Establishment of Dynamic Model for Axle Box Bearing of High-Speed Trains Under Variable Speed Conditions

In this study,a dynamic model for the bearing rotor system of a high-speed train under variable speed conditions is established.In contrast to previous studies,the contact stress is simplifed in the proposed model and the compensation balance excitation caused by the rotor mass eccentricity considered.The angle iteration method is used to overcome the challenge posed by the inability to determine the roller space position during bearing rotation.The simulation results show that the model accurately describes the dynamics of bearings under varying speed profles that contain acceleration,deceleration,and speed oscillation stages.The order ratio spectrum of the bearing vibration signal indicates that both the single and multiple frequencies in the simulation results are consistent with the theoretical results.Experiments on bearings with outer and inner ring faults under various operating conditions are performed to verify the developed model.

Measured load spectra of the bearing in high-speed train gearbox under different gear meshing conditions

The load spectrum is a crucial factor for assess-ing the fatigue reliability of in-service rolling element bear-ings in transmission systems.For a bearing in a high-speed train gearbox,a measurement technique based on strain detection of bearing outer ring was used to instrument the bearing and determine the time histories of the distributed load in the bearing under different gear meshing conditions.Accordingly,the load spectrum of the total radial load car-ried by the bearing was compiled.The mean value and class interval of the obtained load spectrum were found to vary non-monotonously with the speed and torque of gear mesh-ing,which was considered to be caused by the vibration of the shaft and the bearing cage.As the realistic service load input of bearing life assessment,the measured load spectrum under different gear meshing conditions can be used to pre-dict gearbox bearing life realistically based on the damage-equivalent principle and actual operating conditions.

A fault prediction method for catenary of high-speed rails based on meteorological conditions

Fault frequency of catenary is related to meteo-rological conditions. In this work, based on the historical data, catenary fault frequency and weather-related fault rate are introduced to analyse the correlation between catenary faults and meteorological conditions, and further the effect of meteorological conditions on catenary oper-ation. Moreover, machine learning is used for catenary fault prediction. As with the single decision tree, only a small number of training samples can be classified cor-rectly by each weak classifier, the AdaBoost algorithm is adopted to adjust the weights of misclassified samples and weak classifiers, and train multiple weak classifiers. Finally, the weak classifiers are combined to construct a strong classifier, with which the final prediction result is obtained. In order to validate the prediction method, an example is provided based on the historical data from a railway bureau of China. The result shows that the mapping relation between meteorological conditions and catenary faults can be established accurately by AdaBoost algorithm. The AdaBoost algorithm can accurately predict a catenary fault if the meteorological conditions are provided.

Heat Source Analysis of Hard Disk Drives with Different Wall Conditions using Infrared System

Increasing performance parameters of hard disk drive (HDD) such as higher capacity and faster data access speed with decreasing physical size make HDD more susceptible to thermal effects. Contact temperature measurement using thermocouple is not suitable for the rotating platter of HDD. Heat analysis using simulation software requires accurate initial parameter setting such as thermal (initial & boundary) conditions of certain regions. Temperature measurement using infrared (IR) system avoids these limitations;it is non-contact, responsive and does not require initial parameter setting. Thermal pattern distribution can be studied from the thermal images. However, emissivity of the target has to be known and calibration of the system is essential for accurate temperature reading. This paper showed that temperature within the HDD increases with ambient temperature and time, but the thermal distribution pattern in the HDD was not affected by different ambient temperatures. Three wall boundary conditions were conducted to study the thermal distribution pattern in the HDD. A solution was then proposed based on the results obtained from the experiments to improve the heat transfer rate and steady state temperature, and reduce the detrimental effects from high thermal generation in future prototypes. Another important finding was that the averaged temperature of the head cap was generally higher compared to that of the disk, as the spindle motor is the primary heat source within the HDD. Heat source analysis of HDD with IR system allows designers to have better visibility of the temperature generated in different components of the HDD. Proper cooling may enhance disk life as well as ensure the stability and integrity of the system.

Modeling for Action of Recovering from Erroneous Driving Condition Based on Revised Decision Tree

Driving behavior modeling is very important in the research area of road traffic systems safety analysis. The characteristics of action of recovering from erroneous driving condition underlying road traffic accident or incident scenarios is quantitatively analyzed, the model of action of recovering from erroneous driving condition is set up according to the identification of erroneous driving condition and the measurement of correction from erroneous driving condition. And then, the probability of action of recovering from erroneous driving condition has been measured based on a revised decision tree. The measure process uses a combination of test data and subjective judgments of driving behavior. It can provide a very helpful theoretical basis for the further analysis of driving behavior in road traffic system.

Analysis of stress and natural frequencies of high-speed spatial parallel mechanism

In order to grasp the dynamic behaviors of 4-UPS-UPU high-speed spatial parallel mechanism, the stress of driving limbs and natural frequencies of parallel mechanism were investigated. Based on flexible multi-body dynamics theory, the dynamics model of 4-UPS-UPU high-speed spatial parallel mechanism without considering geometric nonlinearity was derived. The stress of driving limbs and natural frequencies of 4-UPS-UPU parallel mechanism with specific parameters were analyzed. The relationship between the basic parameters of parallel mechanism and its dynamic behaviors, such as stress of driving limbs and natural frequencies of parallel mechanism, were discussed. The numerical simulation results show that the stress and natural frequencies are relatively sensitive to the section parameters of driving limbs, the characteristic parameters of material on driving limbs, and the mass of moving platform. The researches can provide important theoretical base of the analysis of dynamic behaviors and optimal design for high-speed spatial parallel mechanism.

Emission Performance of Motorcycles in Real-Road Conditions

WMTC,which means a worldwide motorcycle testing cycle,is now regarded as the most possible choice for the global motorcycle emission testing cycle,but whether or not it can be used in China is still unknown.In this study,a large number of data on the speed-time trace of motorcycles were sampled from various kinds of roads in 5 cities in China.Based on a series of criterion numbers defined,the driving character of motorcycles in the real-road conditions of China was obtained.With the aid of a specially designed program,an emission testing cycle that can indicate the driving characteristics of motorcycle in the real-road conditions was synthesized,and the exhaust emission tests of 20 motorcycles under the synchronized cycle and WMTC were carried out based on a CVS system and a motorcycle chassis dynamometer.The results show that although there do exist differences in some criterion numbers between the real-road condition and WMTC,such as proportion of idling mode,mean speed,mean running speed and the average acceleration and deceleration rates,the driving behaviors are similar.The results of exhaust emission tests indicate that the emission values of motorcycles under the synchronized cycle and WMTC have a relatively strong correlation.This means that WMTC can be introduced as a standard motorcycle emission test regulation into China.

Characteristics of interior noise of a Chinese high-speed train under a variety of conditions

This paper presents an investigation into the characteristics of interior noise of a Chinese high-speed train under several typical conditions. Interior noises within Vehicle TC01, which can be used as a head car or an end car, and Vehicle TP03, the third car counting from TC01, are measured for the train running at speeds from 260 km/h to 385 km/h, along two types of track including a slab track and a ballast track and either on the ground surface or in a tunnel. Data analyses are performed for sound pressure overall levels, frequency, area contributions, and possible generation mechanisms, showing how they are affected by train speed, running direction, track type, and tunnel. The results show that, whether TC01 is used as head car or end car, the interior noise characteristics in the VIP cabin are mostly related to aerodynamic noise. Differences in interior noise between tracks become smaller as the train speed increases. The effect of a tunnel on the interior noise is more important for the middle coach than that for the head coach. This study can provide a basis for noise control of high-speed trains.

Development and stability analysis of a high-speed train bearing system under variable speed conditions

During a high-speed train operation,the train speed changes frequently,resulting in motion change as a function of time.A dynamic model of a double‐row tapered roller bearing system of a high-speed train under variable speed conditions is developed.The model takes into consideration the structural characteristics of one outer ring and two inner rings of the train bearing.The angle iteration method is used to determine the rotation angle of the roller within any time period,solving the difficult problem of determining the location of the roller.The outer ring and inner ring faults are captured by the model,and the model response is obtained under variable speed conditions.Experiments are carried out under two fault conditions to validate the model results.The simulation results are found to be in good agreement with the results of the formula,and the errors between the simulation results and the experimental results when the bearing has outer and inner ring faults are found to be,respectively,5.97% and 2.59%,which demonstrates the effectiveness of the model.The influence of outer ring and inner ring faults on system stability is analyzed quantitatively using the Lempel–Ziv complexity.The results show that for low train acceleration,the inner ring fault has a more significant effect on the system stability,while for high acceleration,the outer ring fault has a more significant effect.However,when the train acceleration changes,the outer ring has a greater influence.In practice,train acceleration is usually small and does not frequently change in one operation cycle.Therefore,the inner ring fault of the bearing deserves more attention.

Fault Detection for PMSM Motor Drive Systems by Monitoring Inverter Input Currents

This paper has proposed a fault detecting method for DC supplied permanent magnet synchronize motor(PMSM)drive systems by monitoring the drive DC input current.This method is based on the fault signal propagation from the torque disturbance on the motor shaft to the inverter input currents.The accuracy of this fault signal propagation is verified by the Matlab simulation and experiment tests with the emulated faulty conditions.The feasible of this approach is shown by the experimental test conducted by the Spectra test rig with the real gearbox fault.This detection scheme is also suitable for monitoring other drive components such as the power converter or the motor itself using only one set of current transducers mounted at the DC input side.

某纯电驱动重载车辆能耗预测模型

高精度能耗预测模型是准确预测车辆续驶里程的重要前提。针对载荷大幅度变化且非结构化道路运行的纯电驱动重载车辆,建立其组合能耗模型,该模型由能耗计算基本模型与长短时记忆(Long Short-Term Memory,LSTM)神经网络差值修正两部分组成。基于能量流动过程驱动电机和变速器效率建模,结合汽车行驶动力学建立能耗计算基本模型;采用LSTM神经网络来修正基本模型能耗预测结果与车辆典型工况功率测试值的差值,有效提高了大幅变载荷且低信噪比坡度环境下的车辆能耗预测精度,因此组合能耗模型具有参数简单和模型拟合不需解释能耗规律的优点。经试验测试分析,与VT-Micro能耗模型和径向基(Radial Basis Function,RBF)神经网络能耗模型相比,所提组合能耗模型的功率预测平均误差率分别降低了17.76%和3.35%,能够实现纯电驱动重载车辆复杂工况下能耗的准确实时预测。

城市道路网联混驾车辆分阶段动态轨迹控制方法

随着城市的进步和不断发展,智能驾驶车辆逐渐代替路段中的部分人工驾驶车辆,但在未来较长时间内人工驾驶车辆并不会被完全取代,此时出现网联车与人工驾驶车辆的混驾环境,即目前以及未来时间内我们面临的驾驶环境。网联车与人工驾驶车辆驾驶行为在路段内相互干扰,造成混合车流行驶效率低下。为减弱2种车辆间的相互作用,提出一种分离混驾环境下网联车和人工驾驶车辆的分阶段动态车道引导算法(dynamic lane guidance algorithm for separating CAVs and HDVs in mixed traffic environment,SCHME)。通过该算法分离在交叉口上游路段的混合流车辆集合,调整智能驾驶车辆的行驶路线并进行实时动态更新,在满足运动学约束收敛的条件下,人工驾驶车辆根据网联车的动态路线进行相应调整,实现在每辆车广义安全损失成本最小的情况下提高路段内混驾环境下车辆运行效率。通过MATLAB模拟车辆在进入交叉口前的车辆运行状态,结果表明,SCHME算法可在广义安全损失成本最小的情况下提高路段内平均车辆通行效率(17.29%),同时当车辆优化数组越大,车辆集合距离交叉口越远时,智能驾驶车辆渗透率越低,每辆车的道路广义安全损失成本越低。

基于设计运行条件的实际道路测试场景复杂度计算模型

自动驾驶车辆在实际道路行驶的安全性与外部交通要素、驾驶员状态以及本车状态密切相关。自动驾驶面临的一大难题是实际交通环境具有道路形态、自然环境、交通参与者及事件等在时间和空间维度的随机性特征,测试场景复杂度存在的差异造成了自动驾驶测试过程的不可复现性和测试结果的不可对比性,导致自动驾驶评价缺乏统一量化的测试环境基准。本文提出了一种基于设计运行条件的实际道路测试场景复杂度计算模型,系统考虑了网联功能、驾驶员感知能力、本车执行能力对自动驾驶车辆在实际道路中面临相关场景时的复杂度影响,建立了以道路等级、交通设施、临时交通变化、交通参与者、自然环境、网联信息、驾驶员状态和本车状态等8个要素大类为基础的自动驾驶实际道路测试场景复杂度计算模型要素库,建立了基于设计运行条件和层次分析法的自动驾驶功能实际道路测试场景复杂度计算模型。采用基于智能化网联化的技术逻辑影响传递机制计算场景要素权重系数,并在实际道路测试中验证了本文方法的可行性和合理性。

计及驾驶风格的氢燃料电池有轨电车自适应能量管理策略

半独立路权运行模式下,氢燃料电池混合动力有轨电车驾驶员的驾驶风格影响锂电池荷电状态,从而对整车运行经济性有较大影响。提出一种结合驾驶员驾驶风格的自适应能量管理策略,以提高能量管理策略对工况和驾驶风格的适应性。首先,考虑不同的道路工况对驾驶员驾驶风格的影响,通过K-均值聚类算法对行驶工况进行识别,将行驶工况分为低速、中速、高速3类;引入冲击度和加速度标准差构建基于模糊逻辑的算法,对驾驶风格进行识别,将驾驶风格分为迟钝型、标准型、激进型3类。其次,建立系统瞬时氢耗量最优的目标函数,在满足约束条件的前提下,引入锂电池荷电状态等效因子修正系数,针对不同驾驶风格调整传统等效氢耗最小策略中相应的等效因子,以实现等效因子随驾驶风格的改变实时变化。最后,将该策略与传统等效氢耗最小策略、庞特里亚金极小值策略进行仿真对比分析,结果表明:该策略能实现3个动力源功率分配最优;锂电池和超级电容荷电状态波动曲线相较于其他2种策略最为平滑;在续驶里程结束时混合动力系统氢耗量为1.39 kg,具有最为优越的燃油经济性;母线电压最大偏移率最小;能使3个动力源平稳出力,具有较强的系统稳定性。研究结果为进一步提高有轨电车实际运行中对驾驶风格的适应性提供参考。

分布驱动无人车在极限工况下的稳定跟踪控制

针对分布式驱动无人车在低附着、高速的极限工况下行驶时偏离目标路径和失稳的现象,提出一种稳定-跟踪联合控制策略,策略包含路径跟踪控制和横向稳定控制,使无人车在提高跟踪精度的同时又使其稳定性得到保障。路径跟踪模块在汽车二自由度模型的基础上,建立了最优LQR路径跟踪控制器,并引入前馈用以改善稳态误差,其次考虑误差变化的规律和路-车位置关系以及驾驶员预瞄模型,设计了改进的权重参数自适应LQR控制器;稳定性模块基于可以减小系统抖振的滑模模糊控制原理,并结合汽车稳定性参数的实际值与期望值的差值,求解出横摆力矩。其次在分配各轮转矩时建立约束条件,使得轮胎负荷率最小用以提升汽车的操纵稳定性。CarSim/Simulink仿真表明在高速、低附着的换道工况下,改进后的LQR控制器有效地改善跟踪误差,具有良好的鲁棒性。且在加入稳定性控制器后,横摆角速度与质心侧偏角的调节时间变短,极大改善了无人车在极限工况下的稳定性。

纯电动公交车驾驶行为对能耗的影响研究

为深入了解城市纯电动公交车驾驶特性及能耗规律,采集其自然驾驶数据,从运行工况、速度、加速度、踏板开度4个方面分析驾驶行为特征。其次,利用相关性分析寻找影响纯电动公交车能耗的因素,从速度、加速度、运行状态、典型工况4个方面分析驾驶行为对能耗的影响规律。分析结果表明,纯电动公交车能耗与速度呈U型变化曲线,与匀速工况占比呈线性负相关,与加减速工况占比呈二次函数关系;存在能量回收最大的加速度区间;典型工况能耗占公交循环总能耗的82.36%。最后,依据分析结论提出纯电动公交车节能驾驶建议,旨在指导公交车驾驶人降低行车能耗。

多工况下的液驱多维力加载装置主轴速度控制

不同工况引起加载力之间的耦合效应降低了速度控制效果,为了更加精准控制不同工况下的主轴速度,提出一种多工况下的液驱多维力加载装置主轴速度控制方法。计算多工况下的液驱多维力加载装置主轴速度,以此作为控制器设计输入。在多种工况下,将液驱多维力加载装置主轴输入和输出速度之间的差值作为输入信号,通过模糊推理算法改进经典PID控制器,通过模糊检测调整改进后的控制器组建模糊自适应PID控制器,实现速度自适应控制。通过实验测试证明,所提方法可以精准地完成液驱多维力加载装置主轴速度控制,受工况影响较小。

基于改进PSO-LSTM算法的风电机组状态监测方法研究

通过改进粒子群算法(particle swarm optimization,PSO)优化长短期记忆神经网络算法(long short-term memory,LSTM)的参数,提出了一种基于改进PSO-LSTM算法的直驱式风电机组运行状态监测方法。首先将数据采集与监控系统(supervisory control and data acquisition,SCADA)采集到的数据利用随机森林的方法进行特征筛选,得到模型的输入参数;其次采用改进PSO-LSTM网络建立有功功率的预测模型,计算出预测值与实际值的残差,根据残差的分布来确实直驱式风电机组的状态;最后利用某风电机组SCADA数据对所提预测模型进行验证分析,结果表明,PSO-LSTM预测模型相比其他三种预测模型,具有较高的预测精度,并在状态异常后最短时间内发出故障警报,保证电场的健康稳定运行。

电磁感应加热装置中磁-热-流耦合特性分析

采用磁热流多元物理场耦合仿真的方法,研究感应加热系统中的不同线圈结构、激励条件下壁面欧姆损失、温度特征值、磁场强度等多物理场相关的特征值,由结果可知:线圈结构以及激励条件会对磁场及温度场产生不同程度的影响,壁面的欧姆损失与电流幅值、电流频率、线圈匝数呈正相关,与线圈与管道中心的距离呈负相关;随着电流幅值从100 A升高至180 A,壁面加热功率从167 W提升至3223 W,出口平均温度从20.5℃提升至28.6℃;管壁内的电流密度以及磁通密度会随着线圈内电流频率的增加而更加集中于管壁薄层内;随着线圈频率从0.05 kHz提升至20 kHz,不锈钢表层内的最大电流密度将从1.29×10^(6)A/m^(2)升高至1.25×10^(8)A/m^(2);当电流频率为0.05 kHz时,最大磁通密度为0.5 T;当电流频率为20 kHz时,最大磁通密度为4.8 T。

基于工况序列寻优的列车节能操纵策略优化

传统“三阶段”“四阶段”工况序列的列车操纵模式难以满足城市轨道交通复杂线路条件下的列车节能运行需求,本文提出一种基于工况序列寻优的列车节能操纵策略优化方法。将物理区间离散为多个等距离子区间,建立工况序列与子区间之间的映射关系,以区间总牵引能耗和运行时间最小化为目标构建列车节能操纵策略多目标优化模型。为提高模型求解效率,改进非支配排序遗传算法的交叉算子和距离算子,通过离散仿真求解列车节能操纵策略集。以福州地铁1号线的两个典型区间为对象进行案例分析,结果表明,相比传统操纵模式,优化后列车牵引能耗平均降低约19%。本文方法通过合理选择算法参数能够有效构建适应不同线路条件的运行工况序列,生成秒级运行时间划分下的列车节能操纵策略集。