轻型商用车集成式电子液压制动系统助力策略设计

伴随轻型商用车电动化的发展,用于轻型商用车的线控制动技术得到发展,针对线控制动技术中的集成式电子液压制动系统,提出一种基于模糊PI控制反应盘主副面位移差的制动助力方法.通过实车验证表明:实际反应盘主副面位移差能够快速跟随目标曲线,制动过程平顺,具有实用性.     

城市新建道路工程既有地下管道保护方案研究

根据城市发展需要,城市道路建设与周边用地开发并非同步进行,工程中时常遇到建设用地下方存在既有管道的情况,一般根据管道埋深、管道规模并综合工程可行性及经济性,选取保护或迁移的设计方案。对于大型管道的保护通常采用护管桥涵或者轻质材料换填的方式,两种技术方法各有其优缺点及适用性。依托项目实际情况,探讨合理的管道迁移或保护技术方案,为类似情况的工程提供参考。     

基于车辆加速度数据的互通立交匝道驾驶风险分析

为明确互通立交匝道的运行特性和驾驶风险,在重庆市南山立交和江南立交开展了超过30位被试者的小客车实车驾驶试验,通过Speedbox和Mobileye等车载高精度仪器采集了小客车在4条迂回式匝道上的连续运行数据,包括行驶速度、横向加速度、纵向加速度等,明确了迂回式匝道的车辆运行状态,然后运用表征横、纵向加速度关系的G-G图分析了匝道行驶过程中的驾驶风险,确定了立交匝道不同位置的危险等级及危险驾驶行为的高发路段。研究结果表明：①立交匝道上小客车的横向加速度与速度呈三角形分布,纵向加速度与速度呈椭圆形分布;②小半径曲线匝道上出现危险驾驶行为的比例要高于大半径曲线匝道;③通过统计不同断面的危险驾驶行为点占比,将匝道的危险断面分为低风险、中风险、高风险3个等级;④男性驾驶员在立交匝道上的危险驾驶行为占比要高于女性驾驶员,冒险型驾驶员的危险驾驶行为占比要高于其他驾驶风格的驾驶员;⑤立交匝道的危险高发路段通常位于速度变化剧烈的路段,即入弯减速段和出弯加速段。     

考虑车辆限行和装箱约束的车辆路径优化方法

在实际配送过程中,考虑到部分城市道路存在限制大型配送车辆通行的现状,以及运输途中车厢内物品满足后进先出等装载约束能有效提高装卸效率的特点,将车辆限行和二维装箱约束加入到需求可拆分车辆路径问题中。同时考虑到车辆的使用成本和行驶成本,以车辆总配送成本最小为目标构建考虑车辆限行和二维装箱约束的需求可拆分车辆路径问题数学模型,设计了启发式算法来求解该模型,其中模拟退火算法确定需求拆分下的车辆配送路径,且在当前最优解判断时调用BLF算法检验物品的二维装箱约束,来减少频繁调用BLF算法的时间。数值案例验证了模型和算法的实用性,且所提出的算法的求解结果波动不大于0.8%,能在合理的时间范围内求解得到较好的配送方案,在车辆限行区域内采用双车型配送能节省15.17%~31.27%的总配送成本。     

土压平衡盾构在复合地层中带压进仓施工技术

结合南京地铁土压平衡盾构在复合地层中带压进仓的具体情况,通过采取带压进仓压力计算、现场试验压力确定以及实施过程,成功地解决了土压平衡盾构进行带压进仓作业,了解掘进面存在的问题以及解决方式等技术难点.通过对监测数据的对比、分析,说明该方法的可行性及合理性,为土压平衡盾构在复合地层中带压进仓的施工提供参考与借鉴.     

基于GTM的岩沥青混合料性能研究

岩沥青以其生产便利性及与沥青间的良好配伍性,得到了研究学者的关注。分别对不同岩沥青掺量的基质沥青和SBS改性沥青开展试验研究;基于"干法"工艺,采用GTM法成型不同岩沥青掺量的基质沥青混合料和SBS改性沥青混合料并开展高温稳定性和水稳定性试验研究。结果表明,随着岩沥青掺量的增加,沥青的粘度和耐热性能逐渐增强,黏附性效果得到改善;沥青混合料的高温稳定性能明显提高,水稳定性有所改善。综合考虑成本问题,推荐岩沥青在基质沥青混合料和SBS改性沥青混合料中的掺量分别为3.0%和1.0%。     

A signal-based fault detection and classification method for heavy haul wagons

This paper proposes a signal-based fault detection and isolation (FDI) system for heavy haul wagons considering the special requirements of low cost and robustness. The sensor network of the proposed system consists of just two accelerometers mounted on the front left and rear right of the carbody. Seven fault indicators (FIs) are proposed based on the cross-correlation analyses of the sensor-collected acceleration signals. Bolster spring fault conditions are focused on in this paper, including two different levels (small faults and moderate faults) and two locations (faults in the left and right bolster springs of the first bogie). A fully detailed dynamic model of a typical 40t axle load heavy haul wagon is developed to evaluate the deterioration of dynamic behaviour under proposed fault conditions and demonstrate the detectability of the proposed FDI method. Even though the fault conditions considered in this paper did not deteriorate the wagon dynamic behaviour dramatically, the proposed FIs show great sensitivity to the bolster spring faults. The most effective and efficient FIs are chosen for fault detection and classification. Analysis results indicate that it is possible to detect changes in bolster stiffness of ±25% and identify the fault location.     

A receding horizon sliding control approach for electric powertrains with backlash and flexible half-shafts

Active control of electric powertrains is challenging, due to the fact that backlash and structural flexibility in transmission components can cause severe performance degradation or even instability of the control system. Furthermore, high impact forces in transmissions reduce driving comfort and possibly lead to damage of the mechanical elements in contact. In this paper, a nonlinear electric powertrain is modelled as a piecewise affine (PWA) system. The novel receding horizon sliding control (RHSC) idea is extended to constrained PWA systems and utilised to systematically address the active control problem for electric powertrains. Simulations are conducted in Matlab/Simulink in conjunction with the high fidelity Carsim software. RHSC shows superior jerk suppression and target wheel speed tracking performance as well as reduced computational cost over classical model predictive control (MPC). This indicates the newly proposed RHSC is an effective method to address the active control problem for electric powertrains.     

Quantifying travel time variability at a single bottleneck based on stochastic capacity and demand distributions

Travel time reliability, an essential factor in traveler route and departure time decisions, serves as an important quality of service measure for dynamic transportation systems. This article investigates a fundamental problem of quantifying travel time variability from its root sources: stochastic capacity and demand variations that follow commonly used log-normal distributions. A volume-to-capacity ratio-based travel time function and a point queue model are used to demonstrate how day-to-day travel time variability can be explained from the underlying demand and capacity variations. One important finding is that closed-form solutions can be derived to formulate travel time variations as a function of random demand/capacity distributions, but there are certain cases in which a closed-form expression does not exist and numerical approximation methods are required. This article also uses probabilistic capacity reduction information to estimate time-dependent travel time variability distributions under conditions of non-recurring traffic congestion. The proposed models provide theoretically rigorous and practically useful tools for understanding the causes of travel time unreliability and evaluating the system-wide benefit of reducing demand and capacity variability.     

Approximate optimal AUTOSAR software components deploying approach for automotive E/E system

The AUTOSAR has been developed as the worldwide standard for automotive E/E software systems, making the electronic components of different suppliers to be employed universally. However, as the number of component-based applications in modern automotive embedded systems grows rapidly and the hardware topology becomes increasingly complex, deploying such large number of components in automotive distributed system in manual way is over-dependent on experience of engineers which in turn is time consuming. Furthermore, the resource limitation and scheduling analysis make the problems more complex for developers to find out an approximate optimal deploying approach in system integration. In this paper, we propose a novel method to deploy the AUTOSAR components onto ECUs with the following features. First, a clustering algorithm is designed for deploying components automatically within relatively low time complexity. Second, a fitness function is designed to balance the ECUs load. The goal of our approach is to minimize the communication cost over all the runnable entities while meeting all corresponding timing constraints and balancing all the ECUs load. The experiment results show that our approach is efficient and has well performance by comparing with other existing methods in specific and synthetic data set.