改进的小生境遗传算法在铁道车辆优化设计中的应用

选取合适的优化方法对铁道车辆转向架悬挂参数进行优化,能有效提高车辆的动力学性能。遗传算法是一种多参数多目标优化方法,提出了采用改进的小生境遗传算法,以某铁道车辆转向架悬挂参数为设计变量,针对车辆的稳定性进行了优化设计。结果显示,通过改进的遗传算法优化出的悬挂参数能有效提高车辆的稳定性,优化后车辆的临界速度到达了600 km/h,而通过基本遗传算法和单目标优化方法得到的临界速度分别仅为500 km/h和520 km/h。研究表明,改进的小生境遗传算法能很好的实现悬挂参数间的合理匹配,优化出良好的动力学性能。     

A joystick driving control algorithm with a longitudinal collision avoidance scheme for an electric vehicle

In this paper, we develop a joystick manual driving algorithm for an electric vehicle called Cycab. Cycab is developed as a public transportation vehicle, which can be driven either by a manual joystick or an automated driving mode. The vehicle uses six motors for driving four wheels, and front/rear steerings. Cycab utilizes one industrial PC with a real time Linux kernel and four Motorola MPC555 micro controllers, and a CAN network for the communication among the five processors. The developed algorithm consists of two automatic vehicle speed control algorithms for normal and emergency situations that override the driver’s joystick command and an open loop torque distribution algorithm for the traction motors. In this study, the algorithm is developed using SynDEx, which is a system level CAD software dedicated to rapid prototyping and optimizing the implementation of real-time embedded applications on distributed architectures. The experimental results verify the usefulness of the two automatic vehicle control algorithms.     

基于多基站IMMKF-DOA辅助车辆协同定位算法研究

针对传统卡尔曼滤波算法在进行车辆实时运动过程中难以精准定位问题,提出一种基于运动状态自适应的交互多模型卡尔曼滤波(Interacting multiple model Kalman filter,IMMKF)与多基站到达方向(Direction-of-arrival,DOA)相融合进行车辆位置实时估计算法。基于无偏估计器对测量噪声协方差进行实时更新并将其嵌入标准卡尔曼滤波算法中实现自适应交互多模型卡尔曼滤波。针对车辆不同运动状态及动态行驶环境对车辆定位估计精度的影响,构建自适应交互多模型卡尔曼滤波器与多基站信息融合算法进行车辆位置实时估计,考虑不同车速与不同基站数等行驶工况下车辆定位精度的变化趋势,实现车辆实时位置的准确估计。利用PreScan-Simulink联合仿真平台进行虚拟仿真验证和实车试验验证。结果表明,基于交互多模型卡尔曼滤波与到达方向角的融合算法相对标准的卡尔曼滤波估计精度高,较好地改善了传统单一模型的卡尔曼滤波算法在进行车辆实时运动状态估计过程中精准定位问题,实车试验验证了提出算法对车辆定位精度较传统卡尔曼滤波算法的精度提高了一个数量级,实现了更精确的车辆位置估计。     

基于SSA算法优化SVM的发动机润滑油信息状态评估

润滑油信息能够有效反映装甲车辆发动机的健康状态,对车辆发动机状态评估十分重要。以某型装甲车辆发动机为研究对象,提出一种基于麻雀搜索算法(Sparrow Search Algorithm, SSA)优化支持向量机(Support Vector Machine, SVM)的发动机状态评估算法。该算法首先对润滑油原始数据进行去噪及归一化处理,然后使用麻雀搜索算法优化支持向量机的核参数与惩罚参数,最后利用寻优后的参数建立评估模型。实验结果表明,采用麻雀搜索算法优化的支持向量机分类准确率高达96.67%,能够有效对发动机状态进行评估,为装甲车辆发动机的换油以及维修提供依据。     

基于遗传整定的主动悬架模糊PID控制设计

针对车辆主动悬架模糊PID控制设计,提出了一种利用遗传算法整定模糊PID增益系数的方法。基于二自由度的1/4车辆模型,根据模糊控制原理和PID控制方法,设计了主动悬架的模糊PID控制器。利用具有全局寻优能力的遗传算法,以悬架二次型性能指标为目标函数,采用适应性比例法确定选择概率,整定了模糊PID的增益系数。优化结果表明,整定后的模糊PID控制主动悬架相对被动悬架综合性能良好,说明了提出的方法是有效的,对模糊PID控制设计具有重要的参考价值。     

基于免疫算法的差速驱动智能车辆轨迹跟踪研究

将车轮运动看成一种无侧滑、纯滚动运动.简化车辆运动模型为两轮共轴但独立差速驱动.并将基于免疫学原理中的人工免疫算法引入到车辆运动控制中.通过对车辆的轨迹跟踪仿真实验,验证免疫算法在车辆控制过程中的优劣.仿真结果表明,将人工免疫算法引入车辆运动控制中取得了良好的效果,具有良好的控制性能.     

重型商用车辆质量估计算法研究

为精确估计重型卡车在预见性巡航控制过程中的质量,以车辆纵向动力学模型为基础,提出了车辆质量估计算法。利用卡尔曼滤波算法对发动机输出轴扭矩进行估计,并将其作为车辆质量估计算法的输入,基于递推最小二乘法对车辆质量进行了估计;对利用MATLAB/Simulink搭建的质量估计模型进行了C代码生成,并嵌入开发板中;最后对所提车辆质量估计算法进行了空载、1/3负载、满载实车道路试验。试验结果表明：所提算法在满载时的最大误差为8.87%,在1/3负载时的最大误差为7.43%,在空载时的最大误差为4.40%,能够满足车辆在预见性巡航控制过程中10%范围内的质量估计误差要求, 对车辆行驶的稳定性与安全性具有重要作用。     

Multi-objective stability control algorithm of heavy tractor semi-trailer based on differential braking

Rollover and jack-knifing of tractor semi-trailer are serious threats for vehicle safety,and accordingly active safety technologies have been widely used to reduce or prevent the occurrence of such accidents.However,currently tractor semi-trailer stability control is generally only a single hazardous condition (rollover or jack-knifing) control,it is difficult to ensure the vehicle comprehensive stability of various dangerous conditions.The main objective of this study is to introduce a multi-objective stability control algorithm which can improve the vehicle stability of a tractor semi-trailer by using differential braking.A vehicle controller is designed to minimize the likelihood of rollover and jack-knifing.First a linear vehicle model of tractor semi-trailer is constructed.Then an optimal yaw control for tractor using differential braking is applied to minimize the yaw rate and lateral acceleration deviation of tractor,as well as the hitch articulation angle of tractor semi-trailer,so as to improve the vehicle stability.Second a braking scheme and variable structure control with sliding mode control are introduced in order to achieve the best braking effect.Last Fishhook maneuver is introduced to the active safety simulation and the active control system effect verification.The simulation results show that multi-objective stability control algorithm of semi-trailer could improve the vehicle stability significantly during the transient maneuvers.The proposed multi-objective stability control algorithm is effective to prevent the vehicle rollover and jackknifing.     

Evaluation of fuel economy for a parallel hybrid electric vehicle

In this work, the fuel economy of a parallel hybrid electric vehicle is investigated. A vehicle control algorithm which yields operating points where operational cost of HEV is minimal is suggested. The operational cost of HEV is decided considering both the cost of fossil fuel consumed by an engine and the cost of electricity consumed by an electric motor. A procedure for obtaining the operating points of minimal fuel consumption is introduced. Simulations are carried out for 3 variations of HEV and the results are compared to the fuel economy of a conventional vehicle in order to investigate the effect of hybridization. Simulation results show that HEV with the vehicle control algorithm suggested in this work has a fuel economy 45% better than the conventional vehicle if braking energy is recuperated fully by regeneration and idling of the engine is eliminated. The vehicle modification is also investigated to obtain the target fuel economy set in PNGV program.     

Development of a washout algorithm for a vehicle driving simulator using new tilt coordination and return mode

A vehicle driving simulator is a virtual reality device which makes a man feel as if he drove art actual vehicle Unlike actual vehicles, the simulator has limited kinematical workspace and bounded dynamic characteristics So it is difficult to simulate dynamic motions of a multi-body vehicle model In order to overcome these problems, a washout algorithm which controls the workspace of the simulator within the kinematical limitation is needed However, a classical washout algorithm contains several problems such as generation of wrong sensation of motions by filters in tilt coordination, requirement of trial and error method in selecting the proper cutoff frequencies and difficulty in returning the simulator to its origin using only high pass filters This paper proposes a washout algorithm with new tilt coordination method which gives more accurate sensations to drivers To reduce the time in returning the simulator to its ougin, an algonthrn that applies selectively onset mode from high pass filters and return mode from error functions is proposed As a result of this study, the results of the proposed algorithm are compared with the results of classical washout algorithm through the human perception models Also, the performance of the suggested algorithm is evaluated by using human perception and sensibility of some drivers through experiments     

Algorithm for calculating torque base in vehicle traction control system

Existing research on the traction control system(TCS) mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS (referred to as the torque base in this paper), which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an algorithm is proposed to determine the torque base. First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop(HIL) simulation and vehicle tests emulating sudden start on low friction roads have been conducted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS.     

Real-time Tire Parameters Observer for Vehicle Dynamics Stability Control

The performance of the vehicle dynamics stability control system(DSC) is dominated by the accurate estimation of tire forces in real-time.The characteristics of tire forces are determined by tire dynamic states and parameters,which vary in an obviously large scope along with different working conditions.Currently,there have been many methods based on the nonlinear observer to estimate the tire force and dynamic parameters,but they were only used in off-line analysis because of the computation complexity and the dynamics differences of four tires in the steering maneuver conditions were not considered properly.This paper develops a novel algorithm to observe tire parameters in real-time controller for DSC.The algorithm is based on the sensor-fusion technology with the signals of DSC sensors,and the tire parameters are estimated during a set of maneuver courses.The calibrated tire parameters in the control cycle are treated as the elementary states for vehicle dynamics observation,in which the errors between the calculated and the measured vehicle dynamics are used as the correcting factors for the tire parameter observing process.The test process with a given acceleration following a straight line is used to validate the estimation method of the longitudinal stiffness;while the test process with a given steering angle is used to validate the estimated value of the cornering stiffness.The ground test result shows that the proposed algorithm can estimate the tire stiffness accurately with an acceptable computation cost for real-time controller only using DSC sensor signal.The proposed algorithm can be an efficient algorithm for estimating the tire dynamic parameters in vehicle dynamics stability control system,and can be used to improve the robustness of the DSC controller.     

Lateral control of autonomous vehicle by yaw rate feedback

In the autonomous vehicle, the reference lane is continually detected by machine vision system. And then the vehicle is steered to follow the reference yaw rates which are generated by the deviations of lateral distance and the yaw angle between a vehicle and the reference lane. To cope with the steering delay and the side-slip of vehicle, PI controller is introduced by yaw rate feedback and tuned from the simulation where the vehicle is modeled as 2 DOF and 79 DOF and verified by the results of an actual vehicle test. The lateral control algorithm by yaw rate feedback has good performances of lane tracking and passenger comfort.     

基于变预测时域MPC的自动驾驶汽车轨迹跟踪控制研究

为了保证自动驾驶汽车轨迹跟踪的精度及行驶过程中的稳定性,提出一种基于车辆横向稳定状态在线识别和模糊算法的变预测时域模型预测控制（MPC）方法。针对车辆稳定状态的在线识别,采用k-means聚类算法对车辆行驶状态参数进行聚类分析,得到聚类质心,通过在线对比当前车辆状态量与不同聚类质心之间的欧氏距离获取车辆的实时安全等级。同时计算出当前车辆的轨迹跟踪横向偏移量,以这二者为输入,通过模糊控制算法在线计算出预测时域的变化量并输出给MPC控制器实现预测时域的自适应调整,最后求解出自动驾驶车辆跟踪轨迹的最优的控制序列,以达到在保持车辆稳定的前提下实现高精度轨迹跟踪控制的目的。CarSim/Simulink联合仿真结果表明,改进后的变预测时域MPC算法在提高自动驾驶汽车轨迹跟踪精度及横向稳定性方面的表现优于传统MPC控制器。     

并联混合电动车辆采用无级变速器速比控制对燃油经济性的改进

考虑到并联混合电动车辆(HEV)动力系响应滞后,建议采用无级变速器(CVT)速比控制方法来实现HEV的燃油经济性的改进.在该方法内,由估算于动力系响应滞后之后根据车辆速度来修正目标CVT速比,并推荐一个加速图谱来估算响应滞后的车辆速度.该CVT速比控制方法采用HEV台架试验机试验证实.根据试验结果,可以看到用修正速比控制方法发动机工作迹线比用常规CVT速比控制对于适度加速模式可以有更有效换档范围,故能给出最佳的燃油经济性.此外,还采用HEV动力系模型对联邦城市驱动计划性能仿真进行估算响应滞后对燃油经济性的影响.仿真结果表明作为响应滞后采用修正CVT速比增大可以实现最佳的燃油经济性.但在实际应用中,要求最佳燃油经济性和加速性能之间进行折衷.     

燃料电池汽车动力系统功率平衡控制策略

燃料电池汽车动力总成控制的主要目的是平衡各个动力总成部件如燃料电池发动机、动力蓄电池和电动机之间的功率流向和能量平衡,使车辆保持较好的动力性和经济性。依据燃料电池汽车动力系统基本拓扑结构,提出了基于DC/DC变换器电流控制方式和基于模糊决策的蓄电池恒荷电状态控制的动力系统功率平衡控制算法,在MATLAB环境中进行了离线仿真,并用快速控制原型方法进行了实车试验验证。     

汽车方向预瞄式自适应PD控制算法

针对汽车动力学强非线性时变特性及驾驶员行为特性,基于预瞄跟随理论提出了汽车方向预瞄式自适应PD控制算法,并结合仿真计算和场地试验论证了算法的可行性和有效性。算法中建立了可近似描述汽车转向动力学特性的一阶线性参考模型,并实时在线地辨识了参考模型传递函数的参数;由此根据理想预瞄跟随器的结构,进行了PD控制器参数的自整定。该控制算法可较为精确地控制汽车跟随预期轨迹,且自适应控制算法的采用也提高了控制系统的鲁棒性和适应性,从而为智能汽车方向控制系统的研究提供了一条可行的研究途径。     

基于ADAMS模型的履带车辆半主动悬挂自适应控制

建立了某履带车辆ADAMS整车模型。搭建了控制算法MATLAB与实体模型ADAMS之间的联合仿真接口。提出了采用模糊控制器调整PID调节器参数实现基于ADAMS建模的整车半主动悬挂控制策略。用动行程及其变化率作为模糊控制器的输入,通过模糊控制器的输出动态调整PID调节器的参数,形成了车辆半主动悬挂自适应控制系统。仿真研究表明,该自适应控制系统能够有效协调加速度和动行程在不同频段的矛盾,明显改善履带车辆行驶的平顺性。     

基于AEKF的车辆质量与道路坡度实时估计

针对车辆在实际行驶过程中外界噪声的统计特性无法已知的问题,以车辆纵向动力学模型为基础,提出了自适应扩展卡尔曼滤波(adaptive extended Kalman filter,简称AEKF)的车辆质量及道路坡度估计算法。以动态估计车辆系统中的质量与坡度为研究对象,引入了旋转质量换算系数,建立车辆纵向动力学系统的状态空间模型,考虑了不同时刻的档位匹配与行驶特殊工况的处理。对系统状态方程进行离散化处理,得到系统状态方程与系统测量方程,在扩展卡尔曼滤波(extended Kalman filter,简称EKF)的基础上引入带遗忘因子的噪声统计估计器,通过AEKF对状态方程与测量方程实时更新,进行在线估计和校正噪声统计值,从而解决系统的噪声时变问题。本研究算法与EKF算法估计及实测结果的对比分析表明,本研究算法能够很好地对车辆质量和坡度信号进行有效滤波和估计,在短时间内逐渐收敛并逼近实测值,从而能够合理有效地检测车辆在行驶过程中的状态信息。     

汽车伪线性内模操稳控制策略建模与仿真

针对采用主动制动方式调节汽车操稳性能的系统提出了一种伪线性内模控制算法。首先建立估测算法确定汽车的车身侧偏角和车速,并建立了操稳控制的控制目标,然后引入四自由度车辆模型作为内模控制算法的内部模型,分析了由于制动而引起的非线性特性,并采用了逆系统方法将原来的非线性系统转化为伪线性系统,使得新系统的输入输出成线性关系,并基于此建立了内模控制器实现汽车操稳性能调节,最后采用主动转向和主动制动不同方式的汽车操稳控制系统进行了仿真比较,分析了各自的特点,并给出研究结论。