基于UG的客车主减速器锥齿轮设计平台的开发

利用UG软件二次开发了客车主减速器锥齿轮专用设计平台,论述了平台的结构设计与功能模块设计,最后给出了设计实例。     

State estimation in roll dynamics for commercial vehicles

Accurate lateral load transfer estimation plays an important role in improving the performance of the active rollover prevention system equipped in commercial vehicles. This estimation depends on the accurate prediction of roll angles for both the sprung and the unsprung subsystems. This paper proposes a novel computational method for roll-angle estimation in commercial vehicles employing sensors which are already used in a vehicle dynamic control system without additional expensive measurement units. The estimation strategy integrates two blocks. The first block contains a sliding-mode observer which is responsible for calculating the lateral tyre forces, while in the second block, the Kalman filter estimates the roll angles of the sprung mass and those of axles in the truck. The validation is conducted through MATLAB/TruckSim co-simulation. Based on the comparison between the estimated results and the simulation results from TruckSim, it can be concluded that the proposed estimation method has a promising tracking performance with low computational cost and high convergence speed. This approach enables a low-cost solution for the rollover prevention in commercial vehicles.     

Travel time estimation oriented freeway sensor placement problem considering sensor failure

Optimal sensor placement on freeway corridor is of great interest to transportation authorities. However, current traffic sensors are easily subject to various failures. Therefore, it is necessary to incorporate sensor failure into the optimal sensor placement model. In this article, a two-stage stochastic model is proposed for the purpose of travel time estimation on freeway corridor. To balance the effectiveness and reliability, a stochastic conditional value at risk (CVaR) model is also proposed. Since both models are too complicated, a customized genetic algorithm is developed. Numerical experiments show that considering sensor failure makes a significant performance improvement in the sensor placement pattern. Sensitivity analysis is also applied to investigate the impact of a number of allowable sensors and different traffic sensor failure probability.     

基于Isight和AMESim的液压减振器关键参数集成优化

在AMESim中搭建了某乘用车前悬架双筒充气式液压减振器的仿真模型。以 Isight 为平台集成AMESim,对减振器模型参数进行DOE分析,提取对减振器性能影响较大的参数,作为优化的设计变量。利用Isight中的Pointer智能求解器进行优化。结果表明,经过集成优化后的减振器阻尼力曲线与目标曲线吻合较好,符合工程实际的需要。与传统方法相比,该方法缩短了时间,提高了设计效率,可用于指导减振器阀系参数的设计与性能预测。     

基于GT-Suite的重型载货车冷却系统仿真及匹配设计

基于GT-Suite软件建立了某重型载货车发动机冷却系统的一维-准三维混合仿真模型,通过对发动机极限工况下出水温度、出水流量等计算结果与试验值对比分析,验证了仿真模型的准确性。最后在此模型基础上对发动机冷却系统进行风扇选型匹配,实现了满足整车冷却性能要求的前提下,减小了其消耗功率,从而提高了整车经济性。     

防抱死制动系统对SUV车辆操控稳定性仿真分析

针对SUV车辆在制动情况下出现的操纵性和稳定性变差现象,在CarSim软件中建立了SUV车辆动力学模型,在对开的路面对行驶的紧急制动工况进行了仿真,初步发现防抱死系统对该工况下车辆操纵稳定性的影响最大,为进一步验证,与Simulink结合建立了整车联合仿真模型,将Carsim中SUV制动过程中的制动压力导出至Simulink模型作制动仿真测试,进一步描绘出车轮侧偏角、横移角速度和偏移位移等影响操纵稳定性的参数数值变化曲线,通过分析对比,确定了紧急制动条件下为SUV车辆加装防抱死系统能达到提高操纵稳定性的目标,最终达到安全驾驶的目的。     

燃料电池电动车车载甲醇重整器

对目前世界几大汽车公司研制开发的燃料电池电动汽车车载甲醇重整器加以介绍，着重讨论了重整器的设计与重整催化剂的布置。指出，甲醇重整器的效果良好，但重整器出口富氢重整气中CO的含量仍然很高，而较高浓度的CO会使燃料电池电极中毒。因此，从重整器中产生出来的重整气在进入燃料电池以前要进行净化。     

车辆排放污染的综合控制

随着我国汽车保有量急剧的增加,车辆排放污染已成为亟待解决的重要课题,控制排放污染是一个大型系统工程,文中从车辆、道路交通环境、交通管理3个方面论述了对排放污染的综合控制。     

关于哈尔滨市城市防洪工程的建设情况

简要介绍哈尔滨市城市防洪工程建设情况。     

Driver behavior formulation in intersection dilemma zones with phone use distraction via a logit-Bayesian network hybrid approach

Use of cellular phone while driving is one of the top contributing factors that induce traffic crashes, resulting in significant loss of life and property. A dilemma zone is a circumstance near signalized intersections where drivers hesitate when making decisions related to their driving behaviors. Therefore, the dilemma zone has been identified as an area with high crash potential. This article utilizes a logit-based Bayesian network (BN) hybrid approach to investigate drivers' decision patterns in a dilemma zone with phone use, based on experimental data from driving simulations from the National Advanced Driving Simulator (NADS). Using a logit regression model, five variables were found to be significant in predicting drivers' decisions in a dilemma zone with distractive phone tasks: older drivers (50–60 years old), yellow signal length, time to stop line, handheld phone tasks, and driver gender. The identified significant variables were then used to train a BN model to predict drivers' decisions at a dilemma zone and examine probabilistic impacts of these variables on drivers' decisions. The analysis results indicate that the trained BN model was effective in driver decision prediction and variable influence extraction. It was found that older drivers, a short yellow signal, a short time to stop line, nonhandheld phone tasks, and female drivers are factors that tend to result in drivers proceeding through intersections in a dilemma zone with phone use distraction. These research findings provide insight in understanding driver behavior patterns in a dilemma zone with distractive phone tasks.