Influence of AC system design on the realisation of tractive efforts by high adhesion locomotives

The main task for heavy haul railway operators is to reduce the cost of exported minerals and enhance the long-term viability of rail transport operations through increasing productivity by running longer and heavier trains. The common opinion is that this is achievable by means of implementation of high adhesion locomotives with advanced AC traction technologies. Modern AC high adhesion locomotives are very complex mechatronic systems and can be designed with two alternative traction topologies of either bogie or individual axle controls. This paper describes a modelling approach for these two types of AC traction systems with the application of an advanced co-simulation methodology, where an electrical system and a traction algorithm are modelled in Matlab/Simulink, and a mechanical system is modelled in a multibody software package. Although the paper concentrates on the analysis of the functioning for these two types of traction control systems, the choice of reference slip values also has an influence on the performance of both systems. All these design variations and issues have been simulated for various adhesion conditions at the wheel–rail interface and their influence on the high traction performance of a locomotive equipped with two three-axle bogies has been discussed.     

基于响应面和遗传算法的柴油机瞬态过程喷油参数优化

基于台架试验数据,利用响应面法建立了某工程机械用柴油机瞬态过程喷油参数与性能的近似高精度模型,基于此模型采用遗传算法对瞬态过程喷油参数分别进行离线优化研究。结果表明:采用单目标优化确定的燃油消耗率(BSFC)、NO_x比排放量和颗粒质量(PM)比排放量的优化极限分别可达180.23g/(kW·h),8.92g/(kW·h)和0.011 8g/(kW·h),相对原机可降低多达4.5%,34.0%和37.3%。双目标优化的Pareto解集表明,相比于同时优化BSFC和NO_x比排放量,BSFC和PM比排放量更容易同时得到优化。采用权重因子适应度函数的三目标优化结果对应的BSFC,NO_x比排放量及PM比排放量分别为184.70g/(kW·h),12.62g/(kW·h)和0.012 2g/(kW·h),较原机分别降低2.1%,6.6%和35.3%。改进优化模型后,性能优化Pareto解集对应的BSFC和PM比排放量水平都非常接近其优化极限,但NO_x比排放量相对其优化极限仍然较高。     

基于小波和粒子群算法的HEV行驶状况辨识方法研究

针对混合动力汽车(HEV)行驶状况(道路坡度和整车载荷)变化难以有效识别,导致驱动系统控制策略不能有效满足驾驶员意图问题,以混联式HEV为研究对象,提出了基于小波滤波和粒子群算法的HEV行驶状况辨识方法。首先建立了汽车行驶状况辨识模型,采用最小二乘法确立了优化目标函数,其次研究了基于小波滤波和粒子群算法的HEV行驶状况辨识原理,最后进行了行驶状况粒子群智能算法辨识试验。在采集实车数据的基础上,对实车数据进行小波滤波,并运用行驶状况辨识方法对道路坡度和整车载荷进行了辨识,并对辨识结果进行小波滤波,结果表明,试验工况下整车载荷辨识的相对误差绝对平均值为2.71%,道路坡度辨识的相对误差绝对平均值为3.85%,验证了所提出方法的有效性。     

路锥投收自动控制系统的研制

针对高速公路交通事故现场快速隔离、警示和防护等日益增强的需求,提出一种新型路锥自动投收装置的系统设计方案.针对传统大型路锥投收装置费用高、结构复杂的弊端,利用虚拟样机技术开展紧凑型路锥自动铺设、回收一体化装置的机械结构的设计,包括路锥的叠置、拾取、传送、放置等机构.并利用Pro/E、ADMAS等仿真软件进行仿真测试.基于ARM提出嵌入式的系统总体设计方案:以uCOS-II操作系统为平台,以STM32系列单片机为CPU,完成控制器的软硬件设计,并采用"S"型加减速控制曲线策略实现电机的平滑控制.基于Android开发了操作方便、友好的人机交互接口,以"蓝牙"作为上下位机的通信桥梁,以RSA算法作为上下位机数据交互中的安全的保障.实车测试结果表明,该设计方案的路锥投放与回收成功率均达到95%,基本符合要求.但高、低速时路锥投放、回收的成功率差异较大(6%),此外,路锥的倒伏率达到5%,该单项指标基本不满足设计要求.     

基于时空GPSO-SVM的短时交通流预测

为了提高城市道路短时交通流预测的精度,提出了一种基于时空遗传粒子群支持向量机的短时交通流预测模型.通过主成分分析法对路网原始交通流量进行时空相关性分析,用较少的主成分代替原始交通流量并作为预测因子,在粒子群算法中引入遗传算法的交叉和变异因子,避免粒子群算法陷入局部最优.利用改进后的粒子群算法优化支持向量机参数,得到最优的支持向量机模型,并实现城市道路的短时交通流预测.以长春市路网的实测数据为基础进行了实例验证,结果表明,优化支持向量机参数时,遗传粒子群算法不会陷入局部最优,优化效果更好;与粒子群支持向量机模型和遗传粒子群支持向量机模型相比,所提出预测模型的相对误差波动较稳定,平均预测精度分别提高了4.96%和3.41%.     

基于遗传支持向量机的综合管廊土建工程造价估算方法研究

综合管廊工程造价估算具有影响因素多、小样本及非线性的特点,传统的造价估算方法对于这类问题无法得到准确结果。针对这一问题,提出一种基于遗传支持向量机的综合管廊造价估算模型。分析综合管廊工程的具体特征,运用支持向量机建立工程造价与影响因子之间的非线性映射关系,利用遗传算法对支持向量机进行参数优化并对综合管廊的工程造价进行估算。以16条已建综合管廊工程作为数据库样本,对该模型进行分析验证。样本测试结果显示,利用该模型可将估算误差控制在10%以内,验证了模型估算的可行性。     

Study on driver model for hybrid truck based on driving simulator experimental results

In this paper, a proposed car-following driver model taking into account some features of both the compensatory and anticipatory model representing the human pedal operation has been verified by driving simulator experiments with several real drivers. The comparison between computer simulations performed by determined model parameters with the experimental results confirm the correctness of this mathematical driver model and identified model parameters. Then the driver model is joined to a hybrid vehicle dynamics model and the moderate car following maneuver simulations with various driver parameters are conducted to investigate influences of driver parameters on vehicle dynamics response and fuel economy. Finally, major driver parameters involved in the longitudinal control of drivers are clarified.     

An approach to geometric optimisation of railway catenaries

The quality of current collection becomes a limiting factor when the aim is to increase the speed of the present railway systems. In this work an attempt is made to improve current collection quality optimising catenary geometry by means of a genetic algorithm (GA). As contact wire height and dropper spacing are thought to be highly influential parameters, they are chosen as the optimisation variables. The results obtained show that a GA can be used to optimise catenary geometry to improve current collection quality measured in terms of the standard deviation of the contact force. Furthermore, it is highlighted that apart from the usual pre-sag, other geometric parameters should also be taken into account when designing railway catenaries.     

软弱土（φ≠0）地基上加筋路堤稳定性分析

探讨软弱土(φ≠0)地基加筋路堤稳定性分析方法。针对传统分析方法因对加筋材料的加筋作用估计不足，导致计算结果过于保守问题，文中在充分考虑加筋体的加筋作用下，提出了加筋路堤稳定性分析新的改进分析计算方法，并同时提出采用演化算法搜索临界滑动面和最小安全系数。算例计算结果表明，提出的加筋路堤稳定性分析方法与工程实际情况吻合较好，而且混合演化算法能有效地搜索到路堤所有的临界滑动面。     

液压半主动悬架的自适应神经网络控制

提出了液压半主动悬架系统的自适应神经网络控制策略 ,分析了系统模型及自适应神经网络控制器的设计和实现 ,并对控制效果进行了仿真研究。结果表明通过这种控制策略可以得到比较好的控制效果。