基于“人—车—路”闭环的无级自动变速系统硬件在环仿真研究
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摘要
汽车自动变速传动系统硬件在环HIL(Hardware-in-the-loop)试验系统是近年来出现的先进汽车自动变速传动测试系统,其利用硬件(变速传动被测单元)与软件相结合的硬件在环实时仿真技术,将驾驶员、发动机、底盘以及行驶环境等模型化后嵌入到软件环境,模拟出自动变速汽车的实际运行状态,从而实现对自动控制车辆车载控制器、液压/电动控制系统以及动作执行器的工作性能加以试验测试与分析校验,为自动控制汽车的研制开发提供一个测试开发平台。
针对目前汽车自动变速系统硬件在环测试只能进行控制策略测试的局限性,本文结合重庆市科技攻关项目《汽车自动变速器硬件在环试验系统的研制开发》和985平台国家重点实验室开放基金《自动变速器硬件在环仿真平台研究》进行了基于人-车-路闭环的无级自动变速器硬件在环理论建模与仿真试验研究。具体工作内容如下:
(1)针对当前驾驶员模型无法体现驾驶操纵熟练程度的缺点,遵循行驶误差最小与体力负担最小原则,采用遗传算法对模糊PID比例因子和量化因子进行离线优化设计,建立基于遗传算法优化的方向模糊PID与速度模糊综合控制的虚拟驾驶模拟模型,并在纵向速度单向变化、侧向双移线工况与大曲率试验道路典型工况下进行仿真分析,同时将遗传算法优化的模糊PID控制方法与传统PID以及模糊PID进行仿真比较,最后确定不同驾驶类型与不同驾驶意图的表现特征,采用模糊推理方法制定其相应的识别体系。
(2)基于15自由度车辆动力学模型,充分考虑横向坡度、纵向坡度以及合成坡度对车辆动力学与轮胎垂直载荷变化模型的影响,建立横向坡度、纵向坡度与合成坡度车辆动力学与轮胎垂直载荷变化模型,联立转向系、制动系、动力传动系、车轮与悬架模型,构建虚拟车辆动态仿真模型,并进行不同横向、纵向、合成坡度以及车速下进行仿真分析比较,最后联立虚拟驾驶模拟模型,构建人-车闭环系统仿真模型。
(3)从人-车-路闭环系统角度以及实时虚拟仿真系统需求出发,依据公路设计规范与道路设计原理,参考国内外汽车试验场的设计,开发一条符合道路设计标准、逼真度高、且能反映出不同行驶环境的封闭式三维虚拟道路,为进一步研究无级变速系统速比自适应智能综合控制提供前提;并确定包括良好路段、复杂路段、颠簸路段、上坡路段、下坡路段与转弯路段等行驶环境的表现特征,制定相应的行驶环境识别体系。
(4)根据无级变速传动动力学仿真模型,综合考虑后备功率、动力传动系损失以及CVT速比变化响应滞后的影响,制定τ算法、发动机转矩补偿以及发动机转速补偿三种无级变速传动系统综合控制方法,并进行动力性与经济性仿真分析比较;基于CVT最佳动力性与最佳经济性速比控制基础上,制定基于不同驾驶类型、不同驾驶意图、不同单一行驶环境的CVT速比控制策略以及多种行驶环境耦合的CVT速比加权控制策略,其中包括提出综合考虑节气门开度变化率、方向盘转角与转弯车速的转弯修正速比控制策略;综合考虑节气门开度和车速微小变化的颠簸路段离散化速比控制策略;综合考虑节气门开度与纵向坡度的上坡修正速比控制策略;综合考虑下坡初始车速、纵向坡度与下坡坡长的下坡修正速比控制策略;以及不同驾驶类型、驾驶意图与行驶环境耦合工况下的CVT速比自适应智能综合控制策略。
(5)根据人-车闭环系统仿真模型与无级变速系统自适应智能综合控制模型,以及在VRML环境下开发的虚拟道路模拟模型,利用VR工具箱开发虚拟试验场,构建基于Simulink与VR联合仿真平台的人-车-路闭环的无级变速系统自适应智能综合控制仿真模型,并针对不同驾驶类型、不同驾驶意图以及不同单一行驶环境工况下的CVT速比控制仿真分析,以及针对驾驶类型、驾驶意图与行驶环境耦合工况下的CVT速比自适应智能综合控制仿真分析,验证自适应智能综合控制策略可行性与准确性。
(6)基于Matlab/Simulink与dSPACE RTI联合实时仿真环境,自主研制开发无级自动变速器硬件在环仿真试验系统,包括总体方案设计、设备购买、零部件设计加工制造、信号采集与处理,软硬件设计等。基于此试验系统首先进行台架性能测试,根据台架性能测试分析结果,进一步进行基于不同驾驶意图、上坡、下坡、弯道、颠簸路段的CVT速比控制试验,以及耦合工况下的CVT速比自适应智能综合控制试验,从试验角度验证提出的CVT速比控制策略的有效性。
Hardware-in-the-loop (HIL) test system for vehicle automatic transmission driveline system is advanced vehicle automatic transmission driveline test system appeared in recent years, which makes driver, engine, chassis, driving environment and so on simulation model embedded into software environment by utilizing HIL real-time simulation technology combined with hardware and software, for simulating automatic transmission actual operation state, detecting and analyzing the working performance of automotive controller, hydraulic/electrical control system and actuator, then offering a test and development platform for the research and development of automatic transmission automotive.
Against the limitation of current hardware-in-the-loop test for vehicle automatic transmission driveline system which only can test control strategies, HIL theory modeling and simulation test research on continuously variable transmission in driver-vehicle-road closed-loop system are carried out relying on the projects of the scientific and technological project of Chongqing《Research and Development of Hardware-in-the-loop Test System for Vehicle Automatic Transmission》and 985 platform national key laboratory open funds《Hardware-in-the-loop Simulation Platform Research on Automatic Transmission》in this paper. The main research work as follows:
(1) In view of driving manipulation qualification which current driver models can not embody out, following running error minimum and physical ability-to-pay minimum principle, fuzzy PID scale factor and quantization factor is off-line optimized adopted with genetic algorithms, then direction fuzzy PID based on genetic algorithms and speed fuzzy integrated control virtual driver simulation model is established; the model is simulated and analyzed under typical mode such as longitudinal speed one-way variation and lateral double lane and big curvature test road, and then compared with traditional PID and fuzzy PID control methods; finally, identification system are regulated adopted with fuzzy deduce method by determining the expressing features of different driver styles and different driver intentions.
(2) Based on 15 degrees of freedom (DOF) vehicle dynamics model, considering road characteristic parameters influence such as lateral gradient, longitudinal gradient and synthetic gradient, the vehicle dynamics model and tire vertical load variation model are established, then virtual vehicle dynamic simulation model is established combined with steering system, braking system, power train system, wheel and suspension models, and analyzed and compared under different lateral, longitudinal, synthetic gradient and vehicle speed; finally the driver-vehicle closed-loop system simulation model is established combined with virtual driver simulation model.
(3) From the requirement of driver-vehicle-road closed-loop system and real-time virtual simulation system, according to the code for design of road and principle for design of road, and consulted with the design of the proving ground of domestic and international, one high fidelity enclosed three-dimension virtual road which is accorded with road design standard and can reflect different driving environment is developed for further researching on ratio self adapted intelligent integrated shift control strategies for continuously variable transmission. Then the driving environment fuzzy identification system is proposed by determining the expressing feature of driving environments including good road section, complicate road section, bumpy road section, upslope road section, downslope road section and curve road section.
(4) Based on dynamic simulation model for continuously variable transmission,τalgorithm, engine torque compensation and engine speed compensation integrated control are proposed by synthetically considering stand-by power, powertrain loss, and CVT ratio change response lag. And then the three integrated control methods are simulated to compare with dynamic and economic performance; Based on CVT optimal dynamic and economy ratio control strategies, CVT ratio control strategies are proposed for different driver styles, different driver intentions and different single driving environment and CVT ratio weight control strategy is proposed for multi-driving environments coupling mode, including turning modified ratio control strategy proposed synthetically considering throttle opening rate, steering wheel steering angle and steering vehicle speed; bumpy road section discretion ratio control strategy proposed synthetically considering throttle opening and vehicle speed micro-variation; upslope modified ratio control strategy proposed synthetically considering throttle opening and longitudinal gradient; downslope modified ratio control strategy synthetically considering downslope initial vehicle speed, longitudinal gradient and downslope length; and CVT ratio self adapted intelligent integrated control strategy for coupling operating mode combined with driver styles, driver intentions and driving environments.
(5) According to driver-vehicle closed-loop system simulation models, self adapted intelligent integrated control model for continuously variable transmission system, and virtual road simulation model developed under VRML, self adapted intelligent integrated control simulation models for continuously variable transmission system in driver-vehicle-road closed-loop system are established based on simulink and VR co_simulation platform by developing virtual proving ground with VR toolbox, then CVT ratio control strategies are simulated and analyzed under different driver styles, driver intentions and single driving environment modes, and CVT ratio self adapted intelligent integrated control models are simulated and analyzed under the coupling operating modes combined with driver styles, driver intentions and driving environments to validate the feasibility and accuracy of the control strategies.
(6) Based on Matlab/Simulink and dSPACE RTI co_simulation platform, hardware-in-the-loop test system for continuously variable transmission is developed, including overall planning design, device purchase, components design and processing and manufacturing, signal collecting and processing, hardware design and software design. By utilizing the test system, and according to firstly bench performance test results, further the CVT ratio control test for different driver intentions, upslope, downslope, curve road and bumpy road section are carried out, then CVT ratio self adapted intelligent integrated control test is carried out for coupling operating modes to validate the availabilty of control strategies.
针对目前汽车自动变速系统硬件在环测试只能进行控制策略测试的局限性,本文结合重庆市科技攻关项目《汽车自动变速器硬件在环试验系统的研制开发》和985平台国家重点实验室开放基金《自动变速器硬件在环仿真平台研究》进行了基于人-车-路闭环的无级自动变速器硬件在环理论建模与仿真试验研究。具体工作内容如下:
(1)针对当前驾驶员模型无法体现驾驶操纵熟练程度的缺点,遵循行驶误差最小与体力负担最小原则,采用遗传算法对模糊PID比例因子和量化因子进行离线优化设计,建立基于遗传算法优化的方向模糊PID与速度模糊综合控制的虚拟驾驶模拟模型,并在纵向速度单向变化、侧向双移线工况与大曲率试验道路典型工况下进行仿真分析,同时将遗传算法优化的模糊PID控制方法与传统PID以及模糊PID进行仿真比较,最后确定不同驾驶类型与不同驾驶意图的表现特征,采用模糊推理方法制定其相应的识别体系。
(2)基于15自由度车辆动力学模型,充分考虑横向坡度、纵向坡度以及合成坡度对车辆动力学与轮胎垂直载荷变化模型的影响,建立横向坡度、纵向坡度与合成坡度车辆动力学与轮胎垂直载荷变化模型,联立转向系、制动系、动力传动系、车轮与悬架模型,构建虚拟车辆动态仿真模型,并进行不同横向、纵向、合成坡度以及车速下进行仿真分析比较,最后联立虚拟驾驶模拟模型,构建人-车闭环系统仿真模型。
(3)从人-车-路闭环系统角度以及实时虚拟仿真系统需求出发,依据公路设计规范与道路设计原理,参考国内外汽车试验场的设计,开发一条符合道路设计标准、逼真度高、且能反映出不同行驶环境的封闭式三维虚拟道路,为进一步研究无级变速系统速比自适应智能综合控制提供前提;并确定包括良好路段、复杂路段、颠簸路段、上坡路段、下坡路段与转弯路段等行驶环境的表现特征,制定相应的行驶环境识别体系。
(4)根据无级变速传动动力学仿真模型,综合考虑后备功率、动力传动系损失以及CVT速比变化响应滞后的影响,制定τ算法、发动机转矩补偿以及发动机转速补偿三种无级变速传动系统综合控制方法,并进行动力性与经济性仿真分析比较;基于CVT最佳动力性与最佳经济性速比控制基础上,制定基于不同驾驶类型、不同驾驶意图、不同单一行驶环境的CVT速比控制策略以及多种行驶环境耦合的CVT速比加权控制策略,其中包括提出综合考虑节气门开度变化率、方向盘转角与转弯车速的转弯修正速比控制策略;综合考虑节气门开度和车速微小变化的颠簸路段离散化速比控制策略;综合考虑节气门开度与纵向坡度的上坡修正速比控制策略;综合考虑下坡初始车速、纵向坡度与下坡坡长的下坡修正速比控制策略;以及不同驾驶类型、驾驶意图与行驶环境耦合工况下的CVT速比自适应智能综合控制策略。
(5)根据人-车闭环系统仿真模型与无级变速系统自适应智能综合控制模型,以及在VRML环境下开发的虚拟道路模拟模型,利用VR工具箱开发虚拟试验场,构建基于Simulink与VR联合仿真平台的人-车-路闭环的无级变速系统自适应智能综合控制仿真模型,并针对不同驾驶类型、不同驾驶意图以及不同单一行驶环境工况下的CVT速比控制仿真分析,以及针对驾驶类型、驾驶意图与行驶环境耦合工况下的CVT速比自适应智能综合控制仿真分析,验证自适应智能综合控制策略可行性与准确性。
(6)基于Matlab/Simulink与dSPACE RTI联合实时仿真环境,自主研制开发无级自动变速器硬件在环仿真试验系统,包括总体方案设计、设备购买、零部件设计加工制造、信号采集与处理,软硬件设计等。基于此试验系统首先进行台架性能测试,根据台架性能测试分析结果,进一步进行基于不同驾驶意图、上坡、下坡、弯道、颠簸路段的CVT速比控制试验,以及耦合工况下的CVT速比自适应智能综合控制试验,从试验角度验证提出的CVT速比控制策略的有效性。
Hardware-in-the-loop (HIL) test system for vehicle automatic transmission driveline system is advanced vehicle automatic transmission driveline test system appeared in recent years, which makes driver, engine, chassis, driving environment and so on simulation model embedded into software environment by utilizing HIL real-time simulation technology combined with hardware and software, for simulating automatic transmission actual operation state, detecting and analyzing the working performance of automotive controller, hydraulic/electrical control system and actuator, then offering a test and development platform for the research and development of automatic transmission automotive.
Against the limitation of current hardware-in-the-loop test for vehicle automatic transmission driveline system which only can test control strategies, HIL theory modeling and simulation test research on continuously variable transmission in driver-vehicle-road closed-loop system are carried out relying on the projects of the scientific and technological project of Chongqing《Research and Development of Hardware-in-the-loop Test System for Vehicle Automatic Transmission》and 985 platform national key laboratory open funds《Hardware-in-the-loop Simulation Platform Research on Automatic Transmission》in this paper. The main research work as follows:
(1) In view of driving manipulation qualification which current driver models can not embody out, following running error minimum and physical ability-to-pay minimum principle, fuzzy PID scale factor and quantization factor is off-line optimized adopted with genetic algorithms, then direction fuzzy PID based on genetic algorithms and speed fuzzy integrated control virtual driver simulation model is established; the model is simulated and analyzed under typical mode such as longitudinal speed one-way variation and lateral double lane and big curvature test road, and then compared with traditional PID and fuzzy PID control methods; finally, identification system are regulated adopted with fuzzy deduce method by determining the expressing features of different driver styles and different driver intentions.
(2) Based on 15 degrees of freedom (DOF) vehicle dynamics model, considering road characteristic parameters influence such as lateral gradient, longitudinal gradient and synthetic gradient, the vehicle dynamics model and tire vertical load variation model are established, then virtual vehicle dynamic simulation model is established combined with steering system, braking system, power train system, wheel and suspension models, and analyzed and compared under different lateral, longitudinal, synthetic gradient and vehicle speed; finally the driver-vehicle closed-loop system simulation model is established combined with virtual driver simulation model.
(3) From the requirement of driver-vehicle-road closed-loop system and real-time virtual simulation system, according to the code for design of road and principle for design of road, and consulted with the design of the proving ground of domestic and international, one high fidelity enclosed three-dimension virtual road which is accorded with road design standard and can reflect different driving environment is developed for further researching on ratio self adapted intelligent integrated shift control strategies for continuously variable transmission. Then the driving environment fuzzy identification system is proposed by determining the expressing feature of driving environments including good road section, complicate road section, bumpy road section, upslope road section, downslope road section and curve road section.
(4) Based on dynamic simulation model for continuously variable transmission,τalgorithm, engine torque compensation and engine speed compensation integrated control are proposed by synthetically considering stand-by power, powertrain loss, and CVT ratio change response lag. And then the three integrated control methods are simulated to compare with dynamic and economic performance; Based on CVT optimal dynamic and economy ratio control strategies, CVT ratio control strategies are proposed for different driver styles, different driver intentions and different single driving environment and CVT ratio weight control strategy is proposed for multi-driving environments coupling mode, including turning modified ratio control strategy proposed synthetically considering throttle opening rate, steering wheel steering angle and steering vehicle speed; bumpy road section discretion ratio control strategy proposed synthetically considering throttle opening and vehicle speed micro-variation; upslope modified ratio control strategy proposed synthetically considering throttle opening and longitudinal gradient; downslope modified ratio control strategy synthetically considering downslope initial vehicle speed, longitudinal gradient and downslope length; and CVT ratio self adapted intelligent integrated control strategy for coupling operating mode combined with driver styles, driver intentions and driving environments.
(5) According to driver-vehicle closed-loop system simulation models, self adapted intelligent integrated control model for continuously variable transmission system, and virtual road simulation model developed under VRML, self adapted intelligent integrated control simulation models for continuously variable transmission system in driver-vehicle-road closed-loop system are established based on simulink and VR co_simulation platform by developing virtual proving ground with VR toolbox, then CVT ratio control strategies are simulated and analyzed under different driver styles, driver intentions and single driving environment modes, and CVT ratio self adapted intelligent integrated control models are simulated and analyzed under the coupling operating modes combined with driver styles, driver intentions and driving environments to validate the feasibility and accuracy of the control strategies.
(6) Based on Matlab/Simulink and dSPACE RTI co_simulation platform, hardware-in-the-loop test system for continuously variable transmission is developed, including overall planning design, device purchase, components design and processing and manufacturing, signal collecting and processing, hardware design and software design. By utilizing the test system, and according to firstly bench performance test results, further the CVT ratio control test for different driver intentions, upslope, downslope, curve road and bumpy road section are carried out, then CVT ratio self adapted intelligent integrated control test is carried out for coupling operating modes to validate the availabilty of control strategies.
引文
[1]范光强.金属带式无级变速器电控单元硬件在环仿真研究[D].镇江:江苏大学, 2009.
[2] dSPACE GmbH, Experiment guide documents for release 4.0. Germany: dSPACE Gnbh. 2003.
[3] dSPACE GmbH, Install and configeration documents for release 4.0. Germany: dSPACE Gnbh. 2003.
[4] dSPACE GmbH, Implementation guide documents for release 4.0. Germany: dSPACE Gnbh. 2003.
[5]张良.基于xPC Target的汽车ESP硬件在环仿真试验台的开发[D].长春:吉林大学, 2009.
[6] Iguchi, M. A study of manual control [J]. Journal of Mechanic Society of Japan, 1962, 1(62): 153-156.
[7] Mcruer, D T. A review of quasi-linear pilot models [J]. IEEE Trans on Human Factors in Electronics, 1967, 8(2): 33-37.
[8] Mcruer, D T. Theory of manual vehicular control [J]. Ergonomics, 1969, 12(4): 16-20.
[9] Kondo M., Ajimine A. Driver’s sight point and dynamics of the driver-vehicle system related to it [C]. SAE technical paper, 680104.
[10]管欣.驾驶员方向控制模型及闭环驾驶安全性预测方法的研究[D].长春:吉林工业大学, 1992.
[11] Sheridan T B. Three models of preview control [J]. IEEE Trans. on Human Factors in Electronics, 1966, 7(2): 187-191.
[12] Macadam, C C. An optimal preview control for linear systems [J]. Journal of Dynamic Systems, Measurement, and Control, ASME, 1980, 102(3): 234-238.
[13] Macadam, C C. Application of an optimal preview control for simulation of closed-loop automobile driving [J]. IEEE Transactions on Systems, Man, and Cybernetics, 1981, 11(9): 574-578.
[14] R N Reddy. Contribution to the simulation of driver-vehicle-road system [C]. SAE technical paper, 810513.
[15] C C Macadam, Gergory E, Johnson. Application of elementary neural networks and preview sensors for representing driver steering control behavior [J]. Vehicle System Dynamics, 1996, 25(7): 3-30.
[16] Kageyama. On a new driver model with fuzzy control [C]. Proceedings of 12th IAVSDSymposium, Lyon, France, 1991.
[17] Charles C Macadam. Understanding and modeling the human driver [J]. Vehicle System Dynamics, 2003, 24(4): 1123-1127.
[18] Kenichi Yoshimoto. Speed control algorithm for an automated driving vehicle [C]. SAE technical paper, 9438619.
[19] R Wade Allen, Raymond E Magdaleno, Colleen Serafin. Driver car following behavior under test track and open road driving condition [C]. NHTSA Technical Report 970170, 1997.
[20] Guo K H. A study of method for modeling closed-loop vehicle directional control [R]. Report in UMTRI, 1982.
[21] Guo K H. Preview-follower method for modeling closed-loop vehicle directional control, symposium of 19th annual conference on manual control [J]. Cambridge Massachusetts, 1983.
[22]郭孔辉.驾驶员-汽车闭环系统操纵运动预瞄最优曲率模型[J].汽车工程, 1984(3): 1-6.
[23]王艺兵,于培人,王占林.驾驶员模型技术发展研究[J].山东纺织工学院学报, 1996, 9(2): 78~84.
[24]李世雄,余群.基于模糊控制的人-车闭路系统的操纵稳定性[J].中国农业大学学报, 1998, 3(4): 108-112.
[25]崔胜民.基于人工神经网络的汽车闭环系统的研究[J].哈尔滨工业大学学报, 2001, 33(1): 54-59.
[26]高振海.汽车方向预瞄式自适应PD控制算法[J].机械工程学报, 2004, 40(5): 101-105.
[27]孟繁杰.速度控制驾驶员建模研究[D].长春:吉林大学, 2007.
[28]王兵.驾驶员对汽车方向的自适应控制行为建模研究[D].长春:吉林大学, 2009.
[29]王景武.汽车自适应巡航的最优预瞄加速度控制算法的研究[D].长春:吉林大学, 2004.
[30] Yoji Seto, Takuya Murakami. Development of a headway distance control system [C]. SAE technical paper, 980616.
[31] R Wade Allen, Raymond E Magdaleno, Colleen Serafin, et al. Driver car following behavior under test track and open road driving condition [R]. NHTSA technical report, 970170.
[32] Kenichi Yoshimoto. Speed control algorithm for an automated driving vehicle [C]. SAE technical paper, 9438619.
[33] Ch. Pressure. A driver model for online control of virtual cars [J]. IEEE, 2001: 1174-1178.
[34]潘峰.人-车闭环系统驾驶员神经网络综合优化建模[D].长春:吉林大学, 2001.
[35] Konghui Guo, Feng Pan, Ying Cheng. Driver model based on the preview optimal artificialneural network [C]. The 6th International Symposium on Advanced Vehicle Control (AVEC’02), 2002.
[36]程颖.基于误差分析法的驾驶员模型及其在ADAMS中的应用[D].长春:吉林大学, 2003.
[37]王汝辉.方向与速度控制驾驶员模型及其误差分析法[D].吉林工业大学, 2004.
[38]万芳.用于汽车操纵稳定性评价的神经网络驾驶员模型[D].长春:吉林大学, 2006.
[39]张立存.汽车驾驶员控制行为统一决策模型的研究[D].长春:吉林大学, 2007.
[40]李英.方向与速度综合控制驾驶员模型及在ADAMS中的应用[D].长春:吉林大学, 2008.
[41] Macadam. Understanding and modeling the human driver [J]. Vehicle System Dynamics, 2003, 3(40): 101-134.
[42] J Juricic, C Reitze. Carmaker Users Guide, 2003.
[43] Bernhard Schick, Birgit Kremer, Josef Henning, et al. Simulation methods to evaluate and verify functions, quality and safety of advanced driver assistance systems [C]. IPG technology conference 2008: 23-24.
[44] Martin Irmscher, Martin Ehmann. Driver classification using ve-DYNA advanced driver [C]. SAE technical paper, 2004-01-0451.
[45] Torsten Butz, Oskar Von Stryk. Optimal control based modeling of vehicle driver properties [C]. SAE technical paper, 2005-01-0420.
[46] Robert J Rieveley, Bruce Minaker, Marc Maurini, et al. Development of an advanced driver model and simulation environment for automotive racing [C]. SAE technical paper, 2009-01-0434.
[47] Segel L. Theoretical prediction and experimental substantiation of the response of the automobile to steering control [J]. The Institute of Mechanical Engineers, 1956.
[48] Milliken W F. General introduction to a program of dynamic research [J]. Proc. IMech. E. Auto. Div, 1956.
[49] Speckhart. A computer simulation for three dimensional vehicle dynamics [C]. SAE technical paper, 730526.
[50] Olley M. Road manners of the modern car [J]. Automobile Engineers, 1976.
[51] D J Segal. Highway vehicle object simulation model [J]. Validation, 1976.
[52] D J Segal. Highway vehicle object simulation model [R]. Programmers Manual, 1976.
[53] D J Segal. Highway vehicle object simulation model [R]. Users Manual, 1976.
[54] Segel L. An overview of developments in road vehicle dynamics: past, present and future [J]. Proceedings of IMech E Conference on Vehicle Ride and Handling, 1993.
[55] Michael W Sayers. A generic multibody vehicle model for simulating handling and braking [J]. Vehicle System Dynamics, 1996(25): 599-613.
[56]李波,刘瑾瑜.农用三轮运输车转向系统参数与行驶稳定性[J].农业机械学报, 1994, 25(1): 27-32.
[57]陈家瑞,林逸,刘明科.键合图理论在汽车振动分析中的应用[J].汽车工程, 1993, 15(1): 26-33.
[58]张智谦,倪建华,张陵.不同路况下车辆悬架系统的动态特性研究[J].机械科学与技术, 2000, 19(1): 32-35.
[59]王国权,余群,吕伟. 8自由度乘坐动力学模型及时域仿真[J].中国农业大学学报, 2002, 7(2): 99-103.
[60]周长峰,孙蓓蓓,孙庆鸿.铰接式自卸车悬架系统动力学建模与仿真[J].汽车技术, 2004(9): 15-18.
[61]徐学进.基于驾驶模拟器的车辆动力学建模研究[D].武汉:武汉理工大学, 2007.
[62]寇发荣.大客车操纵动力学14自由度模型仿真研究[J].西安科技大学学报, 2005, 25(4): 507-510.
[63]张云清,高斯,李凌阳.基于多体力学的车辆动力学控制系统仿真及优化[J].动力学与控制学报, 2007, 5(1): 68-74.
[64]朱浩.基于多体动力学理论的车辆主动悬挂的控制策略研究[D].长沙:中南大学, 2006.
[65]郭孔辉.汽车操纵动力学[M].长春:吉林科学技术出版社, 1991.
[66]林逸.带有非完整约束的汽车多刚体系统动力学研究[D].长春:吉林工业大学, 1989.
[67]上官文斌,黄虎,刘德清.多刚体系统动力学在汽车独立悬架运动分析中的应用[J].汽车工程, 1992, 14(1): 19-31.
[68]张海岑.汽车列车操纵稳定性和制动性模拟计算研究[D].北京:清华大学, 1992.
[69]刘红军.计及弹性体运动的多体力学方法初探及在整车动力学上的应用[D].北京:清华大学, 1994.
[70]陈欣.汽车悬架多柔体系统动力学研究[D].长春:吉林工业大学, 1995.
[71]张越今.多体动力学在轿车动力学仿真及优化研究中的应用[D].北京:清华大学, 1997.
[72] ADSL汽车运动动力学实时仿真模型理论手册[R].长春:吉林工业大学, 1998.
[73]杨得军,林柏忠,管欣.用于开发型驾驶模拟器17自由度汽车动力学仿真的数学模型及算法[J].汽车技术, 2002(12): 6-10.
[74]管欣,张威,林柏忠.车辆实时动态仿真模型的研究[J].江苏大学学报, 2004, 25(3): 203-207.
[75]吴振昕.基于总成结构的汽车动力学实时仿真方法的研究[D].长春:吉林大学, 2007.
[76]王鹏.汽车实时动力学仿真中转向回正特征建模方法研究[D].长春:吉林大学, 2008.
[77] The CARD/1 System [R]. Ingenieurburo Basedow & Tornow Gmbh, 1995.
[78]李斌,张健. RoadCAD 2002在公路设计中的应用[C].中国公路学会计算机应用学会, 2002: 135-139.
[79]乐晓峰,周群强. InRoads的工作流程及在道路设计中的使用[J].公路, 1997(8): 44-49.
[80]王乘,周均清,李利军. Creator可视化仿真建模技术[M].武汉:华中科技大学出版社, 2005.
[81]任耀,秦军. AutoCAD Civil 3D 2008实战教程[M].北京:人民交通出版社, 2008.
[82]付建林. GIS中地形可视化与铁路信息查询的研究[D].成都:西南交通大学, 2002.
[83]王身高.道路集成CAD系统的开发研究[J].公路, 1996(8): 55-59.
[84]房虎.纬地三维道路CAD系统在低等级公路设计中的应用体会[J].广西水利水电, 2008(5): 1-2.
[85]蒋红斐.铁路线路三维可视化设计原理与方法的研究[D].长沙:中南大学, 2001.
[86]唐利民,赵建三.道路地形动态三维可视化及相关属性查询研究[J].长沙交通学院学报, 2005, 21(3): 43-47.
[87]李国华.面向驾驶模拟器的高等级公路三维视景建模[D].昆明:昆明理工大学, 2005.
[88]毕乾坤. AMT换挡特性仿真系统的研究[D].长春:吉林大学, 2004.
[89]贾春萍.轿车CVT无级变速性能可视化仿真系统研究[D].长春:吉林大学, 2006.
[90] CarSim Data manual [R]. Mechanical Simulation Corporation, 2005.
[91] Bernhard Schick, Birgit Kremer, Josef Henning. Simulation methods to evaluate and verify functions, quality and safety of advanced driver assistance systems [J]. IPG Technology Conference, 2008:1-8.
[92] O J Gietelink, D J Verburg, K Labibes. Pre-crash system validation with prescan and VeHIL [J]. 2004 IEEE Intelligent Vehicles Symposium University of Parma, Italy, 2004:913-918.
[93] Osman Aliefendioglu, Ferit Kü?ükay. Real-time statistical-based test environment for transmission control unit of passenger cars [C]. SAE technical paper, 1999-01-1047.
[94] Felipe V Brand?o, David F Kelly, Kevin Fan, et al. Using model, software and hardware-in-loop to develop automated transmission [C]. SAE technical paper, 2007-01-2581.
[95] Kenji hagiwara, satoshi terayama, yohei takeda, et al. The development and utilization of hardware-in-the-loop simulation for the development of an automatic transmission control system [C]. SAE technical paper, 2002-01-1255.
[96] Kenji hagiwara, satoshi terayama, yohei takeda, et al. Development of automatictransmission control system using hardware-in-the-loop simulation system [J]. JSAE Review. 2002, 23(1): 55-59.
[97] Kenji hagiwara, Rei Ito, Ko Yoda, et al. Development of transient state model for CVT-HILS [J]. Honda R&D Technical Review, 2005, 17(1): 65-72.
[98] Lawrence Mianzo. A transmission model for hardware in the loop powertrain control system software development [J]. International Conference on Control Applications, 2000: 1-8.
[99] Toshio Matsumura, Shuji Ichikawa, Fuyuku Katsu, et al. The development of a controller confirmation system for automatic transmissions and its applications [J]. International Conference on Control Applications, 2004: 1415-1419.
[100] Saeawoot Watechagit. Modeling and estimation for stepped automatic transmission with clutch-to-clutch shift technology [D]. Ohio State University, 2004.
[101] Shushan Bai, Robert Moseds. Development of a new clutch-to-clutch shift control technology [J]. SAE technical paper, 2002(1): 315-324.
[102] Joe Steiber, Bapiraju Surampudi, Mike Rosati, et al. Modeling, simulation, and hardware-in-the-loop transmission test system software development [C]. SAE technical paper, 2003-01-0673.
[103] Joe Steiber. Hardware in the loop powertrain component development [R]. http://www.swri.org/4org/d03/vehsys/advveh/avt/hardware.htm.
[104] Joe Steiber, Bapiraju Surampudi, Ben Treichel, et al. Vehicle HIL, the near term solution for optimizing engine and transmission development [C]. SAE technical paper, 2005-01-1050.
[105] Southwest Research Institute. Moving on-road powertrain testing into the test cell [R].2002, www.opal-rt.com.
[106] Steve Hann, Wensi Jin. An automated design synthesis system involving hardware-in-the-loop simulation [R]. http://www.rt-lab.com/files/engineous_2003.ppt.
[107] Jean Bélanger. Next-generation HIL design tools for next-generation vehicles [R]. 2005, http://www.rt-lab.com/files/autovision2010.pps.
[108] Turbett Marlin R, Senseney Robert M, Nash Steven D, et al. Virtual vehicle transmission test cell [P]. United States Patent 6754603.
[109] Quan-Zhong Yan, John M. Williams, Jim Li. Chassis control system development using simulation: software in the loop, rapid prototyping, and hardware in the loop [C]. SAE technical paper, 2002-01-1565.
[110] Quan-Zhong Yan, Frank C. Thompson, Russell E. Paul. Hardware in the loop for dynamic chassis control algorithms test and validation [C]. SAE technical paper, 2004-01-2059.
[111] Quan-Zhong Yan, Faisal Oueslati, Jim Bielenda, et al. Hardware in the loop for a dynamicdriving System controller testing and validation [C]. SAE technical paper, 2005-01-1667.
[112] Peter Waeltermann, Thomas Michalsky, Johannes Held. Hardware-in-the-loop testing in racing applications [C]. SAE technical paper, 2004-01-3502.
[113] In-Gyu Jang, Inkeun Seo, Jaewook Jeon, et al. Testing 32-bit embedded system using hardware-in-the-loop-simulation of automatic transmission [J]. International Conference on Control, Automation and Systems in COEX, Seoul, Korea. 2007: 399-403.
[114] Quan Zheng, Woowon Chung, Ken Defore, et al. A hardware-in-the-loop test bench for production transmission controls software quality validation [C]. SAE technical paper, 2007-01-0502.
[115] Quan Zheng, Asif Habeebullah, Woowon Chung, et al. A 6-speed automatic transmission plant dynamics model for HIL test bench [C]. SAE technical paper, 2008-01-0630.
[116] Won Hyun Oh, Jung Hee Lee, Hyoung Geun Kwon. Model-based development of automotive embedded systems: a case of continuously variable transmission (CVT) [C]. Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’05), 2005.
[117] Fuyuku Katsu, Toshio Matsumura. Practical use of HILS and an approach to MBCSD for AT and CVT development [J]. International Conference on Control Applications Munich, Germany, 2006: 2111-2114.
[118]戚晓霞,邱绪云,崔荣章.富康轿车自动变速器(AT)半实物仿真试验台的设计与应用[J].武汉船舶职业技术学院学报, 2006(6): 17-21.
[119]殷新锋,田晋跃.硬件在环模拟技术在自动变速器控制系统中的应用[J].客车技术与研究, 2007(6): 8-10.
[120]卢新田.轿车自动变速器换挡控制技术的研究[D].上海:同济大学, 2001.
[121]张新荣,黄宗益.自动变速器电子控制单元硬件在环仿真试验[J].长安大学学报, 2005, 25(6): 78-81.
[122]杜宝安.车辆动力传动控制器在环仿真技术应用研究[D].北京:北京理工大学, 2003.
[123]李长文.车辆动力传动系统ECU硬件在环仿真研究[D].北京:北京理工大学, 2004.
[124]李长文,张付军,黄英等.基于dSPACE系统的电控单元硬件在环发动机控制仿真研究[J].兵工学报, 2004, 25(4): 402-406.
[125]江发潮.汽车AMT电控单元虚拟试验系统的研究[D].北京:中国农业大学, 2003.
[126]江发潮,曹正清,迟瑞娟.车辆传动系虚拟试验系统的研究[J].农业机械学报, 2003, 34(1): 14-17.
[127] S W Yang, D Q Zhao. Object-oriented modeling and real-time simulation of planetary gearbox with modelica and simulink [J]. 6th International Symposium on Test andMeasurement (ISTM), 2005: 773-776.
[128]潘良明.自动变速器ECU硬件在环仿真试验台研究与开发[D].上海:同济大学, 2005.
[129]杨伟斌.双离合器式自动变速器电子控制系统关键技术的研究[D].上海:同济大学, 2007.
[130]吴光强,杨伟斌,杨庆.汽车双离合器式自动变速器硬件在环仿真试验台[P]. CN 101140198A.
[131]李淑英.基于LabCar2 AT硬件在环仿真系统开发[D].长春:吉林大学, 2009.
[132]程飞.车辆自动变速器电控单元硬件在环仿真的研究[D].武汉:武汉理工大学, 2007.
[133]徐佳曙.基于硬件在环控制的液力机械自动变速传动系统参数匹配与实验研究[D].重庆:重庆大学, 2005.
[134]伍国强.重型商用车机械自动变速器控制软件开发及试验研究[D].重庆:重庆大学, 2009.
[135]汪斌.无级变速器快速控制原型研究[D].武汉:武汉理工大学, 2005.
[136]胡朝峰.车辆无级变速器实时控制虚拟实验平台的研究[D].武汉:武汉理工大学, 2006.
[137]张付军. MATLAB/Simulink及dSPACE系统在车辆动力装置匹配及控制系统开发中的应用[R].第一届MATLAB & Simulink中国用户大会暨技术论坛,北京, 2005.
[138]王永庭,黄英,张付军.基于硬件在环仿真的变速箱电子控制单元的开发方法[J].兵工学报. 2007, 28(8): 897-902.
[139]李祖元.基于MATLAB等开发AMT软件项目回报[R].第二届MATLAB & Simulink技术论坛,上海, 2006.
[140]付畅.基于dSPACE的车辆液力自动变速器的快速控制原型开发研究[D].武汉:武汉理工大学, 2006.
[141]付畅,过学迅,胡朝峰.金属带式CVT电控单元硬件在环仿真研究[J].汽车工程, 2008, 30(3): 255-259.
[142]吴保玉.金属带式CVT电控系统控制策略研究[D].武汉:武汉理工大学, 2009.
[143]李新城,范光强,朱伟兴.无级变速器电子控制单元硬件在环仿真系统[J].农业机械学报, 2009, 40(7): 6-9.
[144] Sun Xianan, Wu Guangqiang, He Lin, et al. Hardware-in-the-loop simulation for electro-control system of continuously variable transmission based on dSPACE [J]. IEEE Vehicle Power and Propulsion Conference (VPPC), Harbin, China, 2008.
[145]皮秋生. CVT硬件在环仿真试验平台研究[D].长沙:湖南大学, 2008.
[146]周云山,蔡源春,张飞铁. CVT传动系虚拟试验系统研究[J].中国机械工程, 2008, 19(22): 2762-2766.
[147]蔡源春,周云山,张飞铁.基于硬件在环仿真技术的无级变速器试验系统研究[J].仪器仪表学报, 2009, 30(5): 960-965.
[148]颜志鹏.双离合器自动变速器控制系统软件开发[D].重庆:重庆大学, 2009.
[149]赵玉省.双离合器自动变速系统的综合控制[D].重庆:重庆大学, 2009.
[150] Lou Guo-Huan, Wu Hong-Bin. Study of the fuzzy PID control based on genetic algorithm [J]. 2009 Chinese Control and Decision Conference, CCDC2009: 6110-6112.
[151] Hui Liu, Zhou Jianzhong, Wang Shuqing, et al. Application of fuzzy PID control system based on improved GA in hydraulic turbine generating units [J]. Proceeding of the 7th world congress on intelligent control and automation June 25-27, 2008, Chongqing, China: 7790-7794.
[152] K Valarmarhi, D Devaraj, T K Radhakrishnan. A combined genetic algorithm and sugeno fuzzy logic based approach for on-line tuning in ph process [J]. 4th Intelligent Systems International IEEE Conference, 2008: 202-207.
[153]杨永灯,杨晓萍,邱锦东.基于遗传算法的同步发电机自调整模糊PID励磁控制器研究[J].大电机技术, 2007(1): 52-56.
[154]方千山.模糊遗传算法的自适应PID控制器[J].华侨大学学报, 2005, 26(1): 38-42.
[155] Guo K H, Zong C F, Kong F S. Objective evaluation conrrelated with human judgement approach to the optimization of vehicle handling control system [J]. International Journal of Vehicle Design, 2002, 29(1): 96-111.
[156]王兵.驾驶员对汽车方向的自适应控制行为建模研究[D].长春:吉林大学, 2009.
[157]管欣,高振海,郭孔辉.汽车预期轨迹驾驶员模糊决策模型及典型路况仿真[J].汽车工程, 2001, 23(l): 13-17.
[158] Herbert Schuette, Peter Waeltermann. Hardware-in-the-loop testing of vehicle dynamics controllers-a technical survey [C]. SAE technical paper, 2005-01-1660.
[159]张代胜,李华香.弯道和坡道上汽车操纵稳定性建模仿真[J].农业机械学报, 2006, 37 (4): 21-25.
[160]邓涛,孙冬野,秦大同.无级变速传动系统综合控制仿真与试验[J].汽车工程, 2010, 32(1): 49-55.
[161] E Bakker, H B Pacejka, L Lidner. A new tire model with an application in vehicle dynamics studies [C]. SAE technical paper, 890087.
[162]柯军.汽车自动变速器可靠性试验规范的研究[D].上海:上海交通大学, 2007.
[163]周文辉.基于MultiGen Creator的汽车虚拟试验平台仿真研究[D].西安:长安大学, 2008.
[164]交通部第一公路勘察设计院(JTJ011-94).公路路线设计规范[M].北京:人民交通出版社, 1994.
[165]李绪梅.公路几何设计[M].北京:人民交通出版社, 2004.
[166]袁望方.驾驶员道路安全感虚拟现实评价技术研究[D].西安:长安大学, 2006.
[167]赵德银.道路参数获取及其在换档控制中的应用[D].长春:吉林大学, 2009.
[168]程亚飞.公路路线平面设计方法的研究及应用软件的开发[D].南京:中南大学, 2007.
[169]程文娟.公路线形舒适性评价方法研究[D].石家庄:河北工业大学, 2007.
[170] H Weil, G Probst, F Graf. Fuzzy expert system for automatic transmission control [J]. IEEE, 1992: 716-722.
[171] S Sakaguchi, I Sakai, T Haga. Application of fuzzy logic to shift scheduling method for automatic transmission [J]. IEEE, 1993: 52-58.
[172] Qin Guihe, Ge Anlin, Lee Jujang. Knowledge based gear position decision [J]. IEEE Transactions on Intelligent Transportation Systems, 2004, 5(2): 121-126.
[173] J Yi, Wang X L, Hu Y J. Modelling and simulation of a fuzzy controller of automatic transmission of a tracked vehicle in complicated driving conditions [J]. Proc. IMechE Vol.221 Part D: Automobile Engineering, 2007: 1259-1272.
[174] B Mashadi, A Kazemkhani, R Lakeh. An automatic gear shifting strategy for manual transmissions [J]. Proc. IMechE Vol.221 Part I: Systems and Control Engineering, 2007: 757-768.
[175]葛安林,金辉,张洪坤.一种汽车智能换挡体系的研究[J].中国机械工程, 2001, 12(5): 585-588.
[176]卢新田.轿车自动变速器换档控制技术的研究[D].上海:同济大学, 2001.
[177]彭瑞.汽车自动变速器电子控制单元的研究与实现[D].上海:同济大学, 2003.
[178]史维刚.汽车智能换挡系统的研究[D].长春:吉林大学, 2003.
[179]智国平.基于动力传动系统联合控制的装载机自动换挡系统开发[D],长春:吉林大学, 2004.
[180]鲁民巧.自动变速器智能换档控制的研究[D].哈尔滨:哈尔滨工业大学, 2004.
[181]张宏坤.电控液力自动变速器换档控制技术的研究[D].大连:大连理工大学, 2005.
[182]刘振军.基于人-车-路环境下的汽车电控机械自动变速智能控制研究[D].重庆:重庆大学, 2005.
[183]雷晓东.电控机械自动变速系统换档控制策略研究[D].重庆:重庆大学, 2005.
[184]何涛.自动变速器换档控制技术的研究[D].北京:北京林业大学, 2005.
[185]朱小佩.轿车自动变速器换档规律的研究与仿真[D].上海:同济大学, 2006.
[186]马威.基于模糊控制理论的履带车辆自动换挡规律研究[D].武汉:华中科技大学, 2007.
[187]江立飞.客车自动换档原理研究及操控系统开发[D].大连:大连理工大学, 2007.
[188]邸林峰.自动变速智能换档控制技术的研究[D].沈阳:东北大学, 2007.
[189]何晓鹏.车辆自动换档规律的研究[D].石家庄:河北工业大学, 2007.
[190]孔慧芳.电控机械式自动变速器中传动与控制的关键技术研究[D].合肥:合肥工业大学, 2008.
[191]张金香.液力机械自动变速器的研究[D].兰州:兰州理工大学, 2009.
[192]周国清.混合动力大客车换挡决策研究[D].上海:上海交通大学, 2009.
[193]牛炳. AMT换挡规律及其自适应性研究[D].上海:上海交通大学, 2009.
[194]孙冬野,秦大同.基于人-车-路环境下汽车无级自动变速传动的智能控制[J].中国机械工程, 2005, 16(4): 357-360.
[195] Masayuki Yasuoka, Masaaki Uchida, Shusaku Katakura, et al. An integrated control algorithm for an SI engine and a CVT [C]. SAE technical paper. 1999-01-0752.
[196] T Kim, H Kim. Performance of integrated engine-CVT control considering powertrain loss and CVT response lag [J]. IMechE, 2002(216): 545-553.
[197] Heera Lee, Chulsoo Kim, Talchol Kim, et al. CVT ratio control algorithm by considering powertrain response lag [C]. SAE technical paper, 2004-01-1636.
[198] H Lee, H Kim. Improvement in fuel economy for a parallel hybrid electric vehicle by continuously variable transmission ratio control [J]. Drive System Technique, 2006, 20(3): 29-36.
[199] Wang Hongyan, Zhou Yunshan, Zhang Boying, et al. Research on integrated control strategy of CVT for passenger cars [C]. IVEC’1999: 401-405.
[200] Xie Xianping, Wang Xudong, Zhou Meilan. Study on integrated control strategy and simulation analysis of automotive with CVT [J]. ICEMT’2005: 365-369.
[201]孙冬野,秦大同.液力变矩器-机械无级变速器自动变速汽车综合控制策略研究[J].机械工程学报, 2003, 39(2): 102-105.
[202]何仁,马承广,张涌.基于驾驶意图的无级变速器目标速比确定方法[J].农业机械学报, 2009, 40(5): 16-19.
[203]孙冬野,秦大同,刘振军.汽车无级变速传动系统离散化的速比控制策略[J].江苏大学学报, 2009, 30(4): 352-356.
[204]宁凡坤.基于VR的汽车虚拟试验系统研究[D].成都:西华大学, 2006.
[205]徐延海,宁凡坤.用于汽车操纵稳定性模拟的虚拟现实平台的研究[J].系统仿真学报, 2007, 19(17): 3984-3987.
[206]张家祥,方凌江,毛全胜.基于MATLAB 6.x的系统分析与设计[M].西安:西安电子科技大学出版社, 2004.
[207]尹念东.汽车-驾驶员-环境闭环系统操纵稳定性虚拟试验技术的研究[D].北京:中国农业大学, 2001.
[208]王凯峰.基于虚拟现实与虚拟样机的汽车操纵稳定性研究[D].合肥:合肥工业大学, 2007.
[209]张勇.基于Simulink的机器人虚拟现实仿真研究[D].哈尔滨:哈尔滨工业大学, 2007.
[210]魏青.轻型电子机械制动汽车牵引力控制及虚拟仿真方法研究[D].长春:吉林大学, 2008.
[2] dSPACE GmbH, Experiment guide documents for release 4.0. Germany: dSPACE Gnbh. 2003.
[3] dSPACE GmbH, Install and configeration documents for release 4.0. Germany: dSPACE Gnbh. 2003.
[4] dSPACE GmbH, Implementation guide documents for release 4.0. Germany: dSPACE Gnbh. 2003.
[5]张良.基于xPC Target的汽车ESP硬件在环仿真试验台的开发[D].长春:吉林大学, 2009.
[6] Iguchi, M. A study of manual control [J]. Journal of Mechanic Society of Japan, 1962, 1(62): 153-156.
[7] Mcruer, D T. A review of quasi-linear pilot models [J]. IEEE Trans on Human Factors in Electronics, 1967, 8(2): 33-37.
[8] Mcruer, D T. Theory of manual vehicular control [J]. Ergonomics, 1969, 12(4): 16-20.
[9] Kondo M., Ajimine A. Driver’s sight point and dynamics of the driver-vehicle system related to it [C]. SAE technical paper, 680104.
[10]管欣.驾驶员方向控制模型及闭环驾驶安全性预测方法的研究[D].长春:吉林工业大学, 1992.
[11] Sheridan T B. Three models of preview control [J]. IEEE Trans. on Human Factors in Electronics, 1966, 7(2): 187-191.
[12] Macadam, C C. An optimal preview control for linear systems [J]. Journal of Dynamic Systems, Measurement, and Control, ASME, 1980, 102(3): 234-238.
[13] Macadam, C C. Application of an optimal preview control for simulation of closed-loop automobile driving [J]. IEEE Transactions on Systems, Man, and Cybernetics, 1981, 11(9): 574-578.
[14] R N Reddy. Contribution to the simulation of driver-vehicle-road system [C]. SAE technical paper, 810513.
[15] C C Macadam, Gergory E, Johnson. Application of elementary neural networks and preview sensors for representing driver steering control behavior [J]. Vehicle System Dynamics, 1996, 25(7): 3-30.
[16] Kageyama. On a new driver model with fuzzy control [C]. Proceedings of 12th IAVSDSymposium, Lyon, France, 1991.
[17] Charles C Macadam. Understanding and modeling the human driver [J]. Vehicle System Dynamics, 2003, 24(4): 1123-1127.
[18] Kenichi Yoshimoto. Speed control algorithm for an automated driving vehicle [C]. SAE technical paper, 9438619.
[19] R Wade Allen, Raymond E Magdaleno, Colleen Serafin. Driver car following behavior under test track and open road driving condition [C]. NHTSA Technical Report 970170, 1997.
[20] Guo K H. A study of method for modeling closed-loop vehicle directional control [R]. Report in UMTRI, 1982.
[21] Guo K H. Preview-follower method for modeling closed-loop vehicle directional control, symposium of 19th annual conference on manual control [J]. Cambridge Massachusetts, 1983.
[22]郭孔辉.驾驶员-汽车闭环系统操纵运动预瞄最优曲率模型[J].汽车工程, 1984(3): 1-6.
[23]王艺兵,于培人,王占林.驾驶员模型技术发展研究[J].山东纺织工学院学报, 1996, 9(2): 78~84.
[24]李世雄,余群.基于模糊控制的人-车闭路系统的操纵稳定性[J].中国农业大学学报, 1998, 3(4): 108-112.
[25]崔胜民.基于人工神经网络的汽车闭环系统的研究[J].哈尔滨工业大学学报, 2001, 33(1): 54-59.
[26]高振海.汽车方向预瞄式自适应PD控制算法[J].机械工程学报, 2004, 40(5): 101-105.
[27]孟繁杰.速度控制驾驶员建模研究[D].长春:吉林大学, 2007.
[28]王兵.驾驶员对汽车方向的自适应控制行为建模研究[D].长春:吉林大学, 2009.
[29]王景武.汽车自适应巡航的最优预瞄加速度控制算法的研究[D].长春:吉林大学, 2004.
[30] Yoji Seto, Takuya Murakami. Development of a headway distance control system [C]. SAE technical paper, 980616.
[31] R Wade Allen, Raymond E Magdaleno, Colleen Serafin, et al. Driver car following behavior under test track and open road driving condition [R]. NHTSA technical report, 970170.
[32] Kenichi Yoshimoto. Speed control algorithm for an automated driving vehicle [C]. SAE technical paper, 9438619.
[33] Ch. Pressure. A driver model for online control of virtual cars [J]. IEEE, 2001: 1174-1178.
[34]潘峰.人-车闭环系统驾驶员神经网络综合优化建模[D].长春:吉林大学, 2001.
[35] Konghui Guo, Feng Pan, Ying Cheng. Driver model based on the preview optimal artificialneural network [C]. The 6th International Symposium on Advanced Vehicle Control (AVEC’02), 2002.
[36]程颖.基于误差分析法的驾驶员模型及其在ADAMS中的应用[D].长春:吉林大学, 2003.
[37]王汝辉.方向与速度控制驾驶员模型及其误差分析法[D].吉林工业大学, 2004.
[38]万芳.用于汽车操纵稳定性评价的神经网络驾驶员模型[D].长春:吉林大学, 2006.
[39]张立存.汽车驾驶员控制行为统一决策模型的研究[D].长春:吉林大学, 2007.
[40]李英.方向与速度综合控制驾驶员模型及在ADAMS中的应用[D].长春:吉林大学, 2008.
[41] Macadam. Understanding and modeling the human driver [J]. Vehicle System Dynamics, 2003, 3(40): 101-134.
[42] J Juricic, C Reitze. Carmaker Users Guide, 2003.
[43] Bernhard Schick, Birgit Kremer, Josef Henning, et al. Simulation methods to evaluate and verify functions, quality and safety of advanced driver assistance systems [C]. IPG technology conference 2008: 23-24.
[44] Martin Irmscher, Martin Ehmann. Driver classification using ve-DYNA advanced driver [C]. SAE technical paper, 2004-01-0451.
[45] Torsten Butz, Oskar Von Stryk. Optimal control based modeling of vehicle driver properties [C]. SAE technical paper, 2005-01-0420.
[46] Robert J Rieveley, Bruce Minaker, Marc Maurini, et al. Development of an advanced driver model and simulation environment for automotive racing [C]. SAE technical paper, 2009-01-0434.
[47] Segel L. Theoretical prediction and experimental substantiation of the response of the automobile to steering control [J]. The Institute of Mechanical Engineers, 1956.
[48] Milliken W F. General introduction to a program of dynamic research [J]. Proc. IMech. E. Auto. Div, 1956.
[49] Speckhart. A computer simulation for three dimensional vehicle dynamics [C]. SAE technical paper, 730526.
[50] Olley M. Road manners of the modern car [J]. Automobile Engineers, 1976.
[51] D J Segal. Highway vehicle object simulation model [J]. Validation, 1976.
[52] D J Segal. Highway vehicle object simulation model [R]. Programmers Manual, 1976.
[53] D J Segal. Highway vehicle object simulation model [R]. Users Manual, 1976.
[54] Segel L. An overview of developments in road vehicle dynamics: past, present and future [J]. Proceedings of IMech E Conference on Vehicle Ride and Handling, 1993.
[55] Michael W Sayers. A generic multibody vehicle model for simulating handling and braking [J]. Vehicle System Dynamics, 1996(25): 599-613.
[56]李波,刘瑾瑜.农用三轮运输车转向系统参数与行驶稳定性[J].农业机械学报, 1994, 25(1): 27-32.
[57]陈家瑞,林逸,刘明科.键合图理论在汽车振动分析中的应用[J].汽车工程, 1993, 15(1): 26-33.
[58]张智谦,倪建华,张陵.不同路况下车辆悬架系统的动态特性研究[J].机械科学与技术, 2000, 19(1): 32-35.
[59]王国权,余群,吕伟. 8自由度乘坐动力学模型及时域仿真[J].中国农业大学学报, 2002, 7(2): 99-103.
[60]周长峰,孙蓓蓓,孙庆鸿.铰接式自卸车悬架系统动力学建模与仿真[J].汽车技术, 2004(9): 15-18.
[61]徐学进.基于驾驶模拟器的车辆动力学建模研究[D].武汉:武汉理工大学, 2007.
[62]寇发荣.大客车操纵动力学14自由度模型仿真研究[J].西安科技大学学报, 2005, 25(4): 507-510.
[63]张云清,高斯,李凌阳.基于多体力学的车辆动力学控制系统仿真及优化[J].动力学与控制学报, 2007, 5(1): 68-74.
[64]朱浩.基于多体动力学理论的车辆主动悬挂的控制策略研究[D].长沙:中南大学, 2006.
[65]郭孔辉.汽车操纵动力学[M].长春:吉林科学技术出版社, 1991.
[66]林逸.带有非完整约束的汽车多刚体系统动力学研究[D].长春:吉林工业大学, 1989.
[67]上官文斌,黄虎,刘德清.多刚体系统动力学在汽车独立悬架运动分析中的应用[J].汽车工程, 1992, 14(1): 19-31.
[68]张海岑.汽车列车操纵稳定性和制动性模拟计算研究[D].北京:清华大学, 1992.
[69]刘红军.计及弹性体运动的多体力学方法初探及在整车动力学上的应用[D].北京:清华大学, 1994.
[70]陈欣.汽车悬架多柔体系统动力学研究[D].长春:吉林工业大学, 1995.
[71]张越今.多体动力学在轿车动力学仿真及优化研究中的应用[D].北京:清华大学, 1997.
[72] ADSL汽车运动动力学实时仿真模型理论手册[R].长春:吉林工业大学, 1998.
[73]杨得军,林柏忠,管欣.用于开发型驾驶模拟器17自由度汽车动力学仿真的数学模型及算法[J].汽车技术, 2002(12): 6-10.
[74]管欣,张威,林柏忠.车辆实时动态仿真模型的研究[J].江苏大学学报, 2004, 25(3): 203-207.
[75]吴振昕.基于总成结构的汽车动力学实时仿真方法的研究[D].长春:吉林大学, 2007.
[76]王鹏.汽车实时动力学仿真中转向回正特征建模方法研究[D].长春:吉林大学, 2008.
[77] The CARD/1 System [R]. Ingenieurburo Basedow & Tornow Gmbh, 1995.
[78]李斌,张健. RoadCAD 2002在公路设计中的应用[C].中国公路学会计算机应用学会, 2002: 135-139.
[79]乐晓峰,周群强. InRoads的工作流程及在道路设计中的使用[J].公路, 1997(8): 44-49.
[80]王乘,周均清,李利军. Creator可视化仿真建模技术[M].武汉:华中科技大学出版社, 2005.
[81]任耀,秦军. AutoCAD Civil 3D 2008实战教程[M].北京:人民交通出版社, 2008.
[82]付建林. GIS中地形可视化与铁路信息查询的研究[D].成都:西南交通大学, 2002.
[83]王身高.道路集成CAD系统的开发研究[J].公路, 1996(8): 55-59.
[84]房虎.纬地三维道路CAD系统在低等级公路设计中的应用体会[J].广西水利水电, 2008(5): 1-2.
[85]蒋红斐.铁路线路三维可视化设计原理与方法的研究[D].长沙:中南大学, 2001.
[86]唐利民,赵建三.道路地形动态三维可视化及相关属性查询研究[J].长沙交通学院学报, 2005, 21(3): 43-47.
[87]李国华.面向驾驶模拟器的高等级公路三维视景建模[D].昆明:昆明理工大学, 2005.
[88]毕乾坤. AMT换挡特性仿真系统的研究[D].长春:吉林大学, 2004.
[89]贾春萍.轿车CVT无级变速性能可视化仿真系统研究[D].长春:吉林大学, 2006.
[90] CarSim Data manual [R]. Mechanical Simulation Corporation, 2005.
[91] Bernhard Schick, Birgit Kremer, Josef Henning. Simulation methods to evaluate and verify functions, quality and safety of advanced driver assistance systems [J]. IPG Technology Conference, 2008:1-8.
[92] O J Gietelink, D J Verburg, K Labibes. Pre-crash system validation with prescan and VeHIL [J]. 2004 IEEE Intelligent Vehicles Symposium University of Parma, Italy, 2004:913-918.
[93] Osman Aliefendioglu, Ferit Kü?ükay. Real-time statistical-based test environment for transmission control unit of passenger cars [C]. SAE technical paper, 1999-01-1047.
[94] Felipe V Brand?o, David F Kelly, Kevin Fan, et al. Using model, software and hardware-in-loop to develop automated transmission [C]. SAE technical paper, 2007-01-2581.
[95] Kenji hagiwara, satoshi terayama, yohei takeda, et al. The development and utilization of hardware-in-the-loop simulation for the development of an automatic transmission control system [C]. SAE technical paper, 2002-01-1255.
[96] Kenji hagiwara, satoshi terayama, yohei takeda, et al. Development of automatictransmission control system using hardware-in-the-loop simulation system [J]. JSAE Review. 2002, 23(1): 55-59.
[97] Kenji hagiwara, Rei Ito, Ko Yoda, et al. Development of transient state model for CVT-HILS [J]. Honda R&D Technical Review, 2005, 17(1): 65-72.
[98] Lawrence Mianzo. A transmission model for hardware in the loop powertrain control system software development [J]. International Conference on Control Applications, 2000: 1-8.
[99] Toshio Matsumura, Shuji Ichikawa, Fuyuku Katsu, et al. The development of a controller confirmation system for automatic transmissions and its applications [J]. International Conference on Control Applications, 2004: 1415-1419.
[100] Saeawoot Watechagit. Modeling and estimation for stepped automatic transmission with clutch-to-clutch shift technology [D]. Ohio State University, 2004.
[101] Shushan Bai, Robert Moseds. Development of a new clutch-to-clutch shift control technology [J]. SAE technical paper, 2002(1): 315-324.
[102] Joe Steiber, Bapiraju Surampudi, Mike Rosati, et al. Modeling, simulation, and hardware-in-the-loop transmission test system software development [C]. SAE technical paper, 2003-01-0673.
[103] Joe Steiber. Hardware in the loop powertrain component development [R]. http://www.swri.org/4org/d03/vehsys/advveh/avt/hardware.htm.
[104] Joe Steiber, Bapiraju Surampudi, Ben Treichel, et al. Vehicle HIL, the near term solution for optimizing engine and transmission development [C]. SAE technical paper, 2005-01-1050.
[105] Southwest Research Institute. Moving on-road powertrain testing into the test cell [R].2002, www.opal-rt.com.
[106] Steve Hann, Wensi Jin. An automated design synthesis system involving hardware-in-the-loop simulation [R]. http://www.rt-lab.com/files/engineous_2003.ppt.
[107] Jean Bélanger. Next-generation HIL design tools for next-generation vehicles [R]. 2005, http://www.rt-lab.com/files/autovision2010.pps.
[108] Turbett Marlin R, Senseney Robert M, Nash Steven D, et al. Virtual vehicle transmission test cell [P]. United States Patent 6754603.
[109] Quan-Zhong Yan, John M. Williams, Jim Li. Chassis control system development using simulation: software in the loop, rapid prototyping, and hardware in the loop [C]. SAE technical paper, 2002-01-1565.
[110] Quan-Zhong Yan, Frank C. Thompson, Russell E. Paul. Hardware in the loop for dynamic chassis control algorithms test and validation [C]. SAE technical paper, 2004-01-2059.
[111] Quan-Zhong Yan, Faisal Oueslati, Jim Bielenda, et al. Hardware in the loop for a dynamicdriving System controller testing and validation [C]. SAE technical paper, 2005-01-1667.
[112] Peter Waeltermann, Thomas Michalsky, Johannes Held. Hardware-in-the-loop testing in racing applications [C]. SAE technical paper, 2004-01-3502.
[113] In-Gyu Jang, Inkeun Seo, Jaewook Jeon, et al. Testing 32-bit embedded system using hardware-in-the-loop-simulation of automatic transmission [J]. International Conference on Control, Automation and Systems in COEX, Seoul, Korea. 2007: 399-403.
[114] Quan Zheng, Woowon Chung, Ken Defore, et al. A hardware-in-the-loop test bench for production transmission controls software quality validation [C]. SAE technical paper, 2007-01-0502.
[115] Quan Zheng, Asif Habeebullah, Woowon Chung, et al. A 6-speed automatic transmission plant dynamics model for HIL test bench [C]. SAE technical paper, 2008-01-0630.
[116] Won Hyun Oh, Jung Hee Lee, Hyoung Geun Kwon. Model-based development of automotive embedded systems: a case of continuously variable transmission (CVT) [C]. Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’05), 2005.
[117] Fuyuku Katsu, Toshio Matsumura. Practical use of HILS and an approach to MBCSD for AT and CVT development [J]. International Conference on Control Applications Munich, Germany, 2006: 2111-2114.
[118]戚晓霞,邱绪云,崔荣章.富康轿车自动变速器(AT)半实物仿真试验台的设计与应用[J].武汉船舶职业技术学院学报, 2006(6): 17-21.
[119]殷新锋,田晋跃.硬件在环模拟技术在自动变速器控制系统中的应用[J].客车技术与研究, 2007(6): 8-10.
[120]卢新田.轿车自动变速器换挡控制技术的研究[D].上海:同济大学, 2001.
[121]张新荣,黄宗益.自动变速器电子控制单元硬件在环仿真试验[J].长安大学学报, 2005, 25(6): 78-81.
[122]杜宝安.车辆动力传动控制器在环仿真技术应用研究[D].北京:北京理工大学, 2003.
[123]李长文.车辆动力传动系统ECU硬件在环仿真研究[D].北京:北京理工大学, 2004.
[124]李长文,张付军,黄英等.基于dSPACE系统的电控单元硬件在环发动机控制仿真研究[J].兵工学报, 2004, 25(4): 402-406.
[125]江发潮.汽车AMT电控单元虚拟试验系统的研究[D].北京:中国农业大学, 2003.
[126]江发潮,曹正清,迟瑞娟.车辆传动系虚拟试验系统的研究[J].农业机械学报, 2003, 34(1): 14-17.
[127] S W Yang, D Q Zhao. Object-oriented modeling and real-time simulation of planetary gearbox with modelica and simulink [J]. 6th International Symposium on Test andMeasurement (ISTM), 2005: 773-776.
[128]潘良明.自动变速器ECU硬件在环仿真试验台研究与开发[D].上海:同济大学, 2005.
[129]杨伟斌.双离合器式自动变速器电子控制系统关键技术的研究[D].上海:同济大学, 2007.
[130]吴光强,杨伟斌,杨庆.汽车双离合器式自动变速器硬件在环仿真试验台[P]. CN 101140198A.
[131]李淑英.基于LabCar2 AT硬件在环仿真系统开发[D].长春:吉林大学, 2009.
[132]程飞.车辆自动变速器电控单元硬件在环仿真的研究[D].武汉:武汉理工大学, 2007.
[133]徐佳曙.基于硬件在环控制的液力机械自动变速传动系统参数匹配与实验研究[D].重庆:重庆大学, 2005.
[134]伍国强.重型商用车机械自动变速器控制软件开发及试验研究[D].重庆:重庆大学, 2009.
[135]汪斌.无级变速器快速控制原型研究[D].武汉:武汉理工大学, 2005.
[136]胡朝峰.车辆无级变速器实时控制虚拟实验平台的研究[D].武汉:武汉理工大学, 2006.
[137]张付军. MATLAB/Simulink及dSPACE系统在车辆动力装置匹配及控制系统开发中的应用[R].第一届MATLAB & Simulink中国用户大会暨技术论坛,北京, 2005.
[138]王永庭,黄英,张付军.基于硬件在环仿真的变速箱电子控制单元的开发方法[J].兵工学报. 2007, 28(8): 897-902.
[139]李祖元.基于MATLAB等开发AMT软件项目回报[R].第二届MATLAB & Simulink技术论坛,上海, 2006.
[140]付畅.基于dSPACE的车辆液力自动变速器的快速控制原型开发研究[D].武汉:武汉理工大学, 2006.
[141]付畅,过学迅,胡朝峰.金属带式CVT电控单元硬件在环仿真研究[J].汽车工程, 2008, 30(3): 255-259.
[142]吴保玉.金属带式CVT电控系统控制策略研究[D].武汉:武汉理工大学, 2009.
[143]李新城,范光强,朱伟兴.无级变速器电子控制单元硬件在环仿真系统[J].农业机械学报, 2009, 40(7): 6-9.
[144] Sun Xianan, Wu Guangqiang, He Lin, et al. Hardware-in-the-loop simulation for electro-control system of continuously variable transmission based on dSPACE [J]. IEEE Vehicle Power and Propulsion Conference (VPPC), Harbin, China, 2008.
[145]皮秋生. CVT硬件在环仿真试验平台研究[D].长沙:湖南大学, 2008.
[146]周云山,蔡源春,张飞铁. CVT传动系虚拟试验系统研究[J].中国机械工程, 2008, 19(22): 2762-2766.
[147]蔡源春,周云山,张飞铁.基于硬件在环仿真技术的无级变速器试验系统研究[J].仪器仪表学报, 2009, 30(5): 960-965.
[148]颜志鹏.双离合器自动变速器控制系统软件开发[D].重庆:重庆大学, 2009.
[149]赵玉省.双离合器自动变速系统的综合控制[D].重庆:重庆大学, 2009.
[150] Lou Guo-Huan, Wu Hong-Bin. Study of the fuzzy PID control based on genetic algorithm [J]. 2009 Chinese Control and Decision Conference, CCDC2009: 6110-6112.
[151] Hui Liu, Zhou Jianzhong, Wang Shuqing, et al. Application of fuzzy PID control system based on improved GA in hydraulic turbine generating units [J]. Proceeding of the 7th world congress on intelligent control and automation June 25-27, 2008, Chongqing, China: 7790-7794.
[152] K Valarmarhi, D Devaraj, T K Radhakrishnan. A combined genetic algorithm and sugeno fuzzy logic based approach for on-line tuning in ph process [J]. 4th Intelligent Systems International IEEE Conference, 2008: 202-207.
[153]杨永灯,杨晓萍,邱锦东.基于遗传算法的同步发电机自调整模糊PID励磁控制器研究[J].大电机技术, 2007(1): 52-56.
[154]方千山.模糊遗传算法的自适应PID控制器[J].华侨大学学报, 2005, 26(1): 38-42.
[155] Guo K H, Zong C F, Kong F S. Objective evaluation conrrelated with human judgement approach to the optimization of vehicle handling control system [J]. International Journal of Vehicle Design, 2002, 29(1): 96-111.
[156]王兵.驾驶员对汽车方向的自适应控制行为建模研究[D].长春:吉林大学, 2009.
[157]管欣,高振海,郭孔辉.汽车预期轨迹驾驶员模糊决策模型及典型路况仿真[J].汽车工程, 2001, 23(l): 13-17.
[158] Herbert Schuette, Peter Waeltermann. Hardware-in-the-loop testing of vehicle dynamics controllers-a technical survey [C]. SAE technical paper, 2005-01-1660.
[159]张代胜,李华香.弯道和坡道上汽车操纵稳定性建模仿真[J].农业机械学报, 2006, 37 (4): 21-25.
[160]邓涛,孙冬野,秦大同.无级变速传动系统综合控制仿真与试验[J].汽车工程, 2010, 32(1): 49-55.
[161] E Bakker, H B Pacejka, L Lidner. A new tire model with an application in vehicle dynamics studies [C]. SAE technical paper, 890087.
[162]柯军.汽车自动变速器可靠性试验规范的研究[D].上海:上海交通大学, 2007.
[163]周文辉.基于MultiGen Creator的汽车虚拟试验平台仿真研究[D].西安:长安大学, 2008.
[164]交通部第一公路勘察设计院(JTJ011-94).公路路线设计规范[M].北京:人民交通出版社, 1994.
[165]李绪梅.公路几何设计[M].北京:人民交通出版社, 2004.
[166]袁望方.驾驶员道路安全感虚拟现实评价技术研究[D].西安:长安大学, 2006.
[167]赵德银.道路参数获取及其在换档控制中的应用[D].长春:吉林大学, 2009.
[168]程亚飞.公路路线平面设计方法的研究及应用软件的开发[D].南京:中南大学, 2007.
[169]程文娟.公路线形舒适性评价方法研究[D].石家庄:河北工业大学, 2007.
[170] H Weil, G Probst, F Graf. Fuzzy expert system for automatic transmission control [J]. IEEE, 1992: 716-722.
[171] S Sakaguchi, I Sakai, T Haga. Application of fuzzy logic to shift scheduling method for automatic transmission [J]. IEEE, 1993: 52-58.
[172] Qin Guihe, Ge Anlin, Lee Jujang. Knowledge based gear position decision [J]. IEEE Transactions on Intelligent Transportation Systems, 2004, 5(2): 121-126.
[173] J Yi, Wang X L, Hu Y J. Modelling and simulation of a fuzzy controller of automatic transmission of a tracked vehicle in complicated driving conditions [J]. Proc. IMechE Vol.221 Part D: Automobile Engineering, 2007: 1259-1272.
[174] B Mashadi, A Kazemkhani, R Lakeh. An automatic gear shifting strategy for manual transmissions [J]. Proc. IMechE Vol.221 Part I: Systems and Control Engineering, 2007: 757-768.
[175]葛安林,金辉,张洪坤.一种汽车智能换挡体系的研究[J].中国机械工程, 2001, 12(5): 585-588.
[176]卢新田.轿车自动变速器换档控制技术的研究[D].上海:同济大学, 2001.
[177]彭瑞.汽车自动变速器电子控制单元的研究与实现[D].上海:同济大学, 2003.
[178]史维刚.汽车智能换挡系统的研究[D].长春:吉林大学, 2003.
[179]智国平.基于动力传动系统联合控制的装载机自动换挡系统开发[D],长春:吉林大学, 2004.
[180]鲁民巧.自动变速器智能换档控制的研究[D].哈尔滨:哈尔滨工业大学, 2004.
[181]张宏坤.电控液力自动变速器换档控制技术的研究[D].大连:大连理工大学, 2005.
[182]刘振军.基于人-车-路环境下的汽车电控机械自动变速智能控制研究[D].重庆:重庆大学, 2005.
[183]雷晓东.电控机械自动变速系统换档控制策略研究[D].重庆:重庆大学, 2005.
[184]何涛.自动变速器换档控制技术的研究[D].北京:北京林业大学, 2005.
[185]朱小佩.轿车自动变速器换档规律的研究与仿真[D].上海:同济大学, 2006.
[186]马威.基于模糊控制理论的履带车辆自动换挡规律研究[D].武汉:华中科技大学, 2007.
[187]江立飞.客车自动换档原理研究及操控系统开发[D].大连:大连理工大学, 2007.
[188]邸林峰.自动变速智能换档控制技术的研究[D].沈阳:东北大学, 2007.
[189]何晓鹏.车辆自动换档规律的研究[D].石家庄:河北工业大学, 2007.
[190]孔慧芳.电控机械式自动变速器中传动与控制的关键技术研究[D].合肥:合肥工业大学, 2008.
[191]张金香.液力机械自动变速器的研究[D].兰州:兰州理工大学, 2009.
[192]周国清.混合动力大客车换挡决策研究[D].上海:上海交通大学, 2009.
[193]牛炳. AMT换挡规律及其自适应性研究[D].上海:上海交通大学, 2009.
[194]孙冬野,秦大同.基于人-车-路环境下汽车无级自动变速传动的智能控制[J].中国机械工程, 2005, 16(4): 357-360.
[195] Masayuki Yasuoka, Masaaki Uchida, Shusaku Katakura, et al. An integrated control algorithm for an SI engine and a CVT [C]. SAE technical paper. 1999-01-0752.
[196] T Kim, H Kim. Performance of integrated engine-CVT control considering powertrain loss and CVT response lag [J]. IMechE, 2002(216): 545-553.
[197] Heera Lee, Chulsoo Kim, Talchol Kim, et al. CVT ratio control algorithm by considering powertrain response lag [C]. SAE technical paper, 2004-01-1636.
[198] H Lee, H Kim. Improvement in fuel economy for a parallel hybrid electric vehicle by continuously variable transmission ratio control [J]. Drive System Technique, 2006, 20(3): 29-36.
[199] Wang Hongyan, Zhou Yunshan, Zhang Boying, et al. Research on integrated control strategy of CVT for passenger cars [C]. IVEC’1999: 401-405.
[200] Xie Xianping, Wang Xudong, Zhou Meilan. Study on integrated control strategy and simulation analysis of automotive with CVT [J]. ICEMT’2005: 365-369.
[201]孙冬野,秦大同.液力变矩器-机械无级变速器自动变速汽车综合控制策略研究[J].机械工程学报, 2003, 39(2): 102-105.
[202]何仁,马承广,张涌.基于驾驶意图的无级变速器目标速比确定方法[J].农业机械学报, 2009, 40(5): 16-19.
[203]孙冬野,秦大同,刘振军.汽车无级变速传动系统离散化的速比控制策略[J].江苏大学学报, 2009, 30(4): 352-356.
[204]宁凡坤.基于VR的汽车虚拟试验系统研究[D].成都:西华大学, 2006.
[205]徐延海,宁凡坤.用于汽车操纵稳定性模拟的虚拟现实平台的研究[J].系统仿真学报, 2007, 19(17): 3984-3987.
[206]张家祥,方凌江,毛全胜.基于MATLAB 6.x的系统分析与设计[M].西安:西安电子科技大学出版社, 2004.
[207]尹念东.汽车-驾驶员-环境闭环系统操纵稳定性虚拟试验技术的研究[D].北京:中国农业大学, 2001.
[208]王凯峰.基于虚拟现实与虚拟样机的汽车操纵稳定性研究[D].合肥:合肥工业大学, 2007.
[209]张勇.基于Simulink的机器人虚拟现实仿真研究[D].哈尔滨:哈尔滨工业大学, 2007.
[210]魏青.轻型电子机械制动汽车牵引力控制及虚拟仿真方法研究[D].长春:吉林大学, 2008.