Factors Influence Hanoians’ Choice of Non-Motorized Transport Mode to Access Bus Stations

Hanoi’s rapid urbanization has led to a surge in private vehicle ownership, particularly motorcycles, amidst inadequate public transportation infrastructure. Despite government efforts, many still prefer motorized transport, citing mobility and safety concerns, exacerbated by insufficient pedestrian infrastructure. This study examines the motivations behind this reliance on motorized vehicles, particularly motorcycles, in Hanoi. Findings reveal safety and convenience as primary factors driving motorized transport use, especially for accessing bus stations. Economic incentives could promote non-motorized travel and public transport adoption. Policy implications highlight the importance of addressing economic factors and improving access infrastructure to manage motorized vehicle reliance and foster sustainable urban mobility in Hanoi.

Connected and Autonomous Vehicles (CAVs) Challenges with Non-motorized Amenities Environments

With the deployment of Connected and Automated Vehicles in the coming decades,road transportation will experience a significant upheaval.CAVs(Connected and Autonomous Vehicles)have been a main emphasis of Transportation and the automotive sector,and the future of transportation system analysis is widely anticipated.The examination and future devel­opment of CAVs technology has been the subject of numerous researches.However,as three essential kinds of road users,pedestrians,bicyclists,and motorcyclists have experienced little to no handling.We explored the influ­ence of CAVs on non-motorized mobility in this article and seven various issues that CAVs face in the environment.

Research on Electro Hydraulic Proportional Control for Heavy Vehicle Blend Braking System

A blend braking system of heavy vehicle was proposed.The main control part of the system is the electro hydraulic proportional servo valve.A nonlinear model of brake cylinder controlled by the valve was deduced through the analysis of its control property and system feature.The transfer function of the system was also proposed,and the hydraulic inherent frequency and the PID closed-loop system feature were calculated.The simulated result is consistent with those tested in the bench and on the site with 50 t heavy vehicle.The experimental result shows that the control method has quick response and high precision.

Investigation and Optimization of Priority for Non-motor Vehicles in the Old Urban Area of Nanchang

Under the background of"people-oriented"thought and"green transportation",the idea of"priority for non-motor vehicles"came into being,which can improve the riding environment of non-motor vehicle riders to a certain extent.According to the current situation of priority for non-motor vehicles in the old urban area of Nanchang,through field investigation,questionnaire investigation and interview,this study summarized the existing problems,and put forward optimization suggestions for these problems,in order to provide reference for areas with similar conditions.

Fuzzy Self-adaptive Proportional Integration Differential Control for Attitude Stabilization of Quadrotor UAV

The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.

Simulation study on starting of dual clutch transmission for tracked vehicles

In order to study the application of dual clutch transmission （DCT） on tracked vehicles, a simulation moclel and two control methods were performed for starting analysis. Based on a certain transmission of an existing tracked vehicle, a DCT structure was proposed. Matlab/Simulink was a dopted as a platform to develop the simulation model. The engine speed was controlled to follow the target speed as a launch strategy. Two control methods, a proportional integral derivative （ PID ） control method and a fuzzy control method, were proposed to control the engine throttle and oil pressure in order to track the target engine speed. Simulation results show that either the PID control or fuzzy control method can improve the starting performance compared with no loop control meth od. Fuzzy control method can lead a better starting quality compared with PID control method.

Modeling and Control of Parallel Hybrid Electric Vehicle Using Sea-Lion Optimization

This paper develops a parallel hybrid electric vehicle(PHEV)propor-tional integral controller with driving cycle.To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles(HEVs)combine an electric motor(EM),a battery and an internal combustion engine(ICE).The electric motor assists the engine when accelerating,driving longer highways or climbing hills.This enables the use of a smaller,more efficient engine.It also makes use of the concept of regenerative braking to maximize energy efficiency.In a Hybrid Electric Vehicle(HEV),energy dissipated while braking is utilized to charge the battery.The proportional integral controller was used in this paper to analyze engine,motor performance and the New European Driving Cycle(NEDC)was used in the vehicle driving test using Matlab/Simulink.The proportional integral controllers were designed to track the desired vehicle speed and manage the vehi-cle’s energyflow.The Sea Lion Optimization(SLnO)methods were created to reduce fuel consumption in a parallel hybrid electric vehicle and the results were obtained for the New European Driving Cycle.

磁力馈能主动悬架稳定性分析

为了提高车辆行驶平顺性和安全性,提出了一种新型磁力馈能主动悬架,并研究其稳定性。采用BP神经网络PID控制算法(BP-PID)搭建磁力馈能主动悬架控制系统,利用MATLAB/Simulink进行理论仿真。建立B级和C级随机路面,仿真分析不同速度、不同等级下,磁力馈能主动悬架的稳定性。结果表明,相比于被动悬架效果和PID控制的磁力馈能主动悬架效果,采用BP-PID控制可明显提高悬架稳定性。B级随机路面60 km/h时车身垂直加速度改善了45.90%,证明了BP-PID控制的合理性,可有效提升悬架稳定性。

基于比例继动阀的解耦式制动能量回收

针对纯电动商用车在连续制动时,气源压力偏低会导致驱动轴耦合制动力响应速度变慢,影响制动能量回收效率的问题,提出一种基于比例继动阀的解耦式制动能量回收系统(uncoupled braking energy recovery system,URBS)方案。首先,基于比例继动阀的迟滞特性,采用前馈-单神经元PID控制方法,实现制动气压的准确输出;其次,以电池SOC、车速等为约束条件,根据气源压力信号确定供压模式,并制定解耦式制动能量回收控制策略;最后,基于AMESim,MATLAB/Simulink及TruckSim搭建联合仿真平台,选取单次制动工况与循环工况验证了制动力耦合效果及系统的制动能量回收效果。结果表明,基于比例继动阀的URBS可实现耦合制动力的快速响应,达到稳态压力值75%的时间小于0.1 s,且在中国重型商用车行驶工况和中国重型商用车瞬态工况下有效制动能量回收率分别为10.13%,17.17%。所提URBS方案能有效提高驱动轴耦合制动力的响应速度及耦合精度,可为纯电动商用车气压式URBS方案设计提供参考。

基于扩张状态观测器的无人机云台系统控制算法

针对无人机(UAV)三轴云台增稳控制中变量耦合的问题,提出一种基于扩张状态观测器(ESO)的无人机云台系统控制算法。首先,建立了无人机机载云台期望角的姿态解算算法模型;其次,构建了无人机机载云台位置环和速度环的串级比例-积分-微分(PID)控制回路;最后,引入ESO对机载云台角速度项在线实时估计,解决角速度项由于高耦合、多外扰导致的难以直接测量的问题,并对各通道的控制输入进行补偿。实验结果表明,所提算法在无指令、有指令和综合任务场景下的角度均方根误差分别为0.2357°、0.6317°和0.9463°,与传统PID算法相比,所提算法的角度误差分别降低了69.43%、53.29%和50.43%。可见,所提算法对外界扰动的抗干扰能力更强,控制精度更高。

基于4阶Bézier曲线的路径平滑方法研究

路径平滑技术旨在采用以曲代直的方法解决路径规划中存在的尖角问题,实现路径的平滑化,以满足外形设计和运动规划等工程应用需求。文中在深入探讨了Bézier曲线在路径平滑领域的应用优势及其在路径拟合中产生的较大偏差后,提出了一种基于内外比例因子的4阶Bézier曲线路径平滑新方法。通过严谨的理论分析,证明了该方法能够有效控制平滑误差,在不考虑路径节点坐标的情况下,误差上限为4.25,从而实现对原始路径的高精度平滑近似。在无人机路径平滑的仿真实验中,该方法耗时0.0061 s,证明了其在平滑处理速度方面的优越性。综合理论分析与实验结果,该方法不仅在平滑效果上表现出色,而且在处理速度上也具有明显优势。同时由于仅涉及内外比例因子两个自由参数,因此,操作简单,易于实现,具有较强的适用性和灵活性。

四轮独立驱动电动汽车整车控制策略仿真研究

基于控制器局域网总线(CAN)对四轮独立驱动电动汽车整车控制策略进行优化。控制策略采用了将比例积分微分(PID)与模糊算法融合的模糊比例积分微分控制算法,使用CAN总线进行整车控制,经模糊PID控制算法可获得车轮滑转率最优比及电机转动转矩,可有效实现驱动的防滑操作。并基于Matlab软件建立的整车动力学模型进行政策控制策略的仿真,模糊PID控制算法控制仿真结果表明,调节电机信号输出后,及时进行信号反馈,可形成特定闭环控制系统,实现实际滑转率稳定在最优滑转率附近,并且稳定性高,控制较精准。在模糊PID控制算法控制下,当转向角较小时,4个轮胎纵向力输出基本相等。在转向工况下,两转向前轮,尤其是外侧转向轮,则会输出较大侧向力,在不转向工况下,两后轮输出具有较小的侧向力。在转向工况下,仿真结果在可接受范围内,结果验证了控制策略的合理性。

冷链运输车空调冷风机运行自适应PID控制方法研究

冷链运输车空调冷风机运行环境复杂,导致传统的比例积分微分(PID)控制过程难以准确设定控制参数。为解决这一问题,设计冷链运输车空调冷风机运行自适应PID控制方法。首先,通过分析冷链运输车空调冷风机工作过程,选取多个控制参数,以降低复杂度。然后,设计基于自适应PID控制器的控制模型,以送风温度和送风压力作为控制量,将冷、热水流量及风机转速作为被控制量,求解控制量和被控制量的传递函数。最后,根据传递函数与期望值间的耦合关系,对控制分量的增减进行调整,以实现冷链运输车空调冷风机运行的自适应PID控制。试验结果表明,该方法能够使冷链运输车内温度保持稳定。该方法控制精准度高、鲁棒性强、实用价值高,可以确保货物在整个冷链运输过程中的质量和安全。

基于模糊神经网络PID的无人艇航向控制器研究

针对常规比例、积分和微分(proportional integral derivative,PID)控制器在无人艇航向控制系统中表现出的稳定性差、控制精度低等问题,文章提出一种将模糊控制与反向传播(back propagation,BP)神经网络相结合的控制算法;在MATLAB中对比常规PID控制器、模糊PID控制器与模糊神经网络PID控制器在给定期望航向角下的航向控制性能,仿真结果表明模糊神经网络PID控制器对无人艇的航向控制性能最佳;在搭建的实验平台上对不同航向控制器下无人艇的航行轨迹和航向角进行比较,实验结果进一步验证了模糊神经网络PID航向控制算法的优越性。

两相位信号交叉口直左机动车冲突特性研究

为更好研究交叉口冲突特性,以两相位信号控制交叉口发生冲突频率较高的直左冲突为研究对象,对长春市典型的两相位交叉口进行数据的采集和定量分析,以冲突率和冲突数为指标表征冲突特性,建立直左冲突中左转车占比与冲突率模型和左转车辆数、对向直行车辆数与冲突数模型。结论表明,左转车和对向直行车对冲突数有明显影响,左转车辆数越多,产生冲突的数量越多。研究结果可为两相位交叉口的渠化与信号配时优化提供参考。

基于HCOPSO算法的USV舵向PID控制参数整定方法

高速无人艇(USV)舵向控制要求同时满足调节时间短、超调量小,针对USV舵向比例积分微分(PID)控制的参数整定需求,将混合均值中心反向学习粒子群优化(HCOPSO)算法与PID控制结合,提出一种基于HCOPSO算法的USV舵向PID控制器参数整定方法。利用HCOPSO对PID控制器参数进行寻优,有效解决寻优过程的局部最优解问题。对比研究了粒子群(PSO)算法、线性惯性权重递减粒子群(LDIWPSO)算法、HCOPSO算法的PID控制器参数整定效果,结果表明, HCOPSO算法参数整定的USV舵向PID控制器具有更好的控制效果,相比于PSO、LDIWPSO,调节时间分别缩短22%、15%,超调量分别降低89%、74%,迭代次数分别减少40%、30%。基于研制的“久航750”USV开展了海洋环境测试,测试结果表明了文中设计方法应用于小型高速USV舵向控制的有效性。

高超声速滑翔飞行器预测校正闭环协同末制导方法

针对能量持续衰减的高超声速滑翔飞行器末制导段时间协同问题,提出一种预测飞行时间并校正飞行剖面的协同制导方法。设计了一种带有负比例导引系数的参数化飞行剖面,在辨识气动参数后快速预测剩余飞行时间;通过数值算法修正飞行剖面参数,并输出制导指令,满足单飞行器时间约束制导要求;设计闭环协同策略,在分析飞行器时间调整能力后,各飞行器协调期望飞行时间,再自主规划飞行剖面以同时攻击目标。仿真结果表明:预测校正闭环协同制导方法可以满足时间协同末制导任务需求,落点误差小于5 m,相对时间误差小于1 s。

小速度比视角下高超声速飞行器拦截条件研究

针对高超声速飞行器拦截问题,以吸气式高超声速飞行器为拦截对象,从拦截态势出发,利用交战几何概念,基于小速度比(拦截弹的速度小于高超声速飞行器的速度)视角,理论上给出了成功拦截高超声速飞行器的必要条件以及高超声速飞行器速度前置角的约束条件。然后,以真比例导引律为例,针对高超声速飞行器不同机动模式,给出了拦截弹拦截空间的数学表达式。最后,通过仿真实验,给出了不同速度比、高超声速飞行器不同机动模式下,拦截弹拦截空间的变化曲线,系统性地分析小速度比视角下拦截高超声速飞行器的拦截条件,为后续拦截高超声速飞行器中末制导交接班条件和末制导律设计提供基础理论依据。

基于势场化改进A*算法的履带式车辆路径规划算法

传统的路径规划算法为提高所得路径质量,往往采用曲线平滑化的方式,而忽略了履带式车辆跟踪连续曲线路径精度低的问题。针对这个问题,提出了基于势场化改进A*算法的履带式车辆路径规划算法。该算法将以人工势场指出局部环境下A*算法的子目标,再通过删除冗余节点策略,提高路径直线占比,引入了Reeds-Shepp曲线,约束路径的曲率使之适用于履带车辆的行驶。最后通过MATLAB软件进行仿真,并提出转角次数、直线路径占比两项评估路径质量的评价指标。仿真结果表明,该算法所得路径短,转弯次数显著下降,直线路径占比大,平均直线路径长,复杂环境下效果依然良好。

补贴机制退出对中国新能源汽车出口的影响研究

研究补贴退坡对新能源汽车出口的影响对促进中国新能源汽车产业高质量发展以及“双碳”目标的实现有着重要的意义。本文主要通过断点回归的实证分析方法,利用2017年1月~2022年10月中国海关总署统计的新能源汽车出口数据以及月度时间变量研究新能源汽车补贴退坡政策对新能源汽车出口的影响。结果表明,补贴退坡政策对新能源汽车出口的影响显著为正。补贴退坡政策可以通过提高新能源汽车企业的出口比重、推动新能源汽车企业的技术创新来促进新能源汽车出口,其影响程度受到出口目标国家的经济规模以及出口的新能源汽车种类的影响。本文为补贴退坡政策是否促进、如何促进新能源汽车出口提供了理论依据,也为政府推动新能源汽车出口、发展新能源汽车产业提供了决策依据。