Vehicle Energy Dissipation Due to Road Roughness

Road roughness and surface texture are known to affect tire rolling resistance; however, little emphasis has been placed on the consequent changes in total vehicle energy dissipation due to road roughness. Thus, tire rolling resistance, in isolation from vehicle contributed losses such as dissipation in the suspension, appears to be a weakness in present evaluation procedures as they relate to fuel economy and pollution level testing: Recent work by Funfsinn and Korst has shown that substantial and measurable increases in energy losses occur for vehicles traveling on rough roads. The present investigation uses vehicle axle accelerations as a means of examining various road surfaces. Correlation with computer simulations has allowed the development of a deterministic road roughness model which permits the prediction of energy dissipation in both the tire and suspension as functions of road roughness, tire pressure, and vehicle speed. Comparison to the experiments of Korst and Funfsinn results in good agreement and shows that total rolling loss increases of up to 20 percent compared to ideal smooth roads are possible. The aerodynamic drag coefficient is also found to increase while driving on rough roads.     

Off-set crack propagation analysis under mixed mode loadings

An assessment was carried out herein to study the eccentricity of cracks subjected to mixed-mode loadings. Several loading locations relative to a central line were selected to induce mixed-mode loadings, which were computed using a finite element method. An adaptive meshing technique was adopted during the simulation of crack propagation to ensure the singularity of stress at the tip of the crack. The stress intensity failure criterion was used and programmed, and the node splitting technique was used when the stress intensity factor reached the fracture toughness of the material to simulate crack propagations. It was found that large variations in the stress intensity factor were observed when off-set cracks were used, and that K _II decreased when loading distance increased, but increased when the off-set crack distance was increased. Both crack eccentricity and loading distance played important roles in producing mixed-mode loading, compared to the influence of central cracks. Correction factors were introduced to modify the calculation of stress intensity factors under mixed-mode loadings. Simulations of crack propagation were also conducted to study the effects of crack eccentricities and loading distances. It was found that the crack length, the loading distance relative to the central crack and the crack eccentricity dominated calculations of the integrity of cracked structures.     

Methodology for bus structure torsion stiffness and natural vibration frequency prediction based on a dimensional analysis approach

Engineering bus design requires testing of bus structures prototypes in order to guarantee a certain level of strength and an appropriate static and dynamic behavior of the bus superstructure when exposed to road loads. However, experimental testing of real bus structures is very expensive as it requires expensive resources and space. If testing is done on a scale bus model the previous required expenses are considerably reduced. Therefore, a novel methodology based on dimensional analysis applied to bus structure prediction to evaluate the bus structure static and dynamic performance is proposed. The static performance is evaluated attending to torsion stiffness and the dynamic in terms of the natural vibration frequencies and rollover threshold. A scale bus has been manufactured and dimensionless parameters have been defined in order to project the results obtained in the scale bus model to a larger model. Validation of the proposed methodology has been carried out under experimental and finite element analysis.     

Vehicle sensor data-based analysis on the driving style differences between operating indoor simulator and on-road instrumented vehicle

Abstract

Indoor simulator and on-road instrumented vehicle are the most popular ways to analyze driving behaviors by using collected Vehicle Sensor Data (VSD). However, for a same driver, the driving performance could be different in the real world and in the simulated world. Even though many studies have been conducted to discover the differences of driving behaviors in these two circumstances, little research has focused on analyzing the differences in driving style, which can provide more integrated knowledge of a driver from the natural structure, stimulus–response mechanism, of driving behaviors. Therefore, in this paper, the driving styles in both the real world and the simulated world are extracted by implementing the nonnegative matrix factorization method on the collected VSD data. Through this analysis, the driving style differences can be quantitatively described and discussed in detail. It is found that the drivers tend to be more unstable and sometimes aggressive when driving the simulator and the deviation in the perception of temporal gap in two circumstances is also discovered. The research findings are particularly valuable to calibrate the driving simulator and construct more reliable driving behavior models.     

不同加载幅值下考虑层间界面条件和侧向剪力作用的柔性铺面响应

该文进行了一个三维有限元参数量化的粘弹性路面响应研究,由于不同的轮胎配置:双轮和宽基轮胎在3种温度(5、25和40℃)和两种速度(8、72 km/h);还有影响路面响应的3种因素:移动车轮荷载幅值(连续,梯形),层间界面条件(简单的摩擦和粘弹性模型)和横向力共同对路面响应的影响进行了研究.研究发现连续加载幅值,不但可以模拟路面对运动轮荷载的响应,并且是一种比目前使用的梯形荷载幅值更准确的研究模型.粘弹性模型极大地提高了双轮胎对预测路面的响应,而简单的摩擦模型更接近宽基轮胎的实地测量.侧向剪力是积极改善预测轮底的表面磨损和底部热拌沥青(沥青)基层的较小程度上的应变.研究表明:使用连续加载幅值和非均匀压力分布模拟移动轮,侧向剪切力和适当的界面摩擦可显著改善有限元模型对车辆加载路面响应的预测能力.     

船用柴油机组调速系统仿真研究

模拟电力系统的模拟研究中,柴油机及其调速系统直接影响系统机电暂态过程的准确性,对于判别系统受到大扰动后的暂态稳定和受到小扰动后的静态稳定性具有重要意义。从电站柴油发电机组的运动方程出发,在柴油机及其调速器数学模型的基础上,利用数字仿真计算机实时计算模拟转矩指令,用以控制一套高性能交流调速系统,从而实现电站柴油发电机组中柴油机及其调速器与系统转动惯量的数模混合模拟。实验表明,该模拟系统通用性强,响应速度快,准确性较高。     

A multiobjective chance constrained programming model for supplier selection under uncertainty

Risk management is an inherent part of supplier selection. While companies are enjoying the benefits of outsourcing, risks brought by this practice should be taken into account in the process of decision making. This paper presents a multiobjective stochastic sequential supplier allocation model to help in supplier selection under uncertainty. Demand for products, capacities at suppliers as well as transportation and other variable costs are the main sources of uncertainty and are modeled using probability distributions. Disruptions are exogenous events and the model provides proactive mitigation strategies against disruptions by assigning backup suppliers who can be used in case of a default at a primary supplier. When there is no disruption, the model’s solution is an optimal supplier order assignment, considering operational risks.