商用半挂车制动意图辨识与制动力分配控制策略开发及验证
|
摘要
商用车电控制动系统是一种非常先进的制动系统，通过实现制动线控化，极大弥补了传统气压制动系统的制动延迟，提高了制动系统的响应时间，从而提高了制动安全性及舒适性，为商用车制动性能的提升带了巨大的空间，是未来商用车制动系统研发的方向。
本文依托国家863项目“高品质重型商用车集成开发先进技术”（编号：2006AA110104）及国家自然科学基金项目“基于模型预测的重型半挂车动力学稳定性多目标控制研究”（编号：51075176），在调研国内外商用车电控制动系统理论和应用的现有研究成果基础上，以提高制动安全性及舒适性为目标，以商用车电控制动系统为硬件基础，开发兼顾紧急制动及常规制动的驾驶员制动意图辨识的方法，并在此基础上开发制动辅助、多轴制动力分配等控制策略，为我国商用车电控制动系统的自主研发提供理论支持。论文主要进行了以下几个方面的研究工作：
(1)通过分析商用半挂车的结构特性，开发了商用半挂车26自由度非线性车辆动力学模型。文中将多轴半挂车简化为三轴形式：转向轴、驱动轴和挂车轴。所建立的模型主要是从车辆各个总成部件出发，对每一个子系统进行建模。子系统模型包括驾驶员模型、转向模型、发动机模型、传动系模型、制动系模型、车轮模型、轮胎模型、悬架模型、非簧载模型、车体动力学模型、路面模型和空气动力学模型。利用制动及操稳的工况进行了仿真，并与TruckSim对应工况的实验数据进行对比验证。为控制策略的离线仿真及硬件在环实验台验证提供了模型基础。
(2)对电控制动系统关键部件进行了性能分析及特性测试，针对各个执行机构的不同特性开发有针对性的闭环控制方法。通过对比例继动阀的结构进行观察、分析及测试，验证了其开环特性；针对其存在较大迟滞特性的特点，开发了PID结合前馈控制的控制方法，补偿其迟滞造成的闭环控制误差。由于桥控调节器及挂车桥控阀的核心构件均是开关阀，所以对其采用PWM的控制方法，为提高气室目标压力的闭环控制精度，采用了小步长增压的阶梯增压法。通过对这些关键部件进行开、闭环测试，掌握了这些阀的控制方法，为商用车电控制动系统控制策略的开发提供了硬件基础。
(3)搭建了电控制动系统硬件在环实验台，并进行EBS系统关键部件特性测试及EBS控制策略的硬件在环试验台验证。实验台由轮速模拟系统、测控系统、电控制动系统、人机交互系统及动力学实时交互系统组成。利用Matlab/xPCTarget技术搭建了电控制动系统快速原型平台，以软硬件结合的方式构建了电控制动系统硬件在环实验台，对比例继动阀、桥控调节器和挂车桥控阀的闭环特性进行了测试，并以此为基础，结合26自由度商用半挂车动力学模型，对驾驶员制动意图辨识方法、多轴车辆制动力分配控制策略及制动辅助控制策略进行了硬件在环实验台验证。
(4)利用神经网络的方法，建立了兼顾紧急制动及常规制动的驾驶员制动意图辨识模型。通过对制动时驾驶员制动特性的分析并结合EBS系统硬件特性，选定踏板开度及其变化率作为辨识驾驶员制动意图的参数，通过踏板开度辨识驾驶员期望制动减速度，踏板开度变化率辨识驾驶员制动的紧急程度。并选择神经网络的方法，结合小型驾驶模拟器，设计实验方案，采集驾驶员的制动操纵行为及车辆制动减速度，最终建立了同时适用于紧急制动及常规制动的驾驶员制动意图辨识模型，并对模型精度进行了离线验证。
(5)开发了制动辅助控制方法。利用硬件在环实验台，采集多个驾驶员的紧急制动行为，并通过后处理方法得到相应的紧急制动阈值。利用所建立的制动意图辨识模型，开发了制动辅助控制策略。当判断驾驶员有紧急制动意图时，制动辅助控制策略将取代驾驶员，向气室释放最大制动压力，确保制动系统对车辆施加最大的制动功率，并利用实验台对所开发的控制策略进行了验证。
(6)根据稳定性控制目标，分析了商用半挂车各轴分别抱死时的车辆状态，并基于滑移率控制方法，建立了多轴车辆制动力分配控制策略。通过分析确定，多轴车辆各轴的抱死顺序不同，对车辆的制动稳定性影响非常大：1）当前轴先抱死时，车辆稳定且可控；2）当挂车轴先抱死时，车辆稳定但不可控；3）当牵引车后轴先抱死时，车辆将既不稳定也不可控，将处于危险状态。利用TruckSim对分析结果进行了仿真验证。仿真结果验证了半挂车制动稳定性分析结果，即牵引车后轴先抱死是商用半挂车制动过程中最危险状况。根据商用半挂车动力学分析的结果，本文采用基于滑移率控制的方法，建立了多轴车辆制动力分配控制策略，根据车辆的实际状态通过相关控制算法确定目标滑移率，利用PID控制将滑移率控制在目标滑移率附近。利用所开发的26自由度车辆动力学模型及商用车电控制动系统硬件在环实验台，进行了控制策略的验证。
综上所述，本文取得的创新性成果如下：
(1)通过分析、测试商用车电控制动系统核心执行器的结构、功能及动态特性，搭建了商用半挂车硬件在环实验台，解决了商用车试验难度大，非线性强，试验精度不高等问题，并结合建立的26自由度多轴车辆非线性车辆动力学模型，对所开发的控制策略进行了验证。
(2)通过采集经验丰富的商用车驾驶员制动样本，利用神经网络方法，建立了兼顾紧急制动及常规制动的驾驶员制动意图辨识模型。并对模型进行了离线验证。利用建立的制动意图辨识方法，开发了制动辅助控制策略。
(3)针对多轴汽车抱死给制动安全性带来的隐患，通过对商用半挂车制动时车辆稳定性的分析，确定了牵引车及半挂车各轴抱死顺序对车辆的操纵性及稳定性的影响，提出了多轴车辆各轴抱死的最优顺序；并据此建立了基于滑移率的多轴车辆制动力控制策略；并结合所开发的多轴车辆动力学模型及硬件在环实验台对控制策略进行了验证。
Electronic braking system (EBS) of commercial heavy vehicle is a very advanced brakingsystem. It compensates for brake delay of conventional brake system greatly, and increase theresponse time of the braking system. Through braking by wire, EBS improves brake comfort andsafety significantly, and provides a huge space for commercial vehicle braking performanceenhancement. EBS is the development direction of the coming development of commercial vehiclebraking system.
Base on the research of commercial vehicle electric braking systems theory and applicationfrom domestic to foreign, this Ph.D. dissertation aims at the improvement of braking comfort andsecurity. This dissertation proposed a braking intention recognition method, which was used as thebasis of brake assist and multi-axis brake force distribution control method. This provided atheoretical support for independent research and development of China's commercial vehicleelectrical braking system. The main research work is summarized as follows:
(1)Studied the structural characteristics of commercial vehicle, and develop a26-DOFcommercial vehicle dynamics model
This model was simplified from the vehicle with three-axis: steering shaft, drive shaft and traileraxle, and tires of the axis are simplified to single tire. The established model is amulti-degree-of-freedom nonlinear model, including tractor longitudinal, lateral, yaw and sprungmass roll and vertical freedom; semitrailer longitudinal, lateral, yaw and the roll of sprung mass, pitchand vertical, vertical of the non-sprung mass, pitch and roll of the non-sprung mass;6wheel rotation,aggregately26degrees of freedom model. The model was divided into driver model, steering model,engine and transmission model, brake model, wheel model, tire model, suspension model,non-sprung model, body dynamics model, the road model and aerodynamic model.
(2)Electric performance testing of the core components of the system and the closed-loop control was designed and constructed. The electric control actuation system hardware-in-the-loop testbench was conducted, as well as the proportional relay valve performance testing and controlalgorithms.
Both proportional relay valve and axle modulator contain proportional solenoid valve, whichhas a large hysteresis characteristics. In order to improve the accuracy of the control, a hysteresischaracteristic curve of the relay valve was gained through bench testing. A method was proposed,which used the feed-forward control combined with the PID control method to compensate controlerror caused by the hysteresis of the control valve. This achieves the aiming cylinder pressureimproves control accuracy greatly.
In this dissertation, electric control actuation system hardware in the loop test bed was consistedof a wheel speed simulation system, measurement and control system, electrical control actuationsystem, the wheel cylinder pressure analog system and dynamics real-time interactive system.Proportional relay valve, axle modulator, trailer valve was tested to gain the control method. Aplatform was built with Matlab/xPC Target. This could be used as the basis of thehardware-in-the-loop experiment to verify the driver's braking intention identification strategy, brakeassist strategy and brake force distribution strategy.
(3)A braking intention identification strategy was proposed based on the displacement of thebrake pedal, the pedal displacement rate of change and the braking intensity of the three-dimensionalmodel. The relationship between the operation of the driver and his intention was recognized throughneural network method.
Braking intention reorganization will enhance the safety of the vehicle and the responsecharacteristics of the braking system greatly. This dissertation used the structural characteristics of theelectric control actuation system, selected the appropriate parameters, and established the brake pedalfor the driver's braking intention recognition model. A three-dimensional model, including pedaldisplacement, the pedal displacement rate of change and the brake intensity, was selected torecognize the braking intention.
The relationship between the driver's operation and the intention was obtained through severaldrivers' test on the platform. The data were used to establish the neural network model.
(4)A brake assist strategy was proposed.
When the driver quickly steps the brake pedal, the brake system should identify whether thevehicle is in need of emergency braking, regardless pedal position, the brake assist function willrelease the maximum braking pressure to the brake chamber full braking. In this dissertation, theestablished brake intention identification three-dimensional model could identify the driver's brakingintention. When the change rate of the brake pedal displacement is greater than the experimentallydetermined threshold, the system entered the emergency brake assist state, the strategy releasesmaximum value of the brake pedal. The dissertation collected several driver emergency brakingbehaviors using test bench, and the corresponding brake strength processed data were used todetermine emergency brake threshold.
(5)A multi-axial vehicle brake force distribution strategy was established.
Through the multi-axial vehicle braking mechanics analysis, the state of each axis has wasobtained. When the tractor front axle wheel brake locked, the front wheel would not generate thelateral force, and the train steering was uncontrolled, which would bring loss of steering capability. Inthe disturbance-free case, the vehicle could continue traveling straight until stopping; in lateral forceinterference case, the front wheel would skid, and off tracking occurred. Through the effect of inertialforce and the adjustment of the driver, the vehicle could resume operations under the steering controland straight track; if the semitrailer wheel locked before the tractor wheel, semi-trailer axle wouldalso slide. If the drift was not obvious and the swinging angle was not big, this instability could beovercome by relaxing brake pedal properly while slightly accelerated. The front and rear wheels ofthe car did not lock, and the ground could produce lateral forces; if the tractor rear axle locked first,the train would continue driving straight until stopping when there was no outside interference; whenthere was right lateral force interference (left lateral force interference can also be similar analyzed),the tractor had to rotate counter-clockwise around the saddle, the semi-trailer is a clockwise rotationaround the saddle Because Semitrailer was generally driven by rear axle, so neither to manipulate thesteering wheel or manipulating the accelerator pedal could made the vehicle resume drivingstraight, meanwhile semi-trailer could also exacerbate the folding of the vehicle due to the inertiapushing force generated by the brake on the tractor. Therefore, this braking condition was extremely dangerous condition. To sum up, it is stable and controllable when the front axle locked first, vehicles;it is uncontrollable when the semitrailer axle locked first; it is extremely dangerous when the rear axlelocked first. According to the results of the mechanical analysis, a braking force distributionalgorithm of multi-axial vehicle was developed. Currently, the automotive braking control systemmainly uses the control algorithm based on the threshold logic. This method is more complex, andcontrol process fluctuates heavily. To solve these problems, this dissertation used a method based onslip ratio control method. The PID control would control the slip ratio around the target slip ratio,which was determined through the related control algorithm. The control strategy was simulatedusing the26degrees of freedom vehicle dynamics model.
In summary, this dissertation made innovative achievements as follows：
(1)A26-DOF commercial vehicle dynamics model was developed after the analysis ofcommercial semitrailer's structure. Electric performance testing of the core components of the systemand the closed-loop control was designed and constructed. The electric control actuation systemhardware-in-the-loop test bench was conducted, as well as the proportional relay valve performancetesting and control algorithms.
(2)A three-dimensional model, including pedal displacement, the pedal displacement rate ofchange and the brake intensity, was selected to recognize the braking intention. The relationshipbetween the driver's operation and the intention was obtained through several drivers' test on theplatform. The data were used to establish the neural network model.
(3)The force state of the tractor and the semi-trailer was analyzed, and the effect of the lockingsequence on the vehicle was discussed. This dissertation used a method based on slip ratio controlmethod. The PID control would control the slip ratio around the target slip ratio, which wasdetermined through the related control algorithm. The control strategy was simulated using the26degrees of freedom vehicle dynamics model.
本文依托国家863项目“高品质重型商用车集成开发先进技术”（编号：2006AA110104）及国家自然科学基金项目“基于模型预测的重型半挂车动力学稳定性多目标控制研究”（编号：51075176），在调研国内外商用车电控制动系统理论和应用的现有研究成果基础上，以提高制动安全性及舒适性为目标，以商用车电控制动系统为硬件基础，开发兼顾紧急制动及常规制动的驾驶员制动意图辨识的方法，并在此基础上开发制动辅助、多轴制动力分配等控制策略，为我国商用车电控制动系统的自主研发提供理论支持。论文主要进行了以下几个方面的研究工作：
(1)通过分析商用半挂车的结构特性，开发了商用半挂车26自由度非线性车辆动力学模型。文中将多轴半挂车简化为三轴形式：转向轴、驱动轴和挂车轴。所建立的模型主要是从车辆各个总成部件出发，对每一个子系统进行建模。子系统模型包括驾驶员模型、转向模型、发动机模型、传动系模型、制动系模型、车轮模型、轮胎模型、悬架模型、非簧载模型、车体动力学模型、路面模型和空气动力学模型。利用制动及操稳的工况进行了仿真，并与TruckSim对应工况的实验数据进行对比验证。为控制策略的离线仿真及硬件在环实验台验证提供了模型基础。
(2)对电控制动系统关键部件进行了性能分析及特性测试，针对各个执行机构的不同特性开发有针对性的闭环控制方法。通过对比例继动阀的结构进行观察、分析及测试，验证了其开环特性；针对其存在较大迟滞特性的特点，开发了PID结合前馈控制的控制方法，补偿其迟滞造成的闭环控制误差。由于桥控调节器及挂车桥控阀的核心构件均是开关阀，所以对其采用PWM的控制方法，为提高气室目标压力的闭环控制精度，采用了小步长增压的阶梯增压法。通过对这些关键部件进行开、闭环测试，掌握了这些阀的控制方法，为商用车电控制动系统控制策略的开发提供了硬件基础。
(3)搭建了电控制动系统硬件在环实验台，并进行EBS系统关键部件特性测试及EBS控制策略的硬件在环试验台验证。实验台由轮速模拟系统、测控系统、电控制动系统、人机交互系统及动力学实时交互系统组成。利用Matlab/xPCTarget技术搭建了电控制动系统快速原型平台，以软硬件结合的方式构建了电控制动系统硬件在环实验台，对比例继动阀、桥控调节器和挂车桥控阀的闭环特性进行了测试，并以此为基础，结合26自由度商用半挂车动力学模型，对驾驶员制动意图辨识方法、多轴车辆制动力分配控制策略及制动辅助控制策略进行了硬件在环实验台验证。
(4)利用神经网络的方法，建立了兼顾紧急制动及常规制动的驾驶员制动意图辨识模型。通过对制动时驾驶员制动特性的分析并结合EBS系统硬件特性，选定踏板开度及其变化率作为辨识驾驶员制动意图的参数，通过踏板开度辨识驾驶员期望制动减速度，踏板开度变化率辨识驾驶员制动的紧急程度。并选择神经网络的方法，结合小型驾驶模拟器，设计实验方案，采集驾驶员的制动操纵行为及车辆制动减速度，最终建立了同时适用于紧急制动及常规制动的驾驶员制动意图辨识模型，并对模型精度进行了离线验证。
(5)开发了制动辅助控制方法。利用硬件在环实验台，采集多个驾驶员的紧急制动行为，并通过后处理方法得到相应的紧急制动阈值。利用所建立的制动意图辨识模型，开发了制动辅助控制策略。当判断驾驶员有紧急制动意图时，制动辅助控制策略将取代驾驶员，向气室释放最大制动压力，确保制动系统对车辆施加最大的制动功率，并利用实验台对所开发的控制策略进行了验证。
(6)根据稳定性控制目标，分析了商用半挂车各轴分别抱死时的车辆状态，并基于滑移率控制方法，建立了多轴车辆制动力分配控制策略。通过分析确定，多轴车辆各轴的抱死顺序不同，对车辆的制动稳定性影响非常大：1）当前轴先抱死时，车辆稳定且可控；2）当挂车轴先抱死时，车辆稳定但不可控；3）当牵引车后轴先抱死时，车辆将既不稳定也不可控，将处于危险状态。利用TruckSim对分析结果进行了仿真验证。仿真结果验证了半挂车制动稳定性分析结果，即牵引车后轴先抱死是商用半挂车制动过程中最危险状况。根据商用半挂车动力学分析的结果，本文采用基于滑移率控制的方法，建立了多轴车辆制动力分配控制策略，根据车辆的实际状态通过相关控制算法确定目标滑移率，利用PID控制将滑移率控制在目标滑移率附近。利用所开发的26自由度车辆动力学模型及商用车电控制动系统硬件在环实验台，进行了控制策略的验证。
综上所述，本文取得的创新性成果如下：
(1)通过分析、测试商用车电控制动系统核心执行器的结构、功能及动态特性，搭建了商用半挂车硬件在环实验台，解决了商用车试验难度大，非线性强，试验精度不高等问题，并结合建立的26自由度多轴车辆非线性车辆动力学模型，对所开发的控制策略进行了验证。
(2)通过采集经验丰富的商用车驾驶员制动样本，利用神经网络方法，建立了兼顾紧急制动及常规制动的驾驶员制动意图辨识模型。并对模型进行了离线验证。利用建立的制动意图辨识方法，开发了制动辅助控制策略。
(3)针对多轴汽车抱死给制动安全性带来的隐患，通过对商用半挂车制动时车辆稳定性的分析，确定了牵引车及半挂车各轴抱死顺序对车辆的操纵性及稳定性的影响，提出了多轴车辆各轴抱死的最优顺序；并据此建立了基于滑移率的多轴车辆制动力控制策略；并结合所开发的多轴车辆动力学模型及硬件在环实验台对控制策略进行了验证。
Electronic braking system (EBS) of commercial heavy vehicle is a very advanced brakingsystem. It compensates for brake delay of conventional brake system greatly, and increase theresponse time of the braking system. Through braking by wire, EBS improves brake comfort andsafety significantly, and provides a huge space for commercial vehicle braking performanceenhancement. EBS is the development direction of the coming development of commercial vehiclebraking system.
Base on the research of commercial vehicle electric braking systems theory and applicationfrom domestic to foreign, this Ph.D. dissertation aims at the improvement of braking comfort andsecurity. This dissertation proposed a braking intention recognition method, which was used as thebasis of brake assist and multi-axis brake force distribution control method. This provided atheoretical support for independent research and development of China's commercial vehicleelectrical braking system. The main research work is summarized as follows:
(1)Studied the structural characteristics of commercial vehicle, and develop a26-DOFcommercial vehicle dynamics model
This model was simplified from the vehicle with three-axis: steering shaft, drive shaft and traileraxle, and tires of the axis are simplified to single tire. The established model is amulti-degree-of-freedom nonlinear model, including tractor longitudinal, lateral, yaw and sprungmass roll and vertical freedom; semitrailer longitudinal, lateral, yaw and the roll of sprung mass, pitchand vertical, vertical of the non-sprung mass, pitch and roll of the non-sprung mass;6wheel rotation,aggregately26degrees of freedom model. The model was divided into driver model, steering model,engine and transmission model, brake model, wheel model, tire model, suspension model,non-sprung model, body dynamics model, the road model and aerodynamic model.
(2)Electric performance testing of the core components of the system and the closed-loop control was designed and constructed. The electric control actuation system hardware-in-the-loop testbench was conducted, as well as the proportional relay valve performance testing and controlalgorithms.
Both proportional relay valve and axle modulator contain proportional solenoid valve, whichhas a large hysteresis characteristics. In order to improve the accuracy of the control, a hysteresischaracteristic curve of the relay valve was gained through bench testing. A method was proposed,which used the feed-forward control combined with the PID control method to compensate controlerror caused by the hysteresis of the control valve. This achieves the aiming cylinder pressureimproves control accuracy greatly.
In this dissertation, electric control actuation system hardware in the loop test bed was consistedof a wheel speed simulation system, measurement and control system, electrical control actuationsystem, the wheel cylinder pressure analog system and dynamics real-time interactive system.Proportional relay valve, axle modulator, trailer valve was tested to gain the control method. Aplatform was built with Matlab/xPC Target. This could be used as the basis of thehardware-in-the-loop experiment to verify the driver's braking intention identification strategy, brakeassist strategy and brake force distribution strategy.
(3)A braking intention identification strategy was proposed based on the displacement of thebrake pedal, the pedal displacement rate of change and the braking intensity of the three-dimensionalmodel. The relationship between the operation of the driver and his intention was recognized throughneural network method.
Braking intention reorganization will enhance the safety of the vehicle and the responsecharacteristics of the braking system greatly. This dissertation used the structural characteristics of theelectric control actuation system, selected the appropriate parameters, and established the brake pedalfor the driver's braking intention recognition model. A three-dimensional model, including pedaldisplacement, the pedal displacement rate of change and the brake intensity, was selected torecognize the braking intention.
The relationship between the driver's operation and the intention was obtained through severaldrivers' test on the platform. The data were used to establish the neural network model.
(4)A brake assist strategy was proposed.
When the driver quickly steps the brake pedal, the brake system should identify whether thevehicle is in need of emergency braking, regardless pedal position, the brake assist function willrelease the maximum braking pressure to the brake chamber full braking. In this dissertation, theestablished brake intention identification three-dimensional model could identify the driver's brakingintention. When the change rate of the brake pedal displacement is greater than the experimentallydetermined threshold, the system entered the emergency brake assist state, the strategy releasesmaximum value of the brake pedal. The dissertation collected several driver emergency brakingbehaviors using test bench, and the corresponding brake strength processed data were used todetermine emergency brake threshold.
(5)A multi-axial vehicle brake force distribution strategy was established.
Through the multi-axial vehicle braking mechanics analysis, the state of each axis has wasobtained. When the tractor front axle wheel brake locked, the front wheel would not generate thelateral force, and the train steering was uncontrolled, which would bring loss of steering capability. Inthe disturbance-free case, the vehicle could continue traveling straight until stopping; in lateral forceinterference case, the front wheel would skid, and off tracking occurred. Through the effect of inertialforce and the adjustment of the driver, the vehicle could resume operations under the steering controland straight track; if the semitrailer wheel locked before the tractor wheel, semi-trailer axle wouldalso slide. If the drift was not obvious and the swinging angle was not big, this instability could beovercome by relaxing brake pedal properly while slightly accelerated. The front and rear wheels ofthe car did not lock, and the ground could produce lateral forces; if the tractor rear axle locked first,the train would continue driving straight until stopping when there was no outside interference; whenthere was right lateral force interference (left lateral force interference can also be similar analyzed),the tractor had to rotate counter-clockwise around the saddle, the semi-trailer is a clockwise rotationaround the saddle Because Semitrailer was generally driven by rear axle, so neither to manipulate thesteering wheel or manipulating the accelerator pedal could made the vehicle resume drivingstraight, meanwhile semi-trailer could also exacerbate the folding of the vehicle due to the inertiapushing force generated by the brake on the tractor. Therefore, this braking condition was extremely dangerous condition. To sum up, it is stable and controllable when the front axle locked first, vehicles;it is uncontrollable when the semitrailer axle locked first; it is extremely dangerous when the rear axlelocked first. According to the results of the mechanical analysis, a braking force distributionalgorithm of multi-axial vehicle was developed. Currently, the automotive braking control systemmainly uses the control algorithm based on the threshold logic. This method is more complex, andcontrol process fluctuates heavily. To solve these problems, this dissertation used a method based onslip ratio control method. The PID control would control the slip ratio around the target slip ratio,which was determined through the related control algorithm. The control strategy was simulatedusing the26degrees of freedom vehicle dynamics model.
In summary, this dissertation made innovative achievements as follows：
(1)A26-DOF commercial vehicle dynamics model was developed after the analysis ofcommercial semitrailer's structure. Electric performance testing of the core components of the systemand the closed-loop control was designed and constructed. The electric control actuation systemhardware-in-the-loop test bench was conducted, as well as the proportional relay valve performancetesting and control algorithms.
(2)A three-dimensional model, including pedal displacement, the pedal displacement rate ofchange and the brake intensity, was selected to recognize the braking intention. The relationshipbetween the driver's operation and the intention was obtained through several drivers' test on theplatform. The data were used to establish the neural network model.
(3)The force state of the tractor and the semi-trailer was analyzed, and the effect of the lockingsequence on the vehicle was discussed. This dissertation used a method based on slip ratio controlmethod. The PID control would control the slip ratio around the target slip ratio, which wasdetermined through the related control algorithm. The control strategy was simulated using the26degrees of freedom vehicle dynamics model.
引文
[1]黄炳华,陈祯福. ESC的最新动向和发展趋势[J].汽车工程,2008(1):1-9.
[2]清八山岛,张或定.液压特性与气压特性的比较[J].机床与液压.
[3]李开军,邓堃,夏群生等.半挂汽车列车制动中载荷转移对制动性能的影响[J].农业机械学报,2007,38(11):17-21.
[4]王媛媛. ESP系统的制动力分配控制策略优化[D].长春:吉林大学,2011.
[5]李骏,胡宗梅.汽车制动力分配比的优化与分析[J].农业装备与车辆工程,2008(11):18-19.
[6]余卓平,张元才,徐乐等.复合制动系统制动力协调分配方法仿真研究[J].汽车技术,2008(5):1-4.
[7]周继忠.转弯制动工况下汽车制动力分配策略仿真研究[D].上海:上海交通大学,2008.
[8] Nakazawa M., Isobe O., Takahashi S.et al. Braking force distribution control for improvedvehicle dynamics and brake performance[J]. Vehicle System Dynamics,1995,24(4-5):413-426.
[9] WABCO Company. EBS New Generation [R].2011.
[10]程伟涛,陈丰超. EBS电子制动控制系统[J].汽车与配件,2010(43):64-65.
[11] WABCO Company. WABCO EBS for Trailer[R].2007.
[12] WABCO Company. WABCO EBS system and functional description[R].2007.
[13]罗文发,张庶凯.电子制动系统(EBS)技术[J].汽车与配件,2009(12):73-75.
[14]刘录秀.克罗尔商用车制动系统技术发展(一)[J].汽车与配件,2006(21):48-51.
[15]刘录秀.克诺尔商用车制动系统技术发展(二)[J].汽车与配件,2006(26):36-39.
[16]杨通顺. Knorr制动系统公司展示新一代EBS挂车制动系统[J].汽车与配件,2002(34):20-21.
[17]张永辉,于良耀,宋健等.基于减速度参数的电子制动力分配控制算法[J].江苏大学学报(自然科学版),2010(6):645-650.
[18]林双武,刘志远.基于车轮加速度和滑移率的EBD控制策略[J].控制工程,2009(S2):32-35.
[19]毕竟.电动汽车制动控制策略的研究[J].科技信息,2010(22): I85.
[20]黄源,彭晓燕,谭震.线控制动系统制动力分配策略的研究与仿真[J].计算机仿真,2011(10):324-327.
[21]杨财,宋健. ABS/TCS/AYC中参考车速和滑移率算法研究[J].汽车工程,2009(1):24-27.
[22]制动力分配理论及其各种调整装置的特性[J].国外汽车,1971(5):47-56.
[23]朱忠华,胡景煌.具有感载比例阀的轻型客车制动系统分析及实验验证[J].合肥工业大学学报(自然科学版),2007,30(4):498-501.
[24]饶峻,黄虎.气压制动系统制动压力调节方法的研究[J].上海工程技术大学学报,2005,19(3):220-224.
[25]孟树兴,马恒永,石琴.具有制动力调节阀的汽车制动性能的计算机模拟计算[J].合肥工业大学学报(自然科学版),2003,26(2):213-217.
[26]马丽君.气动感载阀[J].汽车与配件,1989(3):16-17.
[27]邓起孝.货车气制动感载阀数学模型及动态设计方法[J].成都科技大学学报,1985(2):123-131.
[28]朱美璋.感载比例阀静特性优化设计[J].四川工业学院学报,1990,9(1):69-74.
[29]赵晓平.感载比例阀的工作原理及数学模型的建立[J].石家庄职业技术学院学报,2010,22(2):32-34.
[30]李以农,王意宝,罗志前等.气制动感载比例阀的AMESim仿真及试验[J].重庆大学学报,2009,32(7):766-769.
[31]郭福祥.感载比例阀动静特性分析与计算[J].上海汽车,2010(1):7-9.
[32]侯建章,沈昌娟.牵引车与挂车间制动协调分析[J].专用汽车,1993(2):50-57.
[33]付维舟.双挂式汽车列车理想制动力分配方法及制动稳定性[J].陕西汽车,1994(4):24-30.
[34]叶波,郑强.半挂车轴荷分配优化设计[J].十堰职业技术学院学报,2004(2):56-57.
[35]梁深华.低速货车制动力分配系数分析[J].技术与市场,2011(6):31-32.
[36]张建国.半挂汽车列车制动稳定性仿真分析[D].长春:吉林大学,2007.
[37]罗志前,王意宝.基于序列二次规划方法的商用车制动性能优化设计[J].重庆工学院学报(自然科学版),2009(7):13-17.
[38]董金松.半挂汽车列车弯道制动行驶方向稳定性及协调控制策略研究[D].长春:吉林大学,2010.
[39]孙万峰.商用车牵引力与制动力集成控制算法研究-博士[D].长春:吉林大学,2010.
[40]薛美儒,薛强,周良生等.惯性制动全挂车与牵引车制动力分配优化设计[J].天津科技大学学报,2011(3):48-50.
[41]李伟.汽车列车电控制动系统制动力分配的控制算法[J].汽车技术,2011,33(10):885-889.
[42]罗文发,陈晓磊.商用车电子控制制动技术[J].汽车与配件,2008(8):48-51.
[43] C. Beyer H. Schramm J. Wrede. Electronic Braking System EBS-Status and AdvancedFunctions[C]. SAE982781,1998.
[44] William P. Amato Mark A. Bennett,1999-01-3713Verification of Heavy Truck EBS and ABSUsing MatrixX Hardware in the Loop Tools [C], SAE1999-01-3713,1999.
[45] Hecker Falk, Beyer Herbert Schramm and Claus, Heavy Vehicle Stability Notification andAssistance [C], SAE2000-01-3481,2000.
[46] Szente V., Vad J., L O R A Nt G.et al. Computational and Experimental Investigation onDynamics of Electric Braking Systems[C],2001:263-275.
[47] F U Lep T., Oberling J., Palkovics L. Design of redundant brake-by-wire architecture forcommercial vehicles based on qualitative reliability approach[J]. Journal of KONESPowertrain and Transport,2006,13(1)
[48] Bu F., Tan H. S. Pneumatic brake control for precision stopping of heavy-duty vehicles[J].Control Systems Technology, IEEE Transactions on,2007,15(1):53-64.
[49] Erwin Petersen Detlev Neuhaus Klaus Gl be. Vehicle Stability Control for Trucks andBuses[C]. SAE982782,1998.
[50] Zong Chang-Fu, Yang Sheng-Nan, Zheng Hong-Yu. A control strategy of electronic brakingsystem based on brake comfort[C]. Changchun, China,2011:1265-1268.
[51]刘杰.商用车电子控制制动系统的控制算法研究[D].长春:吉林大学,2007.
[52]初亮,古佳运,张军等.商用车电子制动系统的底层CAN总线研究[C].中国山东青岛,2006:76-78.
[53]张军.商用车电子控制制动系统CAN总线试验研究与性能评价[D].长春:吉林大学,2007.
[54] Liang Chu, Jiayun Gu, Minghui Liuet al. Study on CAN Communication of EBS and BrakingPerformance Test for Commercial Vehicle[C].2007:849-852.
[55]袁兼宗,陈慧,刘自凯等.商用车EBS系统的压力闭环控制方法研究[C].中国汽车工程学会.天津,2008
[56]刘自凯,陈慧,袁兼宗等.商用车电子制动系统的建模与仿真[C].中国汽车工程学会.天津,2008
[57]刘旭刚,陈慧,袁兼宗.商用车EBS用比例继动阀控制方法的研究[C],2010
[58] Toshiya Hirose Tetsuo Taniguchi Tadashi Hatano, A Study on the Effect of Brake AssistSystems (BAS)[C]. SAE2008-01-0824,2008
[59] Shohei Kitazawa Yuzuru Matsuura. Feasibility Study of a Braking Assistant System for DriverPedal Operation in Emergency Situations[C]. SAE2004-01-0453,2004.
[60] T Kumagai, M Sakaguchi, Akamatsu. Prediction of Driving Behavior through ProbabilisticInference[M]. SPAIN,2003
[61] S Miller. A Driver Intent-based Collision Avoidance System[M]. Saskatoon Saskatchewan,2009
[62] Breuer J. J., Faulhaber A., Frank P.et al. Real world safety benefits of brake assistancesystems[M].2007
[63]康梅.东风标致307紧急制动辅助系统[J].汽车维修技师,2005(11)
[64]林志轩.制动踏板感觉影响因素分析以及制动意图识别研究[D].上海:同济大学,2007.
[65]王玉海,宋健,李兴坤.制动状态下的AMT换挡策略[J].农业机械学报,2006(01).
[66]张德兆,秦立峰,王建强等.基于电子真空助力器的汽车驾驶辅助系统制动压力控制[J].汽车工程,2011(12).
[67]王英范,宁国宝,余卓平.乘用车驾驶员制动意图识别参数的选择[J].汽车工程,2011(3):213-216.
[68]孙逸神.基于模糊逻辑的制动意图离线识别方法研究[J].北京汽车,2009(6):21-23.
[69]林逸,沈沉,王军等.汽车线控制动技术及发展[J].汽车技术,2005(12)
[70]马朝永,化北,王震等.电子制动踏板感觉模拟器研究[J].电子测量技术,2011(07)
[71]王奎洋,唐金花,刘成晔等.线控制动系统踏板感觉模拟器的分析与设计[J].机床与液压,2011(21):108-111.
[72] Guangyao Zhao,Cuiyun Peng. Intelligent Control for AMT Based on Driver's Intention andANFIS Decision-Making[C]. Proceedings of the7th World Congress on Intelligent Controland AutomationJune25-27, Chongqing, China.,2008,
[73]王玉海,宋健,李兴坤.基于模糊推理的驾驶员意图识别研究[J].公路交通科技,2005(12):113-118.
[74] Guihe Q., Yulong L., Mingkui N.et al. Estimation of road situations and driver's intention inautomotive electronic control system[C]. IEEE,1999:199-201.
[75] Aidemark Joakim, Vinter Jonny, Folkesson Peteret al. Experimental Evaluation ofTime-redundant Execution for a Brake-by-wire Application[C],2002
[76] Zechang S., Qinghe L., Xidong L. Research on Electro-Hydraulic Parallel Brake System forElectric Vehicle[C]. IEEE,2006:376-379.
[77]李玉芳,吴炎花.电-液复合制动电动汽车制动感觉一致性及实现方法[J].中国机械工程,2012(04)
[78]张元才,余卓平,徐乐等.基于制动意图的电动汽车复合制动系统制动力分配策略研究[J].汽车工程,2009(3):244-249.
[79]王畅.基于隐形马尔科夫模型的驾驶员意图辨识方法研究[D].长春:吉林大学,2011.
[80] Gillespie Thomas D.,赵六奇.车辆动力学基础[M].北京:清华大学出版社，2006
[81] Jazar Reza N., Vehicle dynamics[M]. New York: Springer，2008
[82]房永.三轴半挂汽车列车稳定性控制算法研究[D].长春:吉林大学,2010.
[83] Sharp R. S., Peng H. Vehicle dynamics applications of optimal control theory[J]. VehicleSystem Dynamics,2011,49(7):1073-1111.
[84]黄朝胜,隗海林,吴振昕.牵引车-半挂车列车动力学仿真研究[J].汽车工程,2005(6):744-750.
[85]刘宏飞.半挂汽车列车横摆动力学仿真及控制策略研究[D].长春:吉林大学,2005.
[86] Miller Jonathan I., Cebon David. A high performance pneumatic braking system for heavyvehicles[J]. Vehicle System Dynamics,2010(48):373-392.
[87]郭建华.双轴汽车电子稳定性协调控制系统研究[D].长春:吉林大学,2008.
[88] Andrea Fortina Mauro Velardocchia Aldo Sorniotti. Braking System ComponentsModelling[C]. SAE2003-01-3335,2003.
[89] E Bakker, L Nyborg, B. Pacejka H., Tyre modeling for use in vehicle dynamics studies
[C].1987.
[90] Pacejka Hans Bastiaan. Tyre and vehicle dynamics[M]. Elsevier Butterworth-Heinemann，2002
[91] Liang Wei, Medanic Jure, Ruhl Roland, Simulation of Intelligent Convey with AutonomousArticulated Commercial Vehicles [C]. SAE2003-01-3419,2003
[92] Sampson D. J. M. Active Roll Control of Articualated Heavy Vehicles[R],2002.
[93] Sampson. David John Matthew. Active Roll Control of Articulated Heavy Vehicles[D]:England Engineering Department of Cambridge University,2000.
[94]张武,王玲芳,孙鹏.基于MATLAB的线控控制系统分析与设计(第五版)[M].北京:机械工业出版社，2008.
[95] Kang Xiaodi, Deng Weiwen. Vehicle-Trailer Handling Dynamics and Stability Control─anEngineering Review[C]. SAE2007-01-0822,2007.
[96] Chan Brendan, Evaluation of Full and Partial Stability Systems on Tractor Semi Trailer UsingHardware-in-the-Loop Simulation[C]. SAE2010-01-1902,2010.
[97] C. Sandu A. Sandu B. J. Treatment of Constrained Multibody Dynamic Systems withUncertainties[C]. SAE2005-01-0936,2005.
[98]齐鲲鹏,隆武强,陈雷.硬件在环仿真在汽车控制系统开发中的应用及关键技术[J].内燃机,2006(05)
[99] Brendan Chan Ananda Pandy. Forward Collision Mitigation Systems: A Safety BenefitsAnalysis for Commercial Vehicles via Hardware-in-the-loop Simulation[C].SAE2011-01-2259,2011.
[100]郎志涛.商用车ABS系统ECU的开发及硬件在环验证[D].长春:吉林大学,2007.
[101]任国新.商用车ABS/TCS集成控制系统硬件在环仿真试验技术研究[D].长春:吉林大学,2008.
[102] B. J. Chan C. Sandu M. Ahmadian. Development of a Virtual Terramechanics Rig (VTR) forExperimental Validation[C]. SAE2006-01-3481,2006.
[103]郭芹凤.重型卡车ABS控制器的硬件在环仿真研究[D].北京:北京工业大学,2007.
[104] Mark Bennett Michael Tober. ABS System Validation-Integrating Tone Rings and WheelSpeed Sensors in HIL Simulation [C]. SAE2002-01-3123,2002.
[105]武志杰,郭洪艳,柳致海等.基于xPC Target的汽车动力学HiL仿真系统设计[J].控制工程,2011(04).
[106]李建华,宋传学,靳立强等. xPC目标环境下CAN卡驱动模块的开发[J].汽车技术,2010(05).
[107] Norman Andrew, Heavy Duty Truck Systems[M].2000.
[108]何力.基于多领域建模的重卡制动系统动力学研究[D].武汉:华中科技大学,2011.
[109]罗文发.电子控制制动系统EBS在牵引车上的应用[J].商用汽车,2008(6):126-128.
[110]罗文发.商用车气压防抱死制动系统技术应用[J].重型汽车,2009(2):15-18.
[111]李建藩,气压传动系统动力学[M].北京:华中理工大学出版社，1991.
[112]倪文波,王雪梅,李芾等.基于PWM技术的电空比例阀研究[J].机车电传动,2005(3):12-15.
[113]李光彬,张雪梅,赵光.基于PWM控制技术的电液比例阀特性的研究[J].中国设备工程,2007(6):22-23.
[114]郑扣根,唐杰,何通能,嵌入式系统—使用68HC12和HCS12的设计与应用[M].北京:电子工业出版社，2006
[115]邵贝贝,单片机嵌入式应用的在线开发方法[M].北京:清华大学出版社，2004
[116]王宜怀,刘晓升,嵌入式系统—使用HCS12微控制器的设计与应用[M].北京:北京航空航天大学出版社，2008
[117]刘曙光,魏俊民.电气比例阀特性的实验研究[J].液压气动与密封,1995(2):31-33.
[118]廖树昌.汽车前、后轴制动力分配及后轮压力滞后比例阀[J].广西机械,1999(3):13-17.
[119]孙洪程,翁维勤,过程控制系统及工程[M]，2002
[120]龙怀沛,朱麟章,过程控制系统及设计[M]，1995
[121]崔保健,李国新.基于比例阀门的精密气压控制方法研究[J].计算机测量与控制,2005(12):1366-1367.
[122]石成英,韩华锋,施广宏.气体压力闭环控制系统设计[J].现代电子技术,2010(21):135-137.
[123]刘海锋.基于神经网络的系统辨识方法研究[D].西安:西安电子科技大学,2007.
[124]胡玉玲,曹建国.基于模糊神经网络的动态非线性系统辨识研究[J].系统仿真学报,2007(03)
[125]周哲,陈杰,武汉工程大学等.基于RBF神经网络的自适应控制研究[D].武汉:武汉工程大学,2011.
[126]步媛媛,关忠仁.基于K-means聚类算法的研究[J].西南民族大学学报(自然科学版),2009(01)
[127]李鑫滨,杨景明,丁喜峰.基于递推k-均值聚类算法的RBF神经网络及其在系统辨识中的应用[J].燕山大学学报,1999(04)
[128]雷升锴,刘红阳,何嘉等.动态K-均值聚类算法在RBF神经网络中心选取中的应用[J].信息系统工程,2011(06)
[129]徐颖.汽车驾驶模拟器的实时数据采集与控制系统[D].长春:吉林大学,2004.
[130]丁立,熊坚,陈泽林等.面向人-车-环境系统的汽车驾驶模拟器的开发和应用[J].公路交通科技,2002(06)
[131]莫卫国,胡飞.基于Vega的视景仿真系统中的人机交互技术[J].计算机仿真,2007(10)
[132]王艳芹,张维.基于MATLAB的RBF神经网络建模及应用[J].大庆师范学院学报,2007(02)
[133]杜天强,李海斌,王坤.汽车制动辅助系统BAS的应用现状[J].汽车工程师,2011(4):52-55.
[134]布勒伊尔B.,比尔K.,制动技术手册[M].北京:机械工业出版社，2011
[135]张建国.基于闭环控制的半挂汽车列车行驶稳定性研究[D].长春:吉林大学,2010.
[136] Limpert Rudolf, Brake design and safety(2nd)[M].1999.
[137]赖锋.重型汽车制动系统结构分析及其设计方法研究[D].武汉:武汉理工大学,2006.
[138]黄朝胜.重型载货汽车底盘性能设计参数控制研究[D].长春:吉林大学,2005.
[139]郭建磊.车辆防抱死EBD技术的研究[D].天津:河北工业大学,2011.
[140]张体环.混合动力客车制动力协调控制算法研究[D].长春:吉林大学,2011.
[141]何玮,刘昭度,齐志权等.气压ABS系统制动压力动态特性分析[J].液压气动与密封,2006(6):4-6.
[142] Goodarzi A., Behmadi M., Esmailzadeh E. Optimized braking force distribution during abraking-in-turn maneuver for articulated vehicles[C]. IEEE,2010:555-559.
[143] Suh M. W., Park Y. K., Kwon S. J.et al. A simulation program for the braking characteristics oftractor-semitrailer vehicle[J]. SAE2000-01-3415,2000.
[144]张文利.基于滑移率的ABS/EBD控制策略研究[D].长春:吉林大学,2008.
[145]李锐,王蓉,赵双等.汽车电子制动力分配的分级控制与仿真研究[J].重庆邮电大学学报(自然科学版),2009(3):398-401.
[146] Bae H. S., Gerdes J. C. Parameter estimation and command modification for longitudinalcontrol of heavy vehicles[J],2003
[147]郝永明.商用车电子制动力分配系统(EBL)[J].汽车与配件,2006(6):46-47.
[148]方泳龙,汽车制动理论与设计[M].北京:国防工业出版社，2005:184.
[149]崔明博.基于实时滑移率的汽车防抱制动系统及其仿真研究[D].哈尔滨:哈尔滨理工大学,2010.
[150]刘杰.汽车电子制动力分配系统的控制策略研究[D].合肥:合肥工业大学,2009.
[2]清八山岛,张或定.液压特性与气压特性的比较[J].机床与液压.
[3]李开军,邓堃,夏群生等.半挂汽车列车制动中载荷转移对制动性能的影响[J].农业机械学报,2007,38(11):17-21.
[4]王媛媛. ESP系统的制动力分配控制策略优化[D].长春:吉林大学,2011.
[5]李骏,胡宗梅.汽车制动力分配比的优化与分析[J].农业装备与车辆工程,2008(11):18-19.
[6]余卓平,张元才,徐乐等.复合制动系统制动力协调分配方法仿真研究[J].汽车技术,2008(5):1-4.
[7]周继忠.转弯制动工况下汽车制动力分配策略仿真研究[D].上海:上海交通大学,2008.
[8] Nakazawa M., Isobe O., Takahashi S.et al. Braking force distribution control for improvedvehicle dynamics and brake performance[J]. Vehicle System Dynamics,1995,24(4-5):413-426.
[9] WABCO Company. EBS New Generation [R].2011.
[10]程伟涛,陈丰超. EBS电子制动控制系统[J].汽车与配件,2010(43):64-65.
[11] WABCO Company. WABCO EBS for Trailer[R].2007.
[12] WABCO Company. WABCO EBS system and functional description[R].2007.
[13]罗文发,张庶凯.电子制动系统(EBS)技术[J].汽车与配件,2009(12):73-75.
[14]刘录秀.克罗尔商用车制动系统技术发展(一)[J].汽车与配件,2006(21):48-51.
[15]刘录秀.克诺尔商用车制动系统技术发展(二)[J].汽车与配件,2006(26):36-39.
[16]杨通顺. Knorr制动系统公司展示新一代EBS挂车制动系统[J].汽车与配件,2002(34):20-21.
[17]张永辉,于良耀,宋健等.基于减速度参数的电子制动力分配控制算法[J].江苏大学学报(自然科学版),2010(6):645-650.
[18]林双武,刘志远.基于车轮加速度和滑移率的EBD控制策略[J].控制工程,2009(S2):32-35.
[19]毕竟.电动汽车制动控制策略的研究[J].科技信息,2010(22): I85.
[20]黄源,彭晓燕,谭震.线控制动系统制动力分配策略的研究与仿真[J].计算机仿真,2011(10):324-327.
[21]杨财,宋健. ABS/TCS/AYC中参考车速和滑移率算法研究[J].汽车工程,2009(1):24-27.
[22]制动力分配理论及其各种调整装置的特性[J].国外汽车,1971(5):47-56.
[23]朱忠华,胡景煌.具有感载比例阀的轻型客车制动系统分析及实验验证[J].合肥工业大学学报(自然科学版),2007,30(4):498-501.
[24]饶峻,黄虎.气压制动系统制动压力调节方法的研究[J].上海工程技术大学学报,2005,19(3):220-224.
[25]孟树兴,马恒永,石琴.具有制动力调节阀的汽车制动性能的计算机模拟计算[J].合肥工业大学学报(自然科学版),2003,26(2):213-217.
[26]马丽君.气动感载阀[J].汽车与配件,1989(3):16-17.
[27]邓起孝.货车气制动感载阀数学模型及动态设计方法[J].成都科技大学学报,1985(2):123-131.
[28]朱美璋.感载比例阀静特性优化设计[J].四川工业学院学报,1990,9(1):69-74.
[29]赵晓平.感载比例阀的工作原理及数学模型的建立[J].石家庄职业技术学院学报,2010,22(2):32-34.
[30]李以农,王意宝,罗志前等.气制动感载比例阀的AMESim仿真及试验[J].重庆大学学报,2009,32(7):766-769.
[31]郭福祥.感载比例阀动静特性分析与计算[J].上海汽车,2010(1):7-9.
[32]侯建章,沈昌娟.牵引车与挂车间制动协调分析[J].专用汽车,1993(2):50-57.
[33]付维舟.双挂式汽车列车理想制动力分配方法及制动稳定性[J].陕西汽车,1994(4):24-30.
[34]叶波,郑强.半挂车轴荷分配优化设计[J].十堰职业技术学院学报,2004(2):56-57.
[35]梁深华.低速货车制动力分配系数分析[J].技术与市场,2011(6):31-32.
[36]张建国.半挂汽车列车制动稳定性仿真分析[D].长春:吉林大学,2007.
[37]罗志前,王意宝.基于序列二次规划方法的商用车制动性能优化设计[J].重庆工学院学报(自然科学版),2009(7):13-17.
[38]董金松.半挂汽车列车弯道制动行驶方向稳定性及协调控制策略研究[D].长春:吉林大学,2010.
[39]孙万峰.商用车牵引力与制动力集成控制算法研究-博士[D].长春:吉林大学,2010.
[40]薛美儒,薛强,周良生等.惯性制动全挂车与牵引车制动力分配优化设计[J].天津科技大学学报,2011(3):48-50.
[41]李伟.汽车列车电控制动系统制动力分配的控制算法[J].汽车技术,2011,33(10):885-889.
[42]罗文发,陈晓磊.商用车电子控制制动技术[J].汽车与配件,2008(8):48-51.
[43] C. Beyer H. Schramm J. Wrede. Electronic Braking System EBS-Status and AdvancedFunctions[C]. SAE982781,1998.
[44] William P. Amato Mark A. Bennett,1999-01-3713Verification of Heavy Truck EBS and ABSUsing MatrixX Hardware in the Loop Tools [C], SAE1999-01-3713,1999.
[45] Hecker Falk, Beyer Herbert Schramm and Claus, Heavy Vehicle Stability Notification andAssistance [C], SAE2000-01-3481,2000.
[46] Szente V., Vad J., L O R A Nt G.et al. Computational and Experimental Investigation onDynamics of Electric Braking Systems[C],2001:263-275.
[47] F U Lep T., Oberling J., Palkovics L. Design of redundant brake-by-wire architecture forcommercial vehicles based on qualitative reliability approach[J]. Journal of KONESPowertrain and Transport,2006,13(1)
[48] Bu F., Tan H. S. Pneumatic brake control for precision stopping of heavy-duty vehicles[J].Control Systems Technology, IEEE Transactions on,2007,15(1):53-64.
[49] Erwin Petersen Detlev Neuhaus Klaus Gl be. Vehicle Stability Control for Trucks andBuses[C]. SAE982782,1998.
[50] Zong Chang-Fu, Yang Sheng-Nan, Zheng Hong-Yu. A control strategy of electronic brakingsystem based on brake comfort[C]. Changchun, China,2011:1265-1268.
[51]刘杰.商用车电子控制制动系统的控制算法研究[D].长春:吉林大学,2007.
[52]初亮,古佳运,张军等.商用车电子制动系统的底层CAN总线研究[C].中国山东青岛,2006:76-78.
[53]张军.商用车电子控制制动系统CAN总线试验研究与性能评价[D].长春:吉林大学,2007.
[54] Liang Chu, Jiayun Gu, Minghui Liuet al. Study on CAN Communication of EBS and BrakingPerformance Test for Commercial Vehicle[C].2007:849-852.
[55]袁兼宗,陈慧,刘自凯等.商用车EBS系统的压力闭环控制方法研究[C].中国汽车工程学会.天津,2008
[56]刘自凯,陈慧,袁兼宗等.商用车电子制动系统的建模与仿真[C].中国汽车工程学会.天津,2008
[57]刘旭刚,陈慧,袁兼宗.商用车EBS用比例继动阀控制方法的研究[C],2010
[58] Toshiya Hirose Tetsuo Taniguchi Tadashi Hatano, A Study on the Effect of Brake AssistSystems (BAS)[C]. SAE2008-01-0824,2008
[59] Shohei Kitazawa Yuzuru Matsuura. Feasibility Study of a Braking Assistant System for DriverPedal Operation in Emergency Situations[C]. SAE2004-01-0453,2004.
[60] T Kumagai, M Sakaguchi, Akamatsu. Prediction of Driving Behavior through ProbabilisticInference[M]. SPAIN,2003
[61] S Miller. A Driver Intent-based Collision Avoidance System[M]. Saskatoon Saskatchewan,2009
[62] Breuer J. J., Faulhaber A., Frank P.et al. Real world safety benefits of brake assistancesystems[M].2007
[63]康梅.东风标致307紧急制动辅助系统[J].汽车维修技师,2005(11)
[64]林志轩.制动踏板感觉影响因素分析以及制动意图识别研究[D].上海:同济大学,2007.
[65]王玉海,宋健,李兴坤.制动状态下的AMT换挡策略[J].农业机械学报,2006(01).
[66]张德兆,秦立峰,王建强等.基于电子真空助力器的汽车驾驶辅助系统制动压力控制[J].汽车工程,2011(12).
[67]王英范,宁国宝,余卓平.乘用车驾驶员制动意图识别参数的选择[J].汽车工程,2011(3):213-216.
[68]孙逸神.基于模糊逻辑的制动意图离线识别方法研究[J].北京汽车,2009(6):21-23.
[69]林逸,沈沉,王军等.汽车线控制动技术及发展[J].汽车技术,2005(12)
[70]马朝永,化北,王震等.电子制动踏板感觉模拟器研究[J].电子测量技术,2011(07)
[71]王奎洋,唐金花,刘成晔等.线控制动系统踏板感觉模拟器的分析与设计[J].机床与液压,2011(21):108-111.
[72] Guangyao Zhao,Cuiyun Peng. Intelligent Control for AMT Based on Driver's Intention andANFIS Decision-Making[C]. Proceedings of the7th World Congress on Intelligent Controland AutomationJune25-27, Chongqing, China.,2008,
[73]王玉海,宋健,李兴坤.基于模糊推理的驾驶员意图识别研究[J].公路交通科技,2005(12):113-118.
[74] Guihe Q., Yulong L., Mingkui N.et al. Estimation of road situations and driver's intention inautomotive electronic control system[C]. IEEE,1999:199-201.
[75] Aidemark Joakim, Vinter Jonny, Folkesson Peteret al. Experimental Evaluation ofTime-redundant Execution for a Brake-by-wire Application[C],2002
[76] Zechang S., Qinghe L., Xidong L. Research on Electro-Hydraulic Parallel Brake System forElectric Vehicle[C]. IEEE,2006:376-379.
[77]李玉芳,吴炎花.电-液复合制动电动汽车制动感觉一致性及实现方法[J].中国机械工程,2012(04)
[78]张元才,余卓平,徐乐等.基于制动意图的电动汽车复合制动系统制动力分配策略研究[J].汽车工程,2009(3):244-249.
[79]王畅.基于隐形马尔科夫模型的驾驶员意图辨识方法研究[D].长春:吉林大学,2011.
[80] Gillespie Thomas D.,赵六奇.车辆动力学基础[M].北京:清华大学出版社，2006
[81] Jazar Reza N., Vehicle dynamics[M]. New York: Springer，2008
[82]房永.三轴半挂汽车列车稳定性控制算法研究[D].长春:吉林大学,2010.
[83] Sharp R. S., Peng H. Vehicle dynamics applications of optimal control theory[J]. VehicleSystem Dynamics,2011,49(7):1073-1111.
[84]黄朝胜,隗海林,吴振昕.牵引车-半挂车列车动力学仿真研究[J].汽车工程,2005(6):744-750.
[85]刘宏飞.半挂汽车列车横摆动力学仿真及控制策略研究[D].长春:吉林大学,2005.
[86] Miller Jonathan I., Cebon David. A high performance pneumatic braking system for heavyvehicles[J]. Vehicle System Dynamics,2010(48):373-392.
[87]郭建华.双轴汽车电子稳定性协调控制系统研究[D].长春:吉林大学,2008.
[88] Andrea Fortina Mauro Velardocchia Aldo Sorniotti. Braking System ComponentsModelling[C]. SAE2003-01-3335,2003.
[89] E Bakker, L Nyborg, B. Pacejka H., Tyre modeling for use in vehicle dynamics studies
[C].1987.
[90] Pacejka Hans Bastiaan. Tyre and vehicle dynamics[M]. Elsevier Butterworth-Heinemann，2002
[91] Liang Wei, Medanic Jure, Ruhl Roland, Simulation of Intelligent Convey with AutonomousArticulated Commercial Vehicles [C]. SAE2003-01-3419,2003
[92] Sampson D. J. M. Active Roll Control of Articualated Heavy Vehicles[R],2002.
[93] Sampson. David John Matthew. Active Roll Control of Articulated Heavy Vehicles[D]:England Engineering Department of Cambridge University,2000.
[94]张武,王玲芳,孙鹏.基于MATLAB的线控控制系统分析与设计(第五版)[M].北京:机械工业出版社，2008.
[95] Kang Xiaodi, Deng Weiwen. Vehicle-Trailer Handling Dynamics and Stability Control─anEngineering Review[C]. SAE2007-01-0822,2007.
[96] Chan Brendan, Evaluation of Full and Partial Stability Systems on Tractor Semi Trailer UsingHardware-in-the-Loop Simulation[C]. SAE2010-01-1902,2010.
[97] C. Sandu A. Sandu B. J. Treatment of Constrained Multibody Dynamic Systems withUncertainties[C]. SAE2005-01-0936,2005.
[98]齐鲲鹏,隆武强,陈雷.硬件在环仿真在汽车控制系统开发中的应用及关键技术[J].内燃机,2006(05)
[99] Brendan Chan Ananda Pandy. Forward Collision Mitigation Systems: A Safety BenefitsAnalysis for Commercial Vehicles via Hardware-in-the-loop Simulation[C].SAE2011-01-2259,2011.
[100]郎志涛.商用车ABS系统ECU的开发及硬件在环验证[D].长春:吉林大学,2007.
[101]任国新.商用车ABS/TCS集成控制系统硬件在环仿真试验技术研究[D].长春:吉林大学,2008.
[102] B. J. Chan C. Sandu M. Ahmadian. Development of a Virtual Terramechanics Rig (VTR) forExperimental Validation[C]. SAE2006-01-3481,2006.
[103]郭芹凤.重型卡车ABS控制器的硬件在环仿真研究[D].北京:北京工业大学,2007.
[104] Mark Bennett Michael Tober. ABS System Validation-Integrating Tone Rings and WheelSpeed Sensors in HIL Simulation [C]. SAE2002-01-3123,2002.
[105]武志杰,郭洪艳,柳致海等.基于xPC Target的汽车动力学HiL仿真系统设计[J].控制工程,2011(04).
[106]李建华,宋传学,靳立强等. xPC目标环境下CAN卡驱动模块的开发[J].汽车技术,2010(05).
[107] Norman Andrew, Heavy Duty Truck Systems[M].2000.
[108]何力.基于多领域建模的重卡制动系统动力学研究[D].武汉:华中科技大学,2011.
[109]罗文发.电子控制制动系统EBS在牵引车上的应用[J].商用汽车,2008(6):126-128.
[110]罗文发.商用车气压防抱死制动系统技术应用[J].重型汽车,2009(2):15-18.
[111]李建藩,气压传动系统动力学[M].北京:华中理工大学出版社，1991.
[112]倪文波,王雪梅,李芾等.基于PWM技术的电空比例阀研究[J].机车电传动,2005(3):12-15.
[113]李光彬,张雪梅,赵光.基于PWM控制技术的电液比例阀特性的研究[J].中国设备工程,2007(6):22-23.
[114]郑扣根,唐杰,何通能,嵌入式系统—使用68HC12和HCS12的设计与应用[M].北京:电子工业出版社，2006
[115]邵贝贝,单片机嵌入式应用的在线开发方法[M].北京:清华大学出版社，2004
[116]王宜怀,刘晓升,嵌入式系统—使用HCS12微控制器的设计与应用[M].北京:北京航空航天大学出版社，2008
[117]刘曙光,魏俊民.电气比例阀特性的实验研究[J].液压气动与密封,1995(2):31-33.
[118]廖树昌.汽车前、后轴制动力分配及后轮压力滞后比例阀[J].广西机械,1999(3):13-17.
[119]孙洪程,翁维勤,过程控制系统及工程[M]，2002
[120]龙怀沛,朱麟章,过程控制系统及设计[M]，1995
[121]崔保健,李国新.基于比例阀门的精密气压控制方法研究[J].计算机测量与控制,2005(12):1366-1367.
[122]石成英,韩华锋,施广宏.气体压力闭环控制系统设计[J].现代电子技术,2010(21):135-137.
[123]刘海锋.基于神经网络的系统辨识方法研究[D].西安:西安电子科技大学,2007.
[124]胡玉玲,曹建国.基于模糊神经网络的动态非线性系统辨识研究[J].系统仿真学报,2007(03)
[125]周哲,陈杰,武汉工程大学等.基于RBF神经网络的自适应控制研究[D].武汉:武汉工程大学,2011.
[126]步媛媛,关忠仁.基于K-means聚类算法的研究[J].西南民族大学学报(自然科学版),2009(01)
[127]李鑫滨,杨景明,丁喜峰.基于递推k-均值聚类算法的RBF神经网络及其在系统辨识中的应用[J].燕山大学学报,1999(04)
[128]雷升锴,刘红阳,何嘉等.动态K-均值聚类算法在RBF神经网络中心选取中的应用[J].信息系统工程,2011(06)
[129]徐颖.汽车驾驶模拟器的实时数据采集与控制系统[D].长春:吉林大学,2004.
[130]丁立,熊坚,陈泽林等.面向人-车-环境系统的汽车驾驶模拟器的开发和应用[J].公路交通科技,2002(06)
[131]莫卫国,胡飞.基于Vega的视景仿真系统中的人机交互技术[J].计算机仿真,2007(10)
[132]王艳芹,张维.基于MATLAB的RBF神经网络建模及应用[J].大庆师范学院学报,2007(02)
[133]杜天强,李海斌,王坤.汽车制动辅助系统BAS的应用现状[J].汽车工程师,2011(4):52-55.
[134]布勒伊尔B.,比尔K.,制动技术手册[M].北京:机械工业出版社，2011
[135]张建国.基于闭环控制的半挂汽车列车行驶稳定性研究[D].长春:吉林大学,2010.
[136] Limpert Rudolf, Brake design and safety(2nd)[M].1999.
[137]赖锋.重型汽车制动系统结构分析及其设计方法研究[D].武汉:武汉理工大学,2006.
[138]黄朝胜.重型载货汽车底盘性能设计参数控制研究[D].长春:吉林大学,2005.
[139]郭建磊.车辆防抱死EBD技术的研究[D].天津:河北工业大学,2011.
[140]张体环.混合动力客车制动力协调控制算法研究[D].长春:吉林大学,2011.
[141]何玮,刘昭度,齐志权等.气压ABS系统制动压力动态特性分析[J].液压气动与密封,2006(6):4-6.
[142] Goodarzi A., Behmadi M., Esmailzadeh E. Optimized braking force distribution during abraking-in-turn maneuver for articulated vehicles[C]. IEEE,2010:555-559.
[143] Suh M. W., Park Y. K., Kwon S. J.et al. A simulation program for the braking characteristics oftractor-semitrailer vehicle[J]. SAE2000-01-3415,2000.
[144]张文利.基于滑移率的ABS/EBD控制策略研究[D].长春:吉林大学,2008.
[145]李锐,王蓉,赵双等.汽车电子制动力分配的分级控制与仿真研究[J].重庆邮电大学学报(自然科学版),2009(3):398-401.
[146] Bae H. S., Gerdes J. C. Parameter estimation and command modification for longitudinalcontrol of heavy vehicles[J],2003
[147]郝永明.商用车电子制动力分配系统(EBL)[J].汽车与配件,2006(6):46-47.
[148]方泳龙,汽车制动理论与设计[M].北京:国防工业出版社，2005:184.
[149]崔明博.基于实时滑移率的汽车防抱制动系统及其仿真研究[D].哈尔滨:哈尔滨理工大学,2010.
[150]刘杰.汽车电子制动力分配系统的控制策略研究[D].合肥:合肥工业大学,2009.