Magneto-rheological suspensions for improving ground vehicle’s ride comfort,stability, and handling

ABSTRACT

A state-of-the-art discussion on the applications of magneto-rheological (MR) suspensions for improving ride comfort, handling, and stability in ground vehicles is discussed for both road and rail applications. A historical perspective on the discovery and engineering development of MR fluids is presented, followed by some of the common methods for modelling their non-Newtonian behaviour. The common modes of the MR fluids are discussed, along with the application of the fluid in valve mode for ground vehicles’ dampers (or shock absorbers). The applications span across nearly all road vehicles, including automobiles, trains, semi-trucks, motorcycles, and even bicycles. For each type of vehicle, the results of some of the past studies is presented briefly, with reference to the originating study. It is discussed that Past experimental and modelling studies have indicated that MR suspensions provide clear advantages for ground vehicles that far surpasses the performance of passive suspension. For rail vehicles, the primary advantage is in terms of increasing the speed at which the onset of hunting occurs, whereas for road vehicles – mainly automobiles – the performance improvements are in terms of a better balance between vehicle ride, handling, and stability. To further elaborate on this point, a single-suspension model is used to develop an index-based approach for studying the compromise that is offered by vehicle suspensions, using the H₂ optimisation approach. Evaluating three indices based on the sprung-mass acceleration, suspension rattlespace, and tyre deflection, it is clearly demonstrated that MR suspensions significantly improve road vehicle’s ride comfort, stability, and handling in comparison with passive suspensions. For rail vehicles, the simulation results indicate that using MR suspensions with an on-off switching control can increase the speed at which the on-set of hunting occurs by as much as 50% to more than 300%.     

基于两阶段K-means聚类的道路运行状况评价方法

为有效评价道路运行状况,通过分析车辆在行驶过程中运行状态的变化,研究了一种基于两阶段K-means聚类(TSKC)的道路运行状况评价方法.针对K-means聚类数选取的任意性和聚类中心选取的随机性问题,提出基于遍历的K-means聚类方法,采用类吸引度确定聚类数和初始中心,并以此为初始条件进行第二阶段K-means聚类,得到交通模式.提出模式吸引度、路段评价指数、分布均衡度,并用这些指标来评价路段交通运行状况.以北京市朝阳区北辰东路为例进行验证,结果表明,该方法比传统道路评价方法更细致、全面、直观地描绘了车辆状态的演变过程和交通模式的分布情况,具有良好的实用性.     

基于FCM的内河一类船长实操考试效能评估

为解决内河一类船长实操考试效能评估问题,提出了一种基于模糊认知图的评价模型(FCMES).在建立影响因素层的不同评价等级基础上,通过问卷调查辨识出了25个影响因素;据专家意见将收集到的定性数据转化为三角模糊数,得到不同的模糊矩阵;利用模糊推理规则的方法聚合各模糊矩阵,再解模糊化,获取邻接矩阵.采取输入端数、输出端数及中心度3个指数的方法,分析FCMES中各因素的重要程度,选出核心变量.利用Matlab实现对FCMES认知图的推理仿真,检验核心变量的准确性.结果表明,绩效评估、评估员素质、模拟器效能、考试流程设计合理性,这4个影响因素对内河一类船长实操考试的效能有重要影响.     

基于Breakdown概率模型的快速路匝道与公交专用道协调控制研究

延误是评价快速路协调控制方案的常用指标,然而由于交通流骤降(Breakdown)现象发生导致的车辆运行速度突变,使得基于延误指标的控制方案评价具有较大的不确定性.因此,引入Breakdown概率作为评价指标,并将其与延误指标进行结合形成综合性评价指标以解决该问题.本文以匝道控制和公交专用道设置作为协调手段设计4个协调控制方案,分别利用改进后的Breakdown概率模型及Integration仿真软件对4个方案进行基于Breakdown概率指标和延误指标的评价,进而结合2种指标形成综合指标对方案进行评价,并对以上3种指标的评价结果进行对比分析.分析结果表明,Breakdown概率指标与延误指标的评价结果具有不一致性,即该指标可对拥堵形成过程中的协调方案进行合理评价,而Breakdown概率指标与综合指标评价结果具有一致性.同时Breakdown概率指标可定量评价协调手段对Breakdown概率的影响,采取匝道控制会使得Breakdown发生概率下降约7%,而设置公交专用道则会使得Breakdown发生概率上升约12%.综合评价指标平衡了Breakdown概率指标与延误指标间的评价结果分歧,能够对控制方案进行综合性的评价.     

Assessing the performance of SpeedInfo radar traffic sensors

Traffic speed is a crucial input for real-time traffic management applications. Operating agencies typically deploy their own sensors to collect the measurements, e.g., loop detectors. Recently, SpeedInfo emerged with a different paradigm for traffic speed collection: instead of selling hardware to operating agencies, at each link the company deploys its own Doppler radar in a self-contained wireless unit to measure traffic speeds and then sells the speed data. This study uses well-tuned loop detector-based speed measurements to evaluate 15 of the Doppler radar sensors over several months while the two traffic data collection systems were operating concurrently. The extended study period includes potentially challenging and transient conditions for the radar sensors: both recurrent (rush hour congestion and late night low flow) and nonrecurrent (incidents and precipitation). The analysis took a broad overview, comparing speed measurements from the radar sensors against the concurrent loop detector data and then explicitly looked for any anomalous pattern in the radar data such as latency and system outages. The work found the radar measurements are generally good, but also identified several points that should be considered before deployment, including latency, different biases in free flow and congestion, vulnerability to precipitation, and sensitivity to mounting angle.     

锚固路堑高边坡稳定性非线性模糊评判

针对路堑高边坡锚固后的稳定性评价,基于模糊性与层次性构建锚固路堑高边坡稳定性2级模糊综合评判模型。根据不同类评价指标的取值方法及隶属度函数选取原则,建立统一的隶属度确定方法,采用三角模糊数互补判断矩阵排序方法确定权向量,以体现评价指标重要程度比较的不确定性。引入非线性模糊算子,以消除个别影响因素不利时对结果的突出影响,使评价结果能更真实地反映工程实际状况。以京新高速公路路堑高边坡稳定性评价为应用实例,验证该模型的可行性与合理性。     

岩溶隧道风险等级模糊综合评价

为了获得已探明有溶洞存在时的隧道发生涌水突泥的风险等级,针对叙大铁路有溶洞存在的中坝隧道,选取了针对性的指标体系:溶洞规模,建立了相应的模糊综合评价模型,并采用层次分析法计算各项风险指标的权重,从而得出在有溶洞存在时这一特定条件下,隧道发生涌水突泥风险级别。     

高速公路路面养护管理系统开发和研究

在考虑当前路况的基础上，又考虑路龄的使用性能预测模型，预测的结果更为快速准确。探讨高等级公路道路养护管理决策系统和经济分析方法，提出了改进优劣系数法，该方法充分利用了专家经验知识，减小了决策误差。开发了高速公路路面养护管理辅助决策系统，建立高速公路基本数据库，由系统自动进行路面使用性能评价分析，并利用专家知识系统得出推荐养护方案，系统投入运行后反响良好。该养护管理系统的建立和实施进一步提高和改善了江苏省高等级公路的使用管理和养护管理模式，为高等级公路早日实现网级化系统管理奠定基础。     

基于灰色评价理论的自适应最优路径选择

充分考虑了驾驶员在路径选择中的不同要求,依据层次分析法和灰色评价理论建立了一种根据驾驶员的偏好自适应选择最优路径的方法,并设计了相应的决策支持系统,为智能交通流诱导系统的进一步发展铺平了道路。     

沉管隧道基槽爆破开挖作用下邻近地铁隧道力学响应

为确保邻近地铁隧道在沉管隧道基槽爆破开挖过程的安全性,通过现场实测评价地铁隧道运营现状,借助数值分析法探索地铁隧道对沉管基槽爆破开挖的力学响应特征,并制定既有隧道结构的安全判据和沉管基槽爆破振动安全距离。研究表明： 既有地铁区间隧道现状累计最大沉降为1.89 mm,近半年最大沉降速率为0.01 mm/d,均小于规范规定的控制值,隧道结构现状处于稳定状态;沉管隧道基槽爆破振动引起的地铁隧道结构最大振速为0.359 cm/s,远小于振速安全阈值（2.0 cm/s）,说明地铁结构受爆破振动影响较小,且爆破振动的安全距离为25 m; 基槽开挖应力扰动后引起的地铁隧道累计最大沉降为3.16 mm,小于位移预警值,隧道结构处于稳定状态。