基于1/2车体四自由度的汽车悬架系统性能研究

采用Matlab/simulink软件,建立了二分之一车体四自由度主动悬架系统的动力学模型。结合模糊控制理论,应用FIS Editor工具箱,建立Mamdani型模糊推理系统。在此基础上,本文进行了主动悬架系统特性的仿真分析,并与传统的被动悬架的性能指标比较。研究结果表明,车身垂直加速度峰值下降了43.3%,车身俯仰角加速度峰值下降了31.1%,前悬架动行程下降了35.5%,前轮与路面的动载荷的峰值下降了26.3%,有效地改善了汽车性能指标,能够满足汽车稳定性和舒适性的要求。     

基于ADAMS的汽车驱动桥壳动力学仿真分析

利用机械系统动力学仿真软件ADAMS,建立了矿用汽车驱动桥非线性振动系统的虚拟样机模型,采用动力学仿真的方法,计算桥壳在不平路面激励下所受到的动载荷,仿真结果可为桥壳的有限元动态分析与设计提供载荷方面的准备。     

轮毂电机驱动系统对整车行驶平顺性影响的研究

本文以轮毂电动汽车为依托,建立了1/4车辆双质量振动系统模型,根据系统振动方程,建立MATLAB/Simulink仿真模型,并以此分别分析在路面脉冲激励和路面随机激励下,以不同车速行驶时非簧载质量的增加对车身部分加速度的影响。通过建立传递函数分析不同非簧载质量情况下,车身加速度、相对动载荷和悬架动挠度对路面速度激励的响应情况。最后对目前针对非簧载质量增加对于整车平顺性不利影响的解决方案进行了对比分析。     

汽车电子控制悬架系统

介绍了汽车的电子控制半主动悬架系统和电子控制主动悬架系统的工作原理。     

主动悬架系统模式切换控制策略研究

针对在不同工况下车辆行驶时对于主动悬架系统的性能需求,本文设计出一种可切换悬架工作模式的悬架控制策略,可以提高车辆在不同工况下行驶时的动力学性能。通过对控制策略进行建模仿真,结果得出相较于未进行模式切换的悬架,所设计的模式切换控制策略可以有效改善悬架工作时的性能,为后续控制参数的优化提供了研究基础。     

基于有限元分析的新能源汽车侧面柱碰结构优化研究

文章针对侧面柱碰工况特点对汽车车身结构的传力路径进行了分析,并以某款新能源汽车为分析对象,采用HyperWorks软件搭建有限元仿真计算模型,对侧面柱碰工况车身的主要传力路径上的座椅横梁和中通道进行结构优化,使其车身侵入量和电池包的安全性能均得到明显改善.     

汽车点火系统仿真分析

通过对汽车点火系统工作机理的分析,将点火系统电路进行了合理的简化。利用Matlab软件的可视化仿真环境Simulink建立了汽车点火系统的仿真模型,对电路进行了仿真和分析。     

汽车空气悬架的发展及我国研发对策思考

空气悬架诞生于十九世纪中期,早期用于机械设备隔振.1947年,美国首先在普耳曼汽车上使用空气悬架,欧洲及日本等国家和地区相继对汽车空气悬架作了应用研究.目前,国外这些地方无论是客车还是载重车都已经比较普遍采用空气悬架系统,而国内却处于刚刚起步阶段,只应用在一些豪华客车和少部分重型载货车上.     

某6101型客车车身骨架结构动态扭转响应分析

以某6101型客车车身骨架为研究对象,应用ANSYS软件,建立了其车身骨架结构有限元模型。采用客车驶过正弦波形路面的方式模拟右前轮越障的危险工况,分析了客车动态扭转过程中瞬态响应,得到了车身危险点的位移和应力的时间历程响应。结果表明:在动态扭转工况下,某6101型客车在0.045秒时最大应力达到130MPa,为改进车身结构提供了理论依据。     

基于PID控制的汽车制动系统仿真分析

文章通过汽车理论和制动性性能的分析,建立包含汽车运动、车轮运动和车轮纵向摩擦力的汽车动力学模型。利用Matlab/Simulink仿真软件,建立汽车模型、制动器模型、轮胎模型和PID控制系统仿真分析模型,进行控制系统的仿真分析。并利用PID控制器以滑移率为控制目标,制动距离和制动时间为主要输出量,仿真研究汽车在不同的路面条件下的控制效果。仿真结果表明PID控制,在不同的路面条件下均可实现对车辆性能的有效控制。研究结果为提高汽车的制动安全性,提供了有益的参考。     

Hardware-in-the-loop testbed for evaluating connected vehicle applications

Connected vehicle environment provides the groundwork of future road transportation. Researches in this area are gaining a lot of attention to improve not only traffic mobility and safety, but also vehicles’ fuel consumption and emissions. Energy optimization methods that combine traffic information are proposed, but actual testing in the field proves to be rather challenging largely due to safety and technical issues. In light of this, a Hardware-in-the-Loop-System (HiLS) testbed to evaluate the performance of connected vehicle applications is proposed. A laboratory powertrain research platform, which consists of a real engine, an engine-loading device (hydrostatic dynamometer) and a virtual powertrain model to represent a vehicle, is connected remotely to a microscopic traffic simulator (VISSIM). Vehicle dynamics and road conditions of a target vehicle in the VISSIM simulation are transmitted to the powertrain research platform through the internet, where the power demand can then be calculated. The engine then operates through an engine optimization procedure to minimize fuel consumption, while the dynamometer tracks the desired engine load based on the target vehicle information. Test results show fast data transfer at every 200 ms and good tracking of the optimized engine operating points and the desired vehicle speed. Actual fuel and emissions measurements, which otherwise could not be calculated precisely by fuel and emission maps in simulations, are achieved by the testbed. In addition, VISSIM simulation can be implemented remotely while connected to the powertrain research platform through the internet, allowing easy access to the laboratory setup.     

直线电机式悬架电流滞环控制策略研究

本文设计出一种电流滞环控制策略,通过跟踪直线电机式悬架控制系统输出的最优阻尼力转变,得到参考电流,经过空间矢量调制后输出PWM波,输送到电流逆变器中转换为三相电流,进而控制直线电机的作用。经过仿真可以得出电流滞环控制策略控制效果良好,可以输出理想的阻尼力,为电动汽车主动悬架的研究提供基础。     

A simulation model for evaluating advanced dial-a-ride paratransit systems

This paper presents a simulation system that has been developed to model a variety of technology-oriented dial-a-ride paratransit systems operated in an urban environment. The latest advances in information technologies such as automatic vehicle location (AVL), digital telecommunication and computers have afforded a unique opportunity for public transit agencies to integrate these technologies in their paratransit systems for improved productivity and reliability. This opportunity has also prompted wide spread interest in quantifying the actual benefits that can be attained from such technological enhancement. The primary objective of the simulation model described in this paper was to facilitate the evaluation of the potential effects that these technologies may bring on a paratransit system. The paper discusses the general concepts, models and computational techniques applied in the simulation system, focusing on how various components are modeled and how they interact with each other in the overall simulation framework. The simulation system is applied to evaluate the potential operational improvement that may be attained from the application of automatic vehicle location technology.     

多技术融合的车用传感器与执行器实训系统研制

文章介绍了无线传输技术、机器人技术、虚拟器技术、信号调理技术等多种先进技术在“车用传感器与执行器实训系统”中的应用，并通过试验分析，验证了该系统稳定可靠，能满足行动导向教学、理实一体化教学以及项目教学的需求。     

Green vehicle technology to enhance the performance of a European port: A simulation model with a cost-benefit approach

In this paper, we study the impact of using a new intelligent vehicle technology on the performance and total cost of a European port, in comparison with existing vehicle systems like trucks. Intelligent autonomous vehicles (IAVs) are a new type of automated guided vehicles (AGVs) with better maneuverability and a special ability to pick up/drop off containers by themselves. To identify the most economical fleet size for each type of vehicle to satisfy the port’s performance target, and also to compare their impact on the performance/cost of container terminals, we developed a discrete-event simulation model to simulate all port activities in micro-level (low-level) details. We also developed a cost model to investigate the present values of using two types of vehicle, given the identified fleet size. Results of using the different types of vehicles are then compared based on the given performance measures such as the quay crane net moves per hour and average total discharging/loading time at berth. Besides successfully identifying the optimal fleet size for each type of vehicle, simulation results reveal two findings: first, even when not utilising their ability to pick up/drop off containers, the IAVs still have similar efficacy to regular trucks thanks to their better maneuverability. Second, enabling IAVs’ ability to pick up/drop off containers significantly improves the port performance. Given the best configuration and fleet size as identified by the simulation, we use the developed cost model to estimate the total cost needed for each type of vehicle to meet the performance target. Finally, we study the performance of the case study port with advanced real-time vehicle dispatching/scheduling and container placement strategies. This study reveals that the case study port can greatly benefit from upgrading its current vehicle dispatching/scheduling strategy to a more advanced one.     

Modeling the effect of electric vehicle adoption on pedestrian traffic safety: An agent-based approach

When operated at low speeds, electric and hybrid vehicles have created pedestrian safety concerns in congested areas of various city centers, because these vehicles have relatively silent engines compared to those of internal combustion engine vehicles, resulting in safety issues for pedestrians and cyclists due to the lack of engine noise to warn them of an oncoming electric or hybrid vehicle. However, the driver behavior characteristics have also been considered in many studies, and the high end-prices of electric vehicles indicate that electric vehicle drivers tend to have a higher prosperity index and are more likely to receive a better education, making them more alert while driving and more likely to obey traffic rules. In this paper, the positive and negative factors associated with electric vehicle adoption and the subsequent effects on pedestrian traffic safety are investigated using an agent-based modeling approach, in which a traffic micro-simulation of a real intersection is simulated in 3D using AnyLogic software. First, the interacting agents and dynamic parameters are defined in the agent-based model. Next, a 3D intersection environment is created to integrate the agent-based model into a visual simulation, where the simulation records the number of near-crashes occurring in certain pedestrian crossings throughout the virtual time duration of a year. A sensitivity analysis is also carried out with 9000 subsequent simulations performed in a supercomputer to account for the variation in dynamic parameters (ambient sound level, vehicle sound level, and ambient illumination). According to the analysis, electric vehicles have a 30% higher pedestrian traffic safety risk than internal combustion engine vehicles under high ambient sound levels. At low ambient sound levels, however, electric vehicles have only a 10% higher safety risk for pedestrians. Low levels of ambient illumination also increase the number of pedestrians involved in near-crashes for both electric vehicles and combustion engine vehicles.     

Simulation model performance analysis of a multiple station shared vehicle system

As an alternative transportation paradigm, shared vehicle systems have become increasingly popular in recent years. Shared vehicle systems typically consist of a fleet of vehicles that are used several times each day by different users. One of the main advantages of shared vehicle systems is that they reduce the number of vehicles required to meet total travel demand. An added energy/emissions benefit comes when low-polluting (e.g., electric) vehicles are used in the system. In order to evaluate operational issues such as vehicle availability, vehicle distribution, and energy management, a unique shared vehicle system computer simulation model has been developed. As an initial case study, the model was applied to a resort community in Southern California. The simulation model has a number of input parameters that allow for the evaluation of numerous scenarios. Several measures of effectiveness have been determined and are calculated to characterize the overall system performance. For the case study, it was found that the most effective number of vehicles (in terms of satisfying customer wait time) is in the range of 3–6 vehicles per 100 trips in a 24 h day. On the other hand, if the number of relocations also is to be minimized, there should be approximately 18–24 vehicles per 100 trips. Various inputs to the model were varied to see the overall system response. The model shows that the shared vehicle system is most sensitive to the vehicle-to-trip ratio, the relocation algorithm used, and the charging scheme employed when electric vehicles are used. A preliminary cost analysis was also performed, showing that such a system can be very competitive with present transportation systems (e.g., rental cars, taxies, etc.).     

Transit-oriented autonomous vehicle operation with integrated demand-supply interaction

Autonomous vehicles (AVs) represent potentially disruptive and innovative changes to public transportation (PT) systems. However, the exact interplay between AV and PT is understudied in existing research. This paper proposes a systematic approach to the design, simulation, and evaluation of integrated autonomous vehicle and public transportation (AV + PT) systems. Two features distinguish this research from the state of the art in the literature: the first is the transit-oriented AV operation with the purpose of supporting existing PT modes; the second is the explicit modeling of the interaction between demand and supply.We highlight the transit-orientation by identifying the synergistic opportunities between AV and PT, which makes AVs more acceptable to all the stakeholders and respects the social-purpose considerations such as maintaining service availability and ensuring equity. Specifically, AV is designed to serve first-mile connections to rail stations and provide efficient shared mobility in low-density suburban areas. The interaction between demand and supply is modeled using a set of system dynamics equations and solved as a fixed-point problem through an iterative simulation procedure. We develop an agent-based simulation platform of service and a discrete choice model of demand as two subproblems. Using a feedback loop between supply and demand, we capture the interaction between the decisions of the service operator and those of the travelers and model the choices of both parties. Considering uncertainties in demand prediction and stochasticity in simulation, we also evaluate the robustness of our fixed-point solution and demonstrate the convergence of the proposed method empirically.We test our approach in a major European city, simulating scenarios with various fleet sizes, vehicle capacities, fare schemes, and hailing strategies such as in-advance requests. Scenarios are evaluated from the perspectives of passengers, AV operators, PT operators, and urban mobility system. Results show the trade off between the level of service and the operational cost, providing insight for fleet sizing to reach the optimal balance. Our simulated experiments show that encouraging ride-sharing, allowing in-advance requests, and combining fare with transit help enable service integration and encourage sustainable travel. Both the transit-oriented AV operation and the demand-supply interaction are essential components for defining and assessing the roles of the AV technology in our future transportation systems, especially those with ample and robust transit networks.     

A virtual vehicle probe model for time-dependent travel time estimation on signalized arterials

Estimation of time-dependent arterial travel time is a challenging task because of the interrupted nature of urban traffic flows. Many research efforts have been devoted to this topic, but their successes are limited and most of them can only be used for offline purposes due to the limited availability of traffic data from signalized intersections. In this paper, we describe a real-time arterial data collection and archival system developed at the University of Minnesota, followed by an innovative algorithm for time-dependent arterial travel time estimation using the archived traffic data. The data collection system simultaneously collects high-resolution “event-based” traffic data including every vehicle actuations over loop detector and every signal phase changes from multiple intersections. Using the “event-based” data, we estimate time-dependent travel time along an arterial by tracing a virtual probe vehicle. At each time step, the virtual probe has three possible maneuvers: acceleration, deceleration and no-speed-change. The maneuver decision is determined by its own status and surrounding traffic conditions, which can be estimated based on the availability of traffic data at intersections. An interesting property of the proposed model is that travel time estimation errors can be self-corrected, because the trajectory differences between a virtual probe vehicle and a real one can be reduced when both vehicles meet a red signal phase and/or a vehicle queue. Field studies at a 11-intersection arterial corridor along France Avenue in Minneapolis, MN, demonstrate that the proposed model can generate accurate time-dependent travel times under various traffic conditions.