A Promising Distance-Based Gasoline Tax Charging System Based on Spatio-Temporal Grid Reservation in the Era of Zero-Emission Vehicles

Fuel taxes are still a primary funding source for the development and maintenance of transportation infrastructure. Such a tax is collected as a flat fee from the importer or producer of the taxable fuel product. Fuel-efficiency improvements and the adoption of zero-emission vehicles result in a continuous decrease in gasoline tax revenues. This paper proposes a novel distance-based alternative method to replace current gasoline tax collection systems in Japan by providing a software architecture platform. In this platform, we utilize driving information gathered via communication mechanisms installed in connected automated vehicles to develop a system that collects gasoline tax based on reserving spatio-temporal grids. Spatio-temporal sections are created by dividing space and time into equal grids and a designated tax charge is assigned. Connected automated vehicles reserve a planned travel route in advance and travel based on reservation information. The performance evaluation results indicate that the proposed system adequately reserves the requested grids and accurately collects gasoline taxes based on a spatio-temporal grid with minimum communication time and no data package loss. The proposed method is based on micro travel distance charges, which generates gasoline tax revenue by 5.7 percent for model year 2022 and 21.8 percent for model year 2030 as compared to the current flat-fee system.

General Torsional Stiffness Matching of Off-road Vehicle

Increasing frame torsional stiffness of off-road vehicle will lead to the decrease of body torsional deformation, but the increase of torsional loads of frame and suspension system and the decrease of wheel adhesive weight. In severe case, a certain wheel will be out of contact with road surface. Appropriate matching of body, frame and suspension torsional stiffnesses is a difficult problem for off-road vehicle design. In this paper, these theoretically analytic models of the entire vehicle, body, frame and suspension torsional stiffness are constructed based on the geometry and mechanism of a light off-road vehicle＇s body, frame and suspension. The body and frame torsional stiffnesses can be calculated by applying body CAE method, meanwhile the suspension＇s rolling angle stiffness can be obtained by the bench test of the suspension＇s elastic elements. Through fixing the entire vehicle, using sole timber to raise wheels to simulate the road impact on a certain wheel, the entire vehicle torsional stiffness can be calculated on the geometric relation and loads of testing. Finally some appropriate matching principles of the body, frame and suspension torsional stiffness are summarized according to the test and analysis results. The conclusion can reveal the significance of the suspension torsional stiffness on off-road vehicle＇s torsion-absorbing capability. The results could serve as a reference for the design of other off-road vehicles.

Dynamic Characteristics of Tracked Vehicle Power Train Considering Road Random Torsional Excitation

The road random torsional excitation is one type of torque rooted from the road roughness and vehicle drive system. This paper aims to study how the road random torsional excitation affects the dynamic characteristics of vehicle power train. The method of simulating the random torsional excitation of tracked vehicle is explored at first. Secondly,the road random torsional excitations under different road roughness,vehicle speeds and pre-tensions are obtained. Thirdly,the dynamic analysis model of tracked vehicle power train is constructed with the consideration of the road random torsional excitation. Eventually,the influences of this excitation on output torque,bearing support force,vibration acceleration and dynamic shear stress of transmission shafts are intensively studied.The research conclusions are helpful to correct and refine the present virtual prototype of tracked vehicle power train.

Applications of Serial-Parallel Compensated Resonant Topology in Wireless Charger System Used in Electric Vehicles

There are lots of factors that can influence the wireless charging efficiency in practice, such as misalignment and air-gap difference, which can also change all the charging parameters. To figure out the relationship between those facts and system, this paper presents a serial-parallel compensated(SPC) topology for electric vehicle/plug-in hybrid electric vehicle(EV/PHEV) wireless charger and provides all the parameters changing with corresponding curves. An ANSYS model is built to extract the coupling coefficient of coils. When the system is works at constant output power, the scan frequency process can be applied to wireless power transfer(WPT) and get the resonant frequency. In this way, it could determine the best frequency for system to achieve zero voltage switching status and force the system to hit the maximum transmission efficiency. Then frequency tracking control(FTC) is used to obtain the highest system efficiency. In the paper, the designed system is rated at 500 W with 15 cm air-gap, the overall efficiency is 92%. At the end, the paper also gives the consideration on how to improve the system efficiency.

Electromechanical Aspects of an Experimental Hybrid Vehicle

The design and construction of an experimental solar hybrid vehicle based on the combination of photovoltaic solar energy as the main source of electricity and electric power supplied by a generator activated by the driver＇s pedaling is introduced. The vehicle has a battery to store the energy provided by both systems. The development was motivated by a Latin American solar car race through the Atacama Desert in Chile and the initiative to promote the use of clean energy for transport. A general description of the vehicle, its energetic aspects and experimental results are presented.

Influence of highway space alignment continuous degradation in 3- dimensional space on autonomous vehicle trajectory deviation based on PreScan simulation

The advent of autonomous vehicles(AVs)is expected to transform the current transportation system into a safe and reliable one.The existing infrastructures,operational criteria,and design method were developed to meet the requirements of human drivers.However,previous studies have shown that in the traditional horizontal and vertical combined design methods,where the two-dimensional alignment elements change,there are varying changes in curvature and torsion,which cause the continuous degradation of the spatial curve and torsion.This continuous degradation will inevitably cause changes in the trajectory of Autonomous Vehicles(AVs),thereby affecting driving safety.Therefore,studying the characteristics of autonomous vehicles trajectory deviation has theoretical significance for optimizing highway alignment safety design.Driving simulation tests were performed by using PreScan and Simulink to calibrate the lateral deviation.A machine learning approach called the Gradient Boosting Decision Tree(GBDT)algorithm was implemented to build a model and express the relationship between space alignment parameters and lane deviation.The results showed that the AV’s driving trajectory is significantly affected by the space alignment factors when the vehicle is driving in the inner lane,the downhill section,and the left-turn section.These findings will provide a novel perspective for road safety research based on autonomous vehicle driving trajectories.

日野推出世界首款混合动力重型商用车——“Profia Hybrid”

面向全球绿色低碳经济发展需求,重型商用车是道路交通运输行业CO_2减排的重要组成部分。商用车电动化是实现2050年CO_2零排放的主要技术途径,考虑到市场需求、技术成熟度等多种实际因素,混合动力技术是未来商用车的一个较好的过渡技术方案。日野公司2019年将推出世界上第一台搭载混合动力系统的重型卡车"Profia Hybrid"。该款车型采用并联式混合动力系统以及基于人工智能(AI)的控制系统,能够有效改善燃油经济性与CO_2排放。

一种电动汽车驱动系统扭转振动扭矩梯度控制方法

本文提出一种电动汽车驱动系统扭转振动扭矩梯度控制方法。该方法引入RBF神经网络计算扭矩变化率梯度限制值,利用扭矩变化率限制值对驱动电机的输出扭矩进行限制,以此防止扭矩突然变大所造成的传动系统各轴段的过度扭转,从根源上消除引起驱动系统扭转振动的问题。与传统扭转振动控制方法不同,文章提出的控制方法面向实际工程应用,不依赖于车辆简化的二阶质量模型以及车辆参数,避免由于模型及车辆参数精度问题对控制效果造成的不良影响,具有优良的实际工程应用价值。最后,文章通过实车试验的方式对该方法的可行性及有效性进行验证。

扭转减振器式全地形车悬架系统设计及舒适性研究

为解决履带式全地形车辆舒适性及抗冲击性能差的问题,提出一种含弧弹簧阻尼结构的扭转减振器式悬架系统,设计了单负重轮悬架系统并开展动力学建模与舒适性分析,研究了不同工况下整车舒适性及抗冲击性能。研究发现:①单负重轮悬架系统静、动态特性参数值均在合理的范围内;相同路面车速增加时,单负重轮悬架系统车身垂向加速度和悬架动挠度均方根的相对增长率降低;路面等级、车速增加时,单负重轮悬架系统车身垂向加速度传递率(8.5%~6.5%)以较小的数值呈小幅下降趋势。②整车通过D、E级路面和极端路面时,所提悬架系统相对传统扭杆弹簧悬架系统表现出优良的舒适性和抗冲击性,验证了悬架设计方案的正确性和有效性。

IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.

基于非线性能量阱的汽车传动系统扭振抑制研究

对非线性能量阱(nonlinear energy sink, NES)在汽车传动系统扭振抑制中的应用进行了研究。根据传动系统的结构和振动特点,建立了简化的3自由度传动系统-NES耦合动力学模型;基于增量谐波平衡法联合增量弧长法,推导并求解了耦合系统的频率响应,利用Floquet理论对周期解的稳定性进行判断;在频域和时域上对系统的非线性动力学响应及其影响因素进行了分析,并基于能量谱研究了NES的减振性能;最后,基于扩展的5自由度非线性模型对NES进行了参数优化和验证。结果表明,NES的减振性能受其自身刚度、阻尼及发动机激励幅值影响,合理设计NES参数可以高效抑制汽车传动系统的扭转共振,而不恰当的NES参数会促使系统发生高分支周期响应,导致异常振动峰值出现,经优化后的NES可以仅5%的惯量比使传动系统转速波动均方根值降低41.3%,减振效果显著。该研究可为NES在传动系统扭振抑制中的应用及其参数设计提供参考。

一种改进的车载组合导航零速检测及运动约束方法

零速修正在抑制车载惯性导航系统误差发散方面具有重要作用,普适准确的零速检测方法是实现零速修正的关键。针对传统零速检测方法在复杂环境下易受扰动、检测准确率低的问题,提出了一种改进的车载组合导航零速检测及运动约束方法。首先,归纳总结了基于速度和惯性测量装置数据的几种典型的零速检验方法,并分析了各种方法的优缺点;其次,设计了融合陀螺仪模值检验统计量和水平速度检验统计量的零速检测方案;最后,对所提方法进行了实验验证。实验结果表明,城市环境下所提方法的检测准确率为99.222%,漏检率为0.628%,误检率为1.366%。相较于基于速度的零速检测方法,准确率提高了8.000%,漏检率和误检率分别降低了8.793%和4.901%,速度精度平均提升了32.49%,姿态精度平均提升了28.69%。

基于准零刚度的坦克装甲车辆半主动惯容悬架控制策略

为了提高坦克装甲车辆悬架系统的减振性能,提出“惯容-弹簧”准零刚度的基本架构,以惯容、弹簧、阻尼三元件并联作为悬架构型,对惯容连续控制和惯容开关控制两种方案进行动力学仿真和参数优化。研究结果表明:采用准零刚度控制策略后,车体振动加速度大幅度减小,乘坐舒适性改善明显,同时降低了对阻尼系数的需求,提升了减振效率。通过分析悬架减振过程中各元件的瞬时功率,发现可变惯容起能量补偿作用,使一部分振动能量在弹簧和惯容之间反复动态地传递和转换,突破了弹簧缓冲储能、阻尼生热耗能的传统减振机理,达到了更好的减振效能。

基于深度学习的高超声速飞行器执行器零样本故障辨识

近年来,基于深度学习的故障诊断已经通过大量数据进行了深入的研究.然而,深度学习技术的巨大成功是基于可以获取大量带标签的训练样本的假设.在实际问题中,经常面临数据不平衡、标记的数据太少或没有数据的情况.基于此,本文研究了高超声速飞行器在零样本情况下的故障辨识问题.考虑飞控系统执行器故障,运用深度学习技术来识别特定故障类型(失效故障或卡死故障).“零样本”指的是在故障诊断的深度学习模型构建中,未曾包含或引入任何与目标故障相关的样本数据.因此,该模型必须依赖于其他方法和特征来推断和准确识别这些未知故障,以实现有效的故障辨识.针对这一问题,使用人工定义的故障描述来表征未知故障.具体而言,即利用关系网络学习将已知故障样本与定义的未知故障描述进行比较.进一步,为实现特征提取,结合卷积神经网络及长短期记忆神经网络,构建深度神经网络结构.最后,在Winged-cone(翼椎体)构型的高超声速飞行器上进行零样本故障辨识实验,结果表明在没有目标故障样本的情况下,所设计的算法可以完成对目标故障的诊断工作.

一种面向车联网的零日攻击检测方法

由于缺乏攻击数据,车联网零日攻击检测通常采用基于异常的方法。但车辆实际行驶过程中环境复杂多样、行为模式多变,导致正常的行为模式会出现较大的差异,采用基于异常的方法容易导致高误报率。在车联网环境中零日攻击和已知攻击的攻击原理相似,受迁移学习的启发,基于条件生成对抗网络提出一种应用少样本学习的车联网零日攻击检测方法。首先,提出一种多生成器和多判别器的条件对抗生成网络模型。其次,设计了一种自适应采样数据增强方法,通过对已知的攻击样本进行数据增强优化该网络模型的输入样本以减少误报。为进一步缓解该网络模型的输入攻击样本过少带来的数据不平衡问题,在判别器中给出了一种协作焦点损失函数重点判别难分类数据。最后,基于F2MD车辆网络仿真平台进行了大量实验,实验结果表明所提方法对于零日攻击的检测效果和检测延迟均优于现有方法,为车联网零日攻击检测提供了一种有效的解决方案。

应对零日攻击的混合车联网入侵检测系统

现有机器学习方法在面对零日攻击检测时,存在对样本数据过度依赖以及对异常数据不敏感的问题,从而导致入侵检测系统(IDS)难以有效防御零日攻击。因此,提出一种基于Transformer和自适应模糊神经网络推理系统(ANFIS)的混合车联网入侵检测系统。首先,设计了一种数据增强算法,通过先去除噪声再生成的方法解决了数据样本不平衡的问题;其次,将非线性特征交互引入复杂的特征组合,设计了一个特征工程模块;最后,将Transformer的自注意力机制和ANFIS的自适应学习方法相结合,以提高特征表征能力,减少对样本数据的依赖。在CICIDS-2017和UNSW-NB15入侵数据集上将所提系统与Dual-IDS等先进(SOTA)算法进行比较。实验结果表明,对于零日攻击,所提系统在CICIDS-2017入侵数据集上实现了98.64%的检测精确率和98.31%的F1值,在UNSW-NB15入侵数据集上实现了93.07%的检测精确率和92.43%的F1值,验证了所提算法在零日攻击检测方面的高准确性和强泛化能力。

建筑-交通-能源(BVG)融合的探索应用

随着国家双碳战略的推进,建筑、交通、能源等行业的绿色化、低碳化转型稳步推进。建筑-交通-能源(BVG)融合发展,为建筑行业的低碳化发展提供了前所未有的发展机遇。本文以惠州中建科工绿色科技零能耗办公楼为例,进行了具体的分析与判断。结果显示,光储直柔及建筑-交通-能源(BVG)融合发展,可以降低建筑碳排放,具有重要的意义。

某汽车传动系扭振测试、诊断与数据处理分析

针对某轻型卡车由传动系扭振导致加速过程中驾驶室内出现异常振动与轰鸣噪声现象进行研究。首先,为弄清车内振动噪声产生机理,对整车的扭振和车内振动噪声进行了实车道路试验;其次,对整车试验异常数据进行后处理,通过低通滤波和设置电压波动缓冲区的方法对其进行去噪和再生成,消除了加速工况下转速曲线失速和异常峰值的现象。通过分析转速、振动和噪声数据得出:样车加速过程中发动机2阶激励频率达到整车传动系的固有频率时,引起了传动系扭转共振,连同传动轴的不平衡转动自振,通过悬置、中间支撑和后桥板簧传入到车内,引起驾驶室异常振动和轰鸣噪声。试验分析的结果表明,该文对传动系扭振的测试、诊断和异常数据的处理方法是正确的,可以为汽车传动系扭振测试研究提供参考。

考虑转矩脉动的电动汽车传动系统扭转振动抑制

车用电机低频转矩脉动极易引发电驱动传动系统的扭转振动,降低电动汽车的驾乘体验。采用集中参数法建立典型电驱动传动系统动力学模型,获取传动系统在转矩脉动作用下的扭转振动频率分布规律;利用电机有限元仿真获取电机转矩脉动在齿槽、铁心磁饱和、磁场非正弦等因素作用下的数值解,并建立以定子电流为变量的转矩脉动精确解析模型;提出削弱低频转矩脉动的参考电流谐波设计与电流谐波闭环控制方法,实现电驱动传动系统扭转振动的主动抑制;在MATLAB/Simulink中完成电机转矩脉动模型与传动系统动力学模型的联合仿真,验证所述传动系统扭转振动特性分析与主动抑制的有效性。

轨道车辆车钩多元载荷识别与测量方法探讨

重载货车运行速度和载重的提升对车钩性能的要求更高,需要获取车钩在纵向、横向、垂向的实际载荷谱。然而,传统监测技术无法满足需求,因此,提出一种多元载荷解耦的温度自补偿全桥测量技术,通过建立理论模型、布置应变阵列和组桥设计,实现各钩面应变的精确测量与零漂补偿,最后通过试验验证技术的有效性。此种测量技术为轨道车辆车钩载荷监测提供了科学手段。