media. daimler.com,2008-09-17
[41]Electric & Plug-in Hybrid Electric Vehicles. http://www.hawaiirenewable.com, 2010-01-17
[42]Green Car Congress. BYD Auto To Begin Sales of F3DM Plug-in to Individuals. http://www.greencarcongress.com,2010-03-23
[43]黄伟.基于CVT的四轮驱动混合动力汽车传动控制策略研究：[湖南大学博士学位论文].长沙：湖南大学,2008
[44]2010 Ford EscapE hybrid. http://www.media.ford.com,2009-07
[45]Scott Anderson. Volt Charges GM's Plug-in Hybrid Future. Ward's Engine & Vehicle Technology Update,2007,33(3):1-3
[46]Koichiro Muta, Makoto Yamazaki, Junji Tokieda. Development of New-Generation Hybrid System THS Ⅱ-Drastic Improvement of Power Performance and Fuel Economy. SAE Paper,2004-01-0064
[47]Bob Czarnowski. Powertrain Strategies for the 21st Century. BorgWarner, 2009-07-15
[48]关于提请审议《中华人民共和国大气污染防治法》(修订草案送审稿)的请示环境保护部文件,环法(2010)13号
[49]米庆林,王庆年,曾小华等.基于V模式的混合动力汽车多能源动力总成控制器开发平台.吉林大学学报(工学版),2007,37(6)：]242-1246
[50]韦作高,刘振军,叶明等.基于dSPACE的混合动力实验台系统开发研究.重庆交通大学学报(自然科学版),2008,27(3)：470-473
[51]刘志茹.混合动力汽车动态过程主动控制研究：[吉林大学博士学位论文].长春：吉林大学,2005
[52]张翔,赵韩,钱立军等.混合动力轿车的建模与仿真.计算机仿真,2005,22(1)：233-237
[53]张翔.电动汽车建模与仿真的研究：[合肥工业大学博士后学位论文].合肥：合肥工业大学,2004
[54]Namdoo Kim, Richard Carlson, Forrest Jehlik, etal. Tahoe HEV Model Develop-ment in PSAT. SAE paper,2009-01-1307
[55]Aymeric Rousseau, Sylvain Pagerit, David Gao. Plug-in Hybrid Electric Vehicle Control Strategy Parameter Optimization. In:23rd International Electric Vehicle Symposium (EVS23). Anaheim,2007
[56]刘松灵.插电式全混混合动力轿车控制策略研究与整车性能仿真分析：[上海交通大学硕士学位论文].上海：上海交通大学硕士学位论文,2009
[57]曾小华,余永涛,王加雪等.基于CRUISE软件的混合动力客车主动同步换挡的建模与仿真.吉林大学学报(工学版),2008,38(5)：1015-1019
[58]张建国,苏多,刘英卫.机械产品可靠性分析与优化.第一版.北京：电子工业出版社,2008
[59]罗玉涛,黄向东,黄河等.混合动力电动汽车多能源动力总成优化研究.汽车工程,2005,27(2)：155-159
[60]Xiaolan Wu, Binggang Cao, Jianping Wen, Yansheng Bian. Particle Swarm Optimization for Plug-in Hybrid Electric Vehicle Control Strategy Parameter. In:IEEE Vehicle Power and Propulsion Conference (VPPC). Harbin,2008
[61]王伟华,金启前,曾小华等.混合动力汽车动力总成试验台研究.中国公路学报,2005,22(1)：233-237
[62]梁龙,张欣,李国岫.混合动力电动汽车驱动系统的开发与应用.汽车工程,2001,23(2)：113-116
[63]Mehrdad Ehsani, Yimin Gao, Sebastien E.Gay, etal.现代电动汽车、混合动力电动汽车和燃料电池车—基本原理、理论和设计.倪光正,倪培宏,熊素铭译.第一版.北京：机械工业出版社,2008
[64]赵世科.串联式混合动力电动汽车经济性研究：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2005
[65]卢山,高峰,史广奎.并联型混合动力汽车的仿真研究.机电工程技术,2005,34(5)：59-61
[66]徐清富.汽车混合动力系统的研究.汽车研究与开发,1999,3：34-37
[67]姜顺明.混合动力汽车动力匹配的研究：[江苏大学硕士学位论文].镇江：江苏大学,2001
[68]卢世刚,刘莎.电动汽车用动力电池的主要发展方向.新材料产业,2005,4：49-53
[69]朱华.发展中的电动汽车用蓄电池.汽车电器,2005,1：1-2
[70]陈军.电动汽车电池能量管理系统及整车控制平台的研究与开发：[浙江大学博士后学位论文].杭州：浙江大学,2005
[71]杜江.电池管理系统的标定及匹配技术研究：[上海交通大学硕士学位论文].上海：上海交通大学,2009
[72]何洪文,余晓江.电动车辆动力电池的性能评价.吉林大学学报,2006,5(36)：659-663
[73]邢伟岩.混合动力电动汽车能量存储系统的性能研究及仿真：[大连理工大学硕士学位论文].大连：大连理工大学,2003
[74]杨利辉.电动汽车驱动电机控制器的优化设计：[重庆大学硕士学位论文].重庆：重庆大学,2004
[75]陈燕.电动汽车用开关磁阻电机DSP控制器软件设计：[北京交通大学硕士学位论文].北京：北京交通大学,2004
[76]杨岳峰.电动汽车用开关磁阻电机DSP控制器软件设计：[北京交通大学硕士学位论文].北京：北京交通大学,2004
[77]郑洪涛.电动汽车用异步电动机矢量控制系统研究：[浙江大学博士后学位论文].杭州：浙江大学,2005
[78]杨超.电动汽车用永磁同步电动机驱动系统的模糊控制仿真：[重庆大学硕士学位论文].重庆：重庆大学,2004
[79]谷峪.电动汽车用永磁同步电机控制系统研究与设计：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2007
[80]刘素芳.电动汽车用永磁同步电机模糊控制仿真：[中国农业大学硕士学位论文].北京：中国农业大学,2006
[81]石勇.电动汽车用永磁同步电机直接转矩控制的研究：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2007
[82]杨立勇.电动汽车用永磁无刷直流电机控制技术研究：[重庆大学硕士学位论文].重庆：重庆大学,2004
[83]陈桂兰.交流异步电机夫速度传感器矢量控制方法及其在电动汽车中的应用研究：[中国科学院电工研究所博士学位论文].北京：中国科学院,2005
[84]江海蛟.电动汽乍用稀土磁无刷直流电机的控制方式研究：[西北工业大 学硕士学位论文].西安：西北工业大学,2004
[85]伍理勋.电动汽车用异步电动机矢量控制系统：[中南大学硕士学位论文].长沙：中南大学,2006
[86]陈安红.电动汽车电机驱动控制系统研究：[长安大学硕士学位论文].西安：长安大学,2006
[87]汪伟.电动汽车高性能异步电机的直接转矩控制研究：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2004
[88]李珂.电动汽车高效快响应电驱动系统控制策略研究：[山东大学博士学位论文].济南：山东大学,2007
[89]费德成.HEV用永磁同步电机优化设计与系统性能分析：[江苏大学博士学位论文].镇江：江苏大学,2008
[90]张好明.PHEV复合电源及Halbach永磁同步电机驱动技术的研究：[江苏大学博士学位论文].镇江：江苏大学,2009
[91]张献伟.Plug-in并联混合动力轿车动力性能仿真及试验结果分析：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2008
[92]王伟,王庆年,王鹏宇等.基于车辆循环工况并联混合动力汽车感应电机额定功率和效率的匹配.吉林大学学报(工学版),2008,38(2)：12-17
[93]彭涛,陈全世.并联混合动力电动汽车动力系统的参数匹配.机械工程学报,2003,39(2)：69-73
[94]浦金欢.混合动力汽车能量优化管理与控制策略研究：[上海交通大学博士学位论文].上海：上海交通大学,2004
[95]张欣,郝小健,李从心等.并联式混合动力电动汽车动力总成控制策略的仿真研究.汽车工程,2005,27(2)：141-145
[96]李国岫,李秀杰.并联式混合动力电动汽车动力总成控制策略的研究.公路交通科技,2005,22(4)：129-135
[97]廖海涛.多能源动力总成控制系统的控制策略及仿真：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2003
[98]于俊伟.并联式混合动力电动汽车(PHEV)控制策略及仿真研究：[北京交通大学硕士学位论文].北京：北京交通大学,2004
[99]程莺,罗禹贡,李克强等.前向式混合动力系统模型中控制器建模与仿真.汽车技术,2005,4：15-19
[100]李争,赵涛,姜卫东等.并联式混合动力电动汽车模糊控制策略的仿真研究.公路交通科技,2005,22(2)：126-130
[101]井济民,王旭东.单轴并联式混合动力汽车能量分配的模糊控制策略研究.齐齐哈尔大学学报,2010,26(2)：15-18
[102]王群京,赵涛,姜卫东等.并联式混合动力电动汽车模糊优化控制的仿真研究.系统仿真学报,2004,16(7)：1525-1529
[1 03]钱立军,袭著永.模糊逻辑控制在并联混合动力汽车中的应用.合肥工业大学学报(自然科学版),2004,27(11)：1456-1459
[104]段岩波,张武高,黄震.混合动力汽车模糊逻辑控制策略仿真.内燃机工程,2003,24(2)：66-69
[105]赵树恩,李玉玲.并联混合动力汽车扭矩管理的模糊控制与仿真.车用发动机,2004,10：27-31
[106]邱海漩.并联式混合动力电动汽车的模糊逻辑控制：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2003
[107]李欣.并联式混合动力电动汽车动力系统的模糊控制策略研究：[西安理工大学硕士学位论文].西安：西安理工大学,2007
[108]Arun Rajagopalan, Gregory Washington, Giorgio Rizzoni, etal. Development of Fuzzy Logic and Neural Network Control and Advanced Emissions Modeling for Parallel Hybrid Vehicles. Center for Automotive Research Intelligent Structures and Systems Laboratory, the Ohio State University,2001:22～26
[109]Wang Aihual. Novel Design of Energy Control Strategy for Parallel Hybrid Electric Vehicle. Transactions of Nanjing University of Aeronautics & Astronautics,2009,26(2):107-113
[110]Aymeric Rousseau, Sylvain Saglini, Micheal Jakov, etal. Trade-Offs Between Fuel Economy and NOx Emissions Using Fuzzy Logic Control with a Hybrid CVT Configuration. International Jounal of Automotive Technology,2003, 4(1):47-55
[111]Yimin Gao, Ehsani, M.. Design and Control Methodology of Plug-in Hybrid Electric Vehicles. In:Vehicle Power and Propulsion Conference (VPPC), IEEE. Harbin,2008
[112]Fazal U.Syed, Ming L.Kuang, Matt Smith, etal. Fuzzy Gain-Scheduling Proportional-Integral Control for Improving Engine Power and Speed Behavior in a Hybrid Electric Vehicle. In:Transactions on Vehicular Technology, IEEE.2009,58(1):69-84
[113]王伟华.并联混合动力汽车的控制：[吉林大学博上学位论文].长春：吉林大学,2005
[114]Karbowski, D., Rousseau, A., Pagerit, S., etal. Plug-in Vehicle Control Strategy:From Global Optimization to Real Time Application. In:22th International Electric Vehicle Symposium (EVS22). Yokohama,2006
[115]孟铭,杜爱民.并联式混合动力汽车的基本控制策略和实时控制策略的比较分析.内燃机工程,2005,26(3)：11-14
[116]邵海岳,邵海燕,钟志华等.并联式混合动力汽车的实时控制策略优化.贵州工业大学学报(自然科学版),2004,33(4)：94-98
[117]王庆年,郑君峰,王伟华.一种新的并联混合动力客车的自适应控制策略.吉林大学学报(工学版),2008,38(2)：249-253
[118]吴剑.并联式混合动力汽车能量管理策略优化研究：[山东大学博士学位论文].济南：山东大学,2008
[119]刘家良.基于模糊神经网络的混合动力电动汽车能量管理的研究：[硕士学位论文].武汉：武汉理工大学,2003
[120]张欣,郝小健,李从心,岑艳.并联式混合动力电动汽车动力总成控制策略的仿真研究.汽车工程,2005,27(2)：141-145
[121]Galdi V, Ippolito L, Piccolo A, et al. A Genetic Based Methodology for Hybrid Electric Vehicle Sizing. Soft Computing,2001,5(6):451-457
[122]Piccolo A., Ippolito L., Galdi V., et al. Optimization of Energy Flow Management in Hybrid Electric Vehicles via Genetic Algorithms. In: Proceedings IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Como,2001,434-439
[123]Ippolito L., Loia V., Siano P.. Extended Fuzzy C-Means and Genetic Algorit-hms to Optimize Power Flow Management in Hybrid Electric Vehicles. In: Proceedings of 2003 IEEE Conference on Control Applications. Istanbul,2003, 1:115-119
[124]吴静波,张承宁,邹渊等.基于遗传蚁群算法的履带式混合动力车辆控制策略参数优化.车用发动机,2009,3：44-48
[125]A.S. Hedayat, N.J.A. Sloane, John Stufken. Orthogonal Arrays:Theory and Applications. New York:Springer-Verlag,1999
[126]Boxin Tang. Orthogonal Array-Based Latin Hypercubes. Journal of the American Statistical Association,1993,88(424):1392-1397
[127]M.E. Johnson, L.M. Moore, D. Ylvisaker. Minimax and Maximin Distance Designs. Journal of Statistical Planning and Inference,1990,26:131-148
[128]M.D. McKay, R.J. Beckman, W.J. Conover. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics,2000,42(1):55-61
[129]Kurt Palmer, Kwok-Leung Tsui. Aminimum Bias Latin Hypercube Design. HE Transactions,2001,33(9):793-808
[130]Stephen Leary, Atul Bhaskar, Andy Keane. Optimal Orthogonal-Array-based Latin Hypercubes. Journal of Applied Statistics,2003,30(5):585-598
[131]Michael Stein. Large Sample Properties of Simulations Using Latin Hypercu-be Sampling. Technometrics,1987,29(2):143-151
[132]Andrew J. Booker, J.E, Dennis, Jr., etal. Optimization Using Surrogate Objec-tives on a Helicopter Test Example. Computational Methods in Optimal Design and Control. Boston:Birkhauser,1998,49-58
[133]Knill Duane L., Giunta Anthony A., Baker Chuck A., etal. Response Surface Models Combining Linear and Euler aerodynamics for Supersonic Transport Design. Journal of Aircraft,1999,36(1):75-86
[134]Man Mohan Rai, Nateri K. Madavan. Aerodynamic Design Using Neural Net-works. AIAA Journal,2000,38(1):173-182.
[135]MM Rai, NK Madavan, FW Huber. Improving the Unsteady Aerodynamic Performance of Transonic Turbines Using Neural Networks. In:Proceedings of the 38th AIAA Aerospace Sciences Meeting and Exhibit. Reno,2000, AIAA 2000-0169.
[136]Nateri K. Madavan, Man Mohan Rai, Frank W. Huber. Neural Net-Based Redesign of Transonic Turbines for Improved Unsteady Aerodynamic Perform-ance. In:AIAA/SAE/ASME/ASEE 35th Joint Propulsion Conference.1999, AIAA 99-0559
[137]Jens I. Madsen, Wei Shyy, Raphael T. Haftka. Response Surface Techniques for Diffuser Shape Optimization. AIAA Journal,2000,38(9):1512-1518
[138]Papila Nilay, Shyy Wei, Griffin Lisa, etal. Shape Optimization of Supersonic Turbines Using Global Approximation Methods. Journal of Propulsion and Power,2002,18(3):509-518
[139]Shyy Wei, Papila Nilay, Tucker Kevin, etal. Global Optimization for Fluid Machinery Applications. In:Proceedings of the Second International Symposium on Fluid Machinery and Fluid Engineering(ISFMFE). Beijing, 2000,1-10
[140]Wei Shyy, Nilay Papila, Rajkumar Vaidyanathan, etal. Global Design Optimi-zation for Aerodynamics and Rocket Propulsion Components. Progress in Aerospace Sciences,2001,37(1):59-118
[141]Rajkumar Vaidyanathan, P. Kevin Tucker, Nilay Papila, etal. CFD Based Optimization for a Single Element Rocket Injector. In:41st Aerospace Sciences Meeting and Exhibit. Reno,2003, AIAA 2003-296
[142]Rajkumar Vaidyanathan, Tushar Goel, Wei Shyy, etal. Global Sensitivity and Trade-Off Analyses for Multi-Objective Liquid Rocket Injector Design. In: Proceedings of the 40th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit. Fort Lauderdale,2004, AIAA 2004-4007
[143]Tushar Goel, Rajkumar Vaidyanathan, Raphael T. Haftka, etal. Response Surface Approximation of Pareto Optimal Front in Multi-Objective Optimization. In:Proceedings of the 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. New York,2004, AIAA 2004-4501
[144]Hyoung-Seog Chung, Juan J. Alonso. Comparison of Approximation Models with Merit Functions for Design Optimization. In:Proceedings of the 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Long Beach,2000, AIAA 2000-4754
[145]Ruichen Jin, Wei Chen, Timothy W. Simpson. Comparative Studies of Metamodeling Techniques Under Multiple Modeling Criteria. Structural and Multidisciplinary Optimization,2001,23(1):1-13
[146]Douqlas C. Montgomery, Raymond H. Myers. Response Surface Methodology: Process and Product Optimization Using Designed Experiment. New York: Wiley,1995
[147]G.E.P. Box, Norman R. Draper. A Basis for the Selection of a Response Surface Design. Journal of the American Statistical Association,1959,54(287): 622-654
[148]Dale B. McDonald, Walter J. Grantham, Wayne L. Tabor, etal. Response Surface Model Development for Global and Local Optimization Using Radial Basis Functions. In:Proceedings of the 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Long Beach,2000, AIAA 2000-4776
[149]Timothy W. Simpson, Timothy M. Mauery, John J. Korte, etal. Kriging Models for Global Approximation in Simulation-Based Multidisciplinary Design Optimization. AIAA Journal,2001,39(12):2233-2241
[150]Donald R. Jones, Matthias Schonlau, William J. Welch. Efficient Global Opti-mization of Expensive Black-Box Functions. Journal of Global Optimization, 1998,13(4):455-492
[151]刘金琨.先进PID控制MATLAB仿真.第二版.北京：电子工业出版社2005,210-212
[152]Hong Chen, Ryozo Ooka, Shinsuke Kato. Study on Optimum Design Method for Pleasant Outdoor Thermal Environment Using Genetic Algorithms and Coupled Simulation of Convection, Radiation and Conduction. Building and Environment,2008,43(1):18-31
[153]杜春江,钱林方,徐亚栋等.炮塔体结构分析与优化.系统仿真学报,2009,21(15)： 4899-4902
[154]Ayman Moawad, Gurhari Singh, Simeon Hagspiel, etal. Impact of Real World Drive Cycles on PHEV Fuel Efficiency and Cost for Different Powertrain and Battery Characteristics. In:EVS24 International Batterey, Hybird and Fuel Cell Electric Vehicle Symposium. Stavanger,2009
[2]刘晖.2009年中国进口石油量占总消耗量的51%.http://www.hhciq.com, 2010-01-27
[3]蒋洪林.09年汽车销1 364.5万辆,乘用车1033.1万辆.http://news.bitauto.com, 2010-01-11
[4]夏青.2010年汽车销售量将上升15%.证券日报,2009-12-29
[5]网易财经.2012年北京或实行国V汽车排放标准.http://money.163.com, 2010-02-20
[6]余志生.汽车理论.第四版.北京：机械工业出版社,2002
[7]C. P. Mudannayake, M. F. Rahman. An Integrated Starter Alternator for the 42V PowerNet. Proc.2003 IEEE Power Electronics and Drive Systems,2003,1: 648-653
[8]William CAI. Comparison and Review of Electric Machines for Integrated Starter Alternator Applications. In:39th IAS Annual Meeting, Conference Record of the 2004 IEEE, Industry Applications Conference, IEEE.2004,1: 386-393
[9]Wolfgang Reik, Dierk Reitz, Martin Vornehm, etal.混合动力技术—艰难的选择.舍弗勒科技日,2007,5：116-129
[10]许鸿德,谭浩鹏.欧洲车厂的节能之路：stop-start系统卷土重来.汽车杂志,2008,1：154-157
[11]Bolko Schuseil, Hermann Stief, Zhou Peng.皮带与链传动系统解决方案.舍弗勒科技日,2007,5：22-31
[12]叶先军,赵韩,张炳力等.BSG混合动力轿车动力系统参数设计及试验研究.汽车技术,2008,6：24-27
[13]Andreas Malikopoulos, Zoran Filipi. Dennis Assanis. Simulation of an Integra-ted Starter Alternator (ISA) System for the HMMWV. SAE Paper,2006-01-0442
[14]李振磊,林逸,龚旭.基于Start-Stop技术的微混轿车仿真及试验研究.中国机械工程,2010,21(1)：110-114
[15]陈清泉,孙逢春,祝嘉光.现代电动汽车技术.第一版.北京：北京理工大学出版社,2002
[16]卢山,高峰,史广奎.并联型混合动力汽午的仿真研究.机电工程技术,2005, 34(5)：59-61
[17]何洪文.混合动力车辆驱动系研究和控制策略分析：[北京理工大学博士学位论文].北京：北京理工大学,2003
[18]初亮.混合动力总成的控制算法和参数匹配研究：[吉林大学博士学位论文].长春：吉林大学,2002
[19]刘明辉.混合动力客车整车控制策略及总成参数匹配研究：[吉林大学博士学位论文].长春：吉林大学,2005
[20]曾小华.混合动力客车节能机理与参数设计方法研究：[吉林大学博士学位论文].长春：吉林大学,2005
[21]邵海岳.混合动力汽车驱动系统设计及控制策略优化：[湖南大学硕士学位论文].长沙：湖南大学,2004
[22]Powertrain System Analysis Toolkit (PSAT) Users'Guide. Argonne National Labroarory,2007
[23]吴森,找世科.串联式混合动力电动汽车经济性研究.武汉理工大学学报,2005,27(1)：111-115
[24]刘明辉,赵子亮,李骏.混合动力汽车节油机理研究.汽车技术,2005,5：11-13
[25]黄妙华,喻厚宇.影响并联混合动力电动汽车发动机在高效区工作的因素.汽车工程,2005,27(1)：11-15
[26]吴森,赵世科.串联式混合动力电动汽车经济性研究.武汉理工大学学报,2005,27(1)：111-115
[27]Wakefield, Ernest H. History of the Electric Automobile Hybrid Electric Vehicles. Warrendale, PA:Society of Automotive Engineers,1998,354
[28]Sharer, P, Rousseau, A, Nelson, P., Pagerit, S.. Vehicle Simulation Results for PHEV Battery Requirements. In:22th International Electric Vehicle Symposium (EVS22). Yokohama,2006
[29]Karbowski, D., Rousseau, A, Pagerit, S., Sharer, P.. Plug-in Vehicle Control Strategy:From Global Optimization to Real Time Application. In: 22th International Electric Vehicle Symposium (EVS22). Yokohama,2006
[30]Rousseau, A. Pagerit, S., Gao, D.. Plug-in Hybrid Electric Vehicle Control Strategy Parameter Optimization. In:23rd International Electric Vehicle Symposium (EVS23). Anaheim, CA,2007
[31]Nelson, P., Amine, K., Rousseau, A., Yomoto, H.. Advanced Lithium-ion Batteries for Plug-in Hybrid-Electric Vehicles. In: 23rd International Electric Vehicle Symposium (EVS23). Anaheim, CA,2007
[32]A. Moawad, G. Singh, S. Hagspiel, M. Fellah, A. Rousseau. Real World Drive Cycles on PHEV Fuel Efficiency and Cost for Different Powertrain and Battery Characteristics. In:24rd International Electric Vehicle Symposium (EVS24). Norway,2009
[33]陈晓东,高世杰.混合动力汽车发展所面临的挑战.汽车工业研究,2001,6：16-20
[34]陈清泉,孙逢春.电动汽车的现状和发展趋势.科技导报,2005,23(4)：24-28
[35]徐阳,吴森.发展混合动力技术推动电动汽车产业化进程.武汉理工大学学报,2005,27(3)：56-59
[36]孙逢春.电动汽车发展现状及趋势.科学中国人,2005,8：44-47
[37]陈小复.美国插电式混合动力车项目.上海汽车,2009,1：9-13
[38]网易汽车.国外混合动力汽车发展现状分析.http://auto.163.com,2010-04-09
[39]周荣.国内外电动汽车发展现状和趋势.http://auto.163.com,2010-04-09
[40]Mercedes-Benz S400 Blue HYBRID:The CO2 champion in the luxury class, with an efficient hybrid drive system and lithiumion technology. http://media. daimler.com,2008-09-17
[41]Electric & Plug-in Hybrid Electric Vehicles. http://www.hawaiirenewable.com, 2010-01-17
[42]Green Car Congress. BYD Auto To Begin Sales of F3DM Plug-in to Individuals. http://www.greencarcongress.com,2010-03-23
[43]黄伟.基于CVT的四轮驱动混合动力汽车传动控制策略研究：[湖南大学博士学位论文].长沙：湖南大学,2008
[44]2010 Ford EscapE hybrid. http://www.media.ford.com,2009-07
[45]Scott Anderson. Volt Charges GM's Plug-in Hybrid Future. Ward's Engine & Vehicle Technology Update,2007,33(3):1-3
[46]Koichiro Muta, Makoto Yamazaki, Junji Tokieda. Development of New-Generation Hybrid System THS Ⅱ-Drastic Improvement of Power Performance and Fuel Economy. SAE Paper,2004-01-0064
[47]Bob Czarnowski. Powertrain Strategies for the 21st Century. BorgWarner, 2009-07-15
[48]关于提请审议《中华人民共和国大气污染防治法》(修订草案送审稿)的请示环境保护部文件,环法(2010)13号
[49]米庆林,王庆年,曾小华等.基于V模式的混合动力汽车多能源动力总成控制器开发平台.吉林大学学报(工学版),2007,37(6)：]242-1246
[50]韦作高,刘振军,叶明等.基于dSPACE的混合动力实验台系统开发研究.重庆交通大学学报(自然科学版),2008,27(3)：470-473
[51]刘志茹.混合动力汽车动态过程主动控制研究：[吉林大学博士学位论文].长春：吉林大学,2005
[52]张翔,赵韩,钱立军等.混合动力轿车的建模与仿真.计算机仿真,2005,22(1)：233-237
[53]张翔.电动汽车建模与仿真的研究：[合肥工业大学博士后学位论文].合肥：合肥工业大学,2004
[54]Namdoo Kim, Richard Carlson, Forrest Jehlik, etal. Tahoe HEV Model Develop-ment in PSAT. SAE paper,2009-01-1307
[55]Aymeric Rousseau, Sylvain Pagerit, David Gao. Plug-in Hybrid Electric Vehicle Control Strategy Parameter Optimization. In:23rd International Electric Vehicle Symposium (EVS23). Anaheim,2007
[56]刘松灵.插电式全混混合动力轿车控制策略研究与整车性能仿真分析：[上海交通大学硕士学位论文].上海：上海交通大学硕士学位论文,2009
[57]曾小华,余永涛,王加雪等.基于CRUISE软件的混合动力客车主动同步换挡的建模与仿真.吉林大学学报(工学版),2008,38(5)：1015-1019
[58]张建国,苏多,刘英卫.机械产品可靠性分析与优化.第一版.北京：电子工业出版社,2008
[59]罗玉涛,黄向东,黄河等.混合动力电动汽车多能源动力总成优化研究.汽车工程,2005,27(2)：155-159
[60]Xiaolan Wu, Binggang Cao, Jianping Wen, Yansheng Bian. Particle Swarm Optimization for Plug-in Hybrid Electric Vehicle Control Strategy Parameter. In:IEEE Vehicle Power and Propulsion Conference (VPPC). Harbin,2008
[61]王伟华,金启前,曾小华等.混合动力汽车动力总成试验台研究.中国公路学报,2005,22(1)：233-237
[62]梁龙,张欣,李国岫.混合动力电动汽车驱动系统的开发与应用.汽车工程,2001,23(2)：113-116
[63]Mehrdad Ehsani, Yimin Gao, Sebastien E.Gay, etal.现代电动汽车、混合动力电动汽车和燃料电池车—基本原理、理论和设计.倪光正,倪培宏,熊素铭译.第一版.北京：机械工业出版社,2008
[64]赵世科.串联式混合动力电动汽车经济性研究：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2005
[65]卢山,高峰,史广奎.并联型混合动力汽车的仿真研究.机电工程技术,2005,34(5)：59-61
[66]徐清富.汽车混合动力系统的研究.汽车研究与开发,1999,3：34-37
[67]姜顺明.混合动力汽车动力匹配的研究：[江苏大学硕士学位论文].镇江：江苏大学,2001
[68]卢世刚,刘莎.电动汽车用动力电池的主要发展方向.新材料产业,2005,4：49-53
[69]朱华.发展中的电动汽车用蓄电池.汽车电器,2005,1：1-2
[70]陈军.电动汽车电池能量管理系统及整车控制平台的研究与开发：[浙江大学博士后学位论文].杭州：浙江大学,2005
[71]杜江.电池管理系统的标定及匹配技术研究：[上海交通大学硕士学位论文].上海：上海交通大学,2009
[72]何洪文,余晓江.电动车辆动力电池的性能评价.吉林大学学报,2006,5(36)：659-663
[73]邢伟岩.混合动力电动汽车能量存储系统的性能研究及仿真：[大连理工大学硕士学位论文].大连：大连理工大学,2003
[74]杨利辉.电动汽车驱动电机控制器的优化设计：[重庆大学硕士学位论文].重庆：重庆大学,2004
[75]陈燕.电动汽车用开关磁阻电机DSP控制器软件设计：[北京交通大学硕士学位论文].北京：北京交通大学,2004
[76]杨岳峰.电动汽车用开关磁阻电机DSP控制器软件设计：[北京交通大学硕士学位论文].北京：北京交通大学,2004
[77]郑洪涛.电动汽车用异步电动机矢量控制系统研究：[浙江大学博士后学位论文].杭州：浙江大学,2005
[78]杨超.电动汽车用永磁同步电动机驱动系统的模糊控制仿真：[重庆大学硕士学位论文].重庆：重庆大学,2004
[79]谷峪.电动汽车用永磁同步电机控制系统研究与设计：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2007
[80]刘素芳.电动汽车用永磁同步电机模糊控制仿真：[中国农业大学硕士学位论文].北京：中国农业大学,2006
[81]石勇.电动汽车用永磁同步电机直接转矩控制的研究：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2007
[82]杨立勇.电动汽车用永磁无刷直流电机控制技术研究：[重庆大学硕士学位论文].重庆：重庆大学,2004
[83]陈桂兰.交流异步电机夫速度传感器矢量控制方法及其在电动汽车中的应用研究：[中国科学院电工研究所博士学位论文].北京：中国科学院,2005
[84]江海蛟.电动汽乍用稀土磁无刷直流电机的控制方式研究：[西北工业大 学硕士学位论文].西安：西北工业大学,2004
[85]伍理勋.电动汽车用异步电动机矢量控制系统：[中南大学硕士学位论文].长沙：中南大学,2006
[86]陈安红.电动汽车电机驱动控制系统研究：[长安大学硕士学位论文].西安：长安大学,2006
[87]汪伟.电动汽车高性能异步电机的直接转矩控制研究：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2004
[88]李珂.电动汽车高效快响应电驱动系统控制策略研究：[山东大学博士学位论文].济南：山东大学,2007
[89]费德成.HEV用永磁同步电机优化设计与系统性能分析：[江苏大学博士学位论文].镇江：江苏大学,2008
[90]张好明.PHEV复合电源及Halbach永磁同步电机驱动技术的研究：[江苏大学博士学位论文].镇江：江苏大学,2009
[91]张献伟.Plug-in并联混合动力轿车动力性能仿真及试验结果分析：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2008
[92]王伟,王庆年,王鹏宇等.基于车辆循环工况并联混合动力汽车感应电机额定功率和效率的匹配.吉林大学学报(工学版),2008,38(2)：12-17
[93]彭涛,陈全世.并联混合动力电动汽车动力系统的参数匹配.机械工程学报,2003,39(2)：69-73
[94]浦金欢.混合动力汽车能量优化管理与控制策略研究：[上海交通大学博士学位论文].上海：上海交通大学,2004
[95]张欣,郝小健,李从心等.并联式混合动力电动汽车动力总成控制策略的仿真研究.汽车工程,2005,27(2)：141-145
[96]李国岫,李秀杰.并联式混合动力电动汽车动力总成控制策略的研究.公路交通科技,2005,22(4)：129-135
[97]廖海涛.多能源动力总成控制系统的控制策略及仿真：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2003
[98]于俊伟.并联式混合动力电动汽车(PHEV)控制策略及仿真研究：[北京交通大学硕士学位论文].北京：北京交通大学,2004
[99]程莺,罗禹贡,李克强等.前向式混合动力系统模型中控制器建模与仿真.汽车技术,2005,4：15-19
[100]李争,赵涛,姜卫东等.并联式混合动力电动汽车模糊控制策略的仿真研究.公路交通科技,2005,22(2)：126-130
[101]井济民,王旭东.单轴并联式混合动力汽车能量分配的模糊控制策略研究.齐齐哈尔大学学报,2010,26(2)：15-18
[102]王群京,赵涛,姜卫东等.并联式混合动力电动汽车模糊优化控制的仿真研究.系统仿真学报,2004,16(7)：1525-1529
[1 03]钱立军,袭著永.模糊逻辑控制在并联混合动力汽车中的应用.合肥工业大学学报(自然科学版),2004,27(11)：1456-1459
[104]段岩波,张武高,黄震.混合动力汽车模糊逻辑控制策略仿真.内燃机工程,2003,24(2)：66-69
[105]赵树恩,李玉玲.并联混合动力汽车扭矩管理的模糊控制与仿真.车用发动机,2004,10：27-31
[106]邱海漩.并联式混合动力电动汽车的模糊逻辑控制：[武汉理工大学硕士学位论文].武汉：武汉理工大学,2003
[107]李欣.并联式混合动力电动汽车动力系统的模糊控制策略研究：[西安理工大学硕士学位论文].西安：西安理工大学,2007
[108]Arun Rajagopalan, Gregory Washington, Giorgio Rizzoni, etal. Development of Fuzzy Logic and Neural Network Control and Advanced Emissions Modeling for Parallel Hybrid Vehicles. Center for Automotive Research Intelligent Structures and Systems Laboratory, the Ohio State University,2001:22～26
[109]Wang Aihual. Novel Design of Energy Control Strategy for Parallel Hybrid Electric Vehicle. Transactions of Nanjing University of Aeronautics & Astronautics,2009,26(2):107-113
[110]Aymeric Rousseau, Sylvain Saglini, Micheal Jakov, etal. Trade-Offs Between Fuel Economy and NOx Emissions Using Fuzzy Logic Control with a Hybrid CVT Configuration. International Jounal of Automotive Technology,2003, 4(1):47-55
[111]Yimin Gao, Ehsani, M.. Design and Control Methodology of Plug-in Hybrid Electric Vehicles. In:Vehicle Power and Propulsion Conference (VPPC), IEEE. Harbin,2008
[112]Fazal U.Syed, Ming L.Kuang, Matt Smith, etal. Fuzzy Gain-Scheduling Proportional-Integral Control for Improving Engine Power and Speed Behavior in a Hybrid Electric Vehicle. In:Transactions on Vehicular Technology, IEEE.2009,58(1):69-84
[113]王伟华.并联混合动力汽车的控制：[吉林大学博上学位论文].长春：吉林大学,2005
[114]Karbowski, D., Rousseau, A., Pagerit, S., etal. Plug-in Vehicle Control Strategy:From Global Optimization to Real Time Application. In:22th International Electric Vehicle Symposium (EVS22). Yokohama,2006
[115]孟铭,杜爱民.并联式混合动力汽车的基本控制策略和实时控制策略的比较分析.内燃机工程,2005,26(3)：11-14
[116]邵海岳,邵海燕,钟志华等.并联式混合动力汽车的实时控制策略优化.贵州工业大学学报(自然科学版),2004,33(4)：94-98
[117]王庆年,郑君峰,王伟华.一种新的并联混合动力客车的自适应控制策略.吉林大学学报(工学版),2008,38(2)：249-253
[118]吴剑.并联式混合动力汽车能量管理策略优化研究：[山东大学博士学位论文].济南：山东大学,2008
[119]刘家良.基于模糊神经网络的混合动力电动汽车能量管理的研究：[硕士学位论文].武汉：武汉理工大学,2003
[120]张欣,郝小健,李从心,岑艳.并联式混合动力电动汽车动力总成控制策略的仿真研究.汽车工程,2005,27(2)：141-145
[121]Galdi V, Ippolito L, Piccolo A, et al. A Genetic Based Methodology for Hybrid Electric Vehicle Sizing. Soft Computing,2001,5(6):451-457
[122]Piccolo A., Ippolito L., Galdi V., et al. Optimization of Energy Flow Management in Hybrid Electric Vehicles via Genetic Algorithms. In: Proceedings IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Como,2001,434-439
[123]Ippolito L., Loia V., Siano P.. Extended Fuzzy C-Means and Genetic Algorit-hms to Optimize Power Flow Management in Hybrid Electric Vehicles. In: Proceedings of 2003 IEEE Conference on Control Applications. Istanbul,2003, 1:115-119
[124]吴静波,张承宁,邹渊等.基于遗传蚁群算法的履带式混合动力车辆控制策略参数优化.车用发动机,2009,3：44-48
[125]A.S. Hedayat, N.J.A. Sloane, John Stufken. Orthogonal Arrays:Theory and Applications. New York:Springer-Verlag,1999
[126]Boxin Tang. Orthogonal Array-Based Latin Hypercubes. Journal of the American Statistical Association,1993,88(424):1392-1397
[127]M.E. Johnson, L.M. Moore, D. Ylvisaker. Minimax and Maximin Distance Designs. Journal of Statistical Planning and Inference,1990,26:131-148
[128]M.D. McKay, R.J. Beckman, W.J. Conover. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics,2000,42(1):55-61
[129]Kurt Palmer, Kwok-Leung Tsui. Aminimum Bias Latin Hypercube Design. HE Transactions,2001,33(9):793-808
[130]Stephen Leary, Atul Bhaskar, Andy Keane. Optimal Orthogonal-Array-based Latin Hypercubes. Journal of Applied Statistics,2003,30(5):585-598
[131]Michael Stein. Large Sample Properties of Simulations Using Latin Hypercu-be Sampling. Technometrics,1987,29(2):143-151
[132]Andrew J. Booker, J.E, Dennis, Jr., etal. Optimization Using Surrogate Objec-tives on a Helicopter Test Example. Computational Methods in Optimal Design and Control. Boston:Birkhauser,1998,49-58
[133]Knill Duane L., Giunta Anthony A., Baker Chuck A., etal. Response Surface Models Combining Linear and Euler aerodynamics for Supersonic Transport Design. Journal of Aircraft,1999,36(1):75-86
[134]Man Mohan Rai, Nateri K. Madavan. Aerodynamic Design Using Neural Net-works. AIAA Journal,2000,38(1):173-182.
[135]MM Rai, NK Madavan, FW Huber. Improving the Unsteady Aerodynamic Performance of Transonic Turbines Using Neural Networks. In:Proceedings of the 38th AIAA Aerospace Sciences Meeting and Exhibit. Reno,2000, AIAA 2000-0169.
[136]Nateri K. Madavan, Man Mohan Rai, Frank W. Huber. Neural Net-Based Redesign of Transonic Turbines for Improved Unsteady Aerodynamic Perform-ance. In:AIAA/SAE/ASME/ASEE 35th Joint Propulsion Conference.1999, AIAA 99-0559
[137]Jens I. Madsen, Wei Shyy, Raphael T. Haftka. Response Surface Techniques for Diffuser Shape Optimization. AIAA Journal,2000,38(9):1512-1518
[138]Papila Nilay, Shyy Wei, Griffin Lisa, etal. Shape Optimization of Supersonic Turbines Using Global Approximation Methods. Journal of Propulsion and Power,2002,18(3):509-518
[139]Shyy Wei, Papila Nilay, Tucker Kevin, etal. Global Optimization for Fluid Machinery Applications. In:Proceedings of the Second International Symposium on Fluid Machinery and Fluid Engineering(ISFMFE). Beijing, 2000,1-10
[140]Wei Shyy, Nilay Papila, Rajkumar Vaidyanathan, etal. Global Design Optimi-zation for Aerodynamics and Rocket Propulsion Components. Progress in Aerospace Sciences,2001,37(1):59-118
[141]Rajkumar Vaidyanathan, P. Kevin Tucker, Nilay Papila, etal. CFD Based Optimization for a Single Element Rocket Injector. In:41st Aerospace Sciences Meeting and Exhibit. Reno,2003, AIAA 2003-296
[142]Rajkumar Vaidyanathan, Tushar Goel, Wei Shyy, etal. Global Sensitivity and Trade-Off Analyses for Multi-Objective Liquid Rocket Injector Design. In: Proceedings of the 40th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit. Fort Lauderdale,2004, AIAA 2004-4007
[143]Tushar Goel, Rajkumar Vaidyanathan, Raphael T. Haftka, etal. Response Surface Approximation of Pareto Optimal Front in Multi-Objective Optimization. In:Proceedings of the 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. New York,2004, AIAA 2004-4501
[144]Hyoung-Seog Chung, Juan J. Alonso. Comparison of Approximation Models with Merit Functions for Design Optimization. In:Proceedings of the 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Long Beach,2000, AIAA 2000-4754
[145]Ruichen Jin, Wei Chen, Timothy W. Simpson. Comparative Studies of Metamodeling Techniques Under Multiple Modeling Criteria. Structural and Multidisciplinary Optimization,2001,23(1):1-13
[146]Douqlas C. Montgomery, Raymond H. Myers. Response Surface Methodology: Process and Product Optimization Using Designed Experiment. New York: Wiley,1995
[147]G.E.P. Box, Norman R. Draper. A Basis for the Selection of a Response Surface Design. Journal of the American Statistical Association,1959,54(287): 622-654
[148]Dale B. McDonald, Walter J. Grantham, Wayne L. Tabor, etal. Response Surface Model Development for Global and Local Optimization Using Radial Basis Functions. In:Proceedings of the 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Long Beach,2000, AIAA 2000-4776
[149]Timothy W. Simpson, Timothy M. Mauery, John J. Korte, etal. Kriging Models for Global Approximation in Simulation-Based Multidisciplinary Design Optimization. AIAA Journal,2001,39(12):2233-2241
[150]Donald R. Jones, Matthias Schonlau, William J. Welch. Efficient Global Opti-mization of Expensive Black-Box Functions. Journal of Global Optimization, 1998,13(4):455-492
[151]刘金琨.先进PID控制MATLAB仿真.第二版.北京：电子工业出版社2005,210-212
[152]Hong Chen, Ryozo Ooka, Shinsuke Kato. Study on Optimum Design Method for Pleasant Outdoor Thermal Environment Using Genetic Algorithms and Coupled Simulation of Convection, Radiation and Conduction. Building and Environment,2008,43(1):18-31
[153]杜春江,钱林方,徐亚栋等.炮塔体结构分析与优化.系统仿真学报,2009,21(15)： 4899-4902
[154]Ayman Moawad, Gurhari Singh, Simeon Hagspiel, etal. Impact of Real World Drive Cycles on PHEV Fuel Efficiency and Cost for Different Powertrain and Battery Characteristics. In:EVS24 International Batterey, Hybird and Fuel Cell Electric Vehicle Symposium. Stavanger,2009