The design of electric vehicle charging network

The promotion of Electric Vehicles (EVs) has become a key measure of the governments in their attempt to reduce greenhouse gas emissions. However, range anxiety is a big barrier for drivers to choose EVs over traditional vehicles. Installing more charging stations in appropriate locations can relieve EV drivers’ range anxiety. To determine the locations of public charging stations, we propose two optimization models for two different charging modes - fast and slow charging, which aim at minimizing the total cost while satisfying certain coverage goal. Instead of using discrete points, we use geometric objects to represent charging demands. Importantly, to resolve the partial coverage problem (PCP) for networks, we extend the polygon overlay method to split the demands on the road network. After applying the models to Greater Toronto and Hamilton Area (GTHA) and to Downtown Toronto, we show that the proposed models are practical and effective in determining the locations of charging stations. Moreover, they can eliminate PCP and provide much more accurate results than the complementary partial coverage method (CP).     

Online distributed cooperative model predictive control of energy-saving trajectory planning for multiple high-speed train movements

The cooperative energy-efficient trajectory planning for multiple high-speed train movements is considered in this paper. We model all the high-speed trains as the agents that can communicate with others and propose a local trajectory planning control model using the Model Predictive Control (MPC) theory. After that we design an online distributed cooperative optimization algorithm for multiple train trajectories planning, under which each train agent can regulate the trajectory planning procedure to save energy using redundancy trip time through tuning ACO’s heuristic information parameter. Compared to the existing literature, the vital distinctions of our work lies not only on the online cooperative trajectory planning but also on the distributed mechanism for multiple high-speed trains. Experimental studies are given to illustrate the effectiveness of the proposed methods with the practical operational data of Wuhan-Guangzhou High-speed Railway in China.     

多维随机不确定性下的船舶多学科稳健设计优化研究

通常船舶多学科设计优化仅考虑确定性的影响,忽视设计中不确定性因素的存在,显然优化结果无法真正保障船型方案的可行性和航行性能的优良性。目前,不确定性船舶多学科设计优化主要集中在一维不确定性分析。为了得到船舶设计优化的最优方案,以多维不确定性下的多学科稳健设计优化问题为例,通过分析考虑随机不确定性因素的均匀分布和正态分布并存分布状况,提出了一种新的以Legendre polynomials和Hermite polynomials多项式为基础的多维多项式混沌方法,并以海洋平台支持船为对象构建多维不确定性量化模型。通过对多维随机不确定性因素对船舶优化方案的影响分析完成了船舶多学科稳健设计优化研究,有效地减少和避免船舶设计优化方案失效的可能性。     

基于代理模型的复合材料带加强筋板多目标优化

本文以复合材料带加强筋板的质量、刚度及屈曲载荷为优化目标,在铺层约束下对加强筋的铺层数、铺层顺序以及截面尺寸进行多目标优化。为了使NSGA-Ⅱ算法适应于可变铺层数的铺层顺序优化,对算法的基因编码方式进行改造并在遗传操作中引入Permutation操作。优化过程中采用代理模型对结构的刚度及屈曲载荷进行估计,减少了有限元模型的调用次数。算例表明通过优化算法的改造及代理模型的引入降低了优化成本。     

基于响应面方法的车钩缓冲器特性曲线优化分析

为了更加真实地反映车钩缓冲器实际工作状态和进行缓冲器特性曲线优化,提出采用列车纵向动力学系统对缓冲器的特性曲线进行分析。在优化方面,从响应面方法的基本原理出发,建立响应面的子区域构造方法,运用凝聚函数和惩罚技术处理约束的遗传算法求解加约束条件的二次响应面最优解。以大秦线实际线路、列车编组以及列车纵向动力学性能为优化计算的条件,结合缓冲器数值模型建立缓冲器特性曲线的优化模型,运用所提出基于遗传算法的响应面方法对重载列车缓冲器特性曲线进行优化求解。结果说明所提方法对求解缓冲器特性曲线的优化问题非常有效。     

Highway alignment optimization through feasible gates

An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model's computation time and solution quality. Such improvements are demonstrated with two test examples from a real road project.     

Consequences of Nonlinear Characteristics of a Secondary Suspension in a Three-Piece Freight Car Bogie

Mechanical systems with nonlinear characteristics can show a complex dynamic behavior that should be taken into account when analysing dynamic performance and reliability. The dynamic behavior of the main suspension in a three-piece freight car bogie with constant friction damping is considered in this work. The aim is to investigate the vertical behavior of a specific suspension design due to different driving conditions, weather and wear of the friction wedges. A variation in weather and wear is represented by different friction configurations in the model of the suspension. Models of different levels of detail that are based on experimental data on existing designs are developed. It is found that the suspension performance is very sensitive to variations of the friction configuration and this indicates a possible presence of nonlinear dynamic phenomena at in service like conditions.     

中心站间铁路集装箱运输径路选择优化研究

采用系统观点和类比方法,运用运输组织、离散数学、最优化理论等相关理论,对中心站间集装箱运输径路选择问题的参数和模型进行了深入的研究。在分析和借鉴已有车流径路选择优化模型的基础上,构建了重箱流径路选择的多目标0-1规划模型,并经过对相关算法的研究和分析,选择DBFS和GP作为模型的求解方法。     

列车运行调整微粒群算法研究

列车运行调整问题是铁路行车调度指挥工作的重要内容,决定着区段内行车秩序的优劣。这一问题的计算机自动求解算法是我国铁路信息化建设的一个核心技术和难点问题。本文依据我国铁路行车组织体制的特点,建立了相应的模型。在模型的求解过程中,先运用大系统理论将列车进行分层分级,从而将待解的原始问题分解成若干个子问题,在对分解后的问题进行求解时,设计了微粒群算法,运用该算法可快速得到各子问题的近似最优解。然后,应用系统原理对问题进行还原,即可快速得到一个满意度高、可用性强的列车运行调整方案。最后,采用现场数据,应用该算法对列车运行调整问题进行求解,并与遗传算法进行比较,结果表明微粒群算法解决列车运行调整问题高效、实用。     

列流图优化布局与编制方法

列流图是展示通过某铁路区域的各类客货列流(列车流)的类别、径路和列车数量的直观图形表示形式,列流图包括铁路网络和列流线2部分。通过分析列流图的站场布局合理性、列流线的对称性及尽可能避免交叉等优化编制目标,提出编制列流图的左右、紧凑、分层、对称和分类5种排列原则,以及5种排列原则相冲突时应遵循的先后顺序,给出编制列流图的步骤,据此开发优化编制列流图的计算机软件系统。该系统采用图形输入铁路网络、列表输入列流,根据列流线排列原则和步骤自动生成列流图,并可导出CAD图形文件。对包括3个车站和7个方向的某区域铁路网络,运用该系统编制出具有60余条列流线的列流图。