应用ADVISOR研究丰田混合动力系统

研究了丰田混合动力系统及其主要控制策略，利用ADVISOR软件对Prius轿车的加速过程和燃油经济性进行了模拟计算，并与试验结果进行了对比。UDDS工况下计算的油耗为4．88-5.65L／100km，EPA的试验结果为4．85L／100km；HWFET工况下计算的油耗为3．35-4．28L／100km，EPA的试验结果为4．37L／100km。     

并联混合动力客车再生制动仿真研究

建立了并联式混合动力汽车动力学模型,并对纯电机制动模式和机电混合模式混合动力汽车能量再生制动进行了仿真。仿真结果表明：对于纯电机模式,制动效能低,能量回收率达29％;对于机电混合制动模式,制动效能高,能量回收率仅2％。     

高速公路交通流的分形维数与相空间重构预测

对成渝高速公路短时交通流通过计算不同时间尺度下Hurst指数而等到其相应的分形维数,结果表明,时间间隔越短的交通流,其分形维数越大,结构越复杂.由于时间间隔越短的交通流随机性大和复杂的结构,所以预测也就越困难.提出了一种新的基于相空间重构和移动平均相结合的预测方法——移动平均最近邻域法,从理论与实际数据两方面分析和验证了该方法对短时交通流预测的有效性.     

Impact of vehicle usage on consumer choice of hybrid electric vehicles

We analyze the vehicle usage and consumer profile attributes extracted from both National Household Travel Survey and Vehicle Quality Survey data to understand the impact of vehicle usage upon consumers’ choices of hybrid electric vehicles in the US. In addition, the key characteristics of hybrid vehicle drivers are identified to determine the market segmentations of hybrid electric vehicles and the critical attributes to include in the choice model. After a compatibility test of two datasets, a pooled choice model combining both data sources illustrates the significant influences of vehicle usage upon consumers’ choices of hybrid electric vehicles. Even though the data-bases have in the past been used independently to study travel behavior and vehicle quality ratings, here we use them together.     

Investigating heterogeneity in social influence by social distance in car-sharing decisions under uncertainty: A regret-minimizing hybrid choice model framework based on sequential stated adaptation experiments

The present study is designed to investigate social influence in car-sharing decisions under uncertainty. Social influence indicates that individuals’ decisions are influenced by the choices made by members of their social networks. An individual may experience different degrees of influence depending on social distance, i.e. the strength of the social relationship between individuals. Such heterogeneity in social influence has been largely ignored in the previous travel behavior research. The data used in this study stems from an egocentric social network survey, which measures the strength of the social relationships of each respondent. In addition, a sequential stated adaptation experiment was developed to capture more explicitly the effect of social network choices on the individual decision-making process. Social distance is regarded as a random latent variable. The estimated social distance and social network choices are incorporated into a social influence variable, which is treated as an explanatory variable in the car-sharing decision model. To simultaneously estimate latent social distance and the effects of social influence on the car-sharing decision, we expand the hybrid choice framework to incorporate the latent social distance model into discrete choice analysis. The estimation results show substantial social influence in car-sharing decisions. The magnitude of social influence varies according to the type of relationship, similarity of socio-demographics and the number of social interactions.     

基于C167CS微控制器的混合动力整车主控制器研制

混合动力汽车(HybridElectricVehicle,HEV)具备了内燃机汽车加油方便、续驶里程长和纯电动汽车污染少、效率高的优点,已经成为汽车界竞相开发的热点。本文结合混合动力汽车开发的项目实践,阐述了基于英飞凌C167CS微处理器的整车主控制器的硬件、底层驱动软件、安全模式的设计思路以及各节点间CAN通讯的硬件实现。详细介绍了英飞凌产品:16位控制器C167CS、CAN总线收发器TLE6250G、继电器驱动用上位开关BTS724的具体应用。     

基于扩展摩尔邻域的自由飞行冲突风险研究

为解决三维空间中,自由飞行条件下航空器间的飞行冲突风险判定问题,提出了基于扩展摩尔邻域的飞行冲突风险判定方法.首先分析平面摩尔近邻模型的特点,将其扩展至三维离散空间;然后建立水平、垂直飞行冲突风险可能性表格,提出计算三维飞行冲突风险的方法;最后分别用水平、垂直飞行冲突风险分开和同时计算的方法对同一仿真数据进行计算.结果表明:采用扩展的三维不同层摩尔邻域可以实现空域内航空器的飞行冲突风险的快速计算;水平、垂直飞行冲突风险同时计算的方式可以更快速地解决问题;同时,空间基础单元的间隔选择也会极大影响模型的运算效率.     

Development of hybrid optimization of train schedules model for N-track rail corridors

From a capacity perspective, efficient utilization of a railway corridor has two main objectives; avoidance of schedule conflicts, and finding a proper balance between capacity utilization and level of service (LOS). There are several timetable tools and commercial rail simulation packages available to assist in reaching these objectives, but few of them offer both automatic train conflict resolution and automatic timetable management features for the different types of corridor configurations. This research presents a new rescheduling model to address some of the current limitations. The multi-objective linear programming (LP) model is called “Hybrid Optimization of Train Schedules” (HOTS), and it works together with commercial rail simulation tools to improve capacity utilization or LOS metrics. The HOTS model uses both conflict resolution and timetable compression techniques and is applicable to single-, double-, and multiple-track corridors (N-track networks), using both directional and bi-directional operations. This paper presents the approach, formulation and data requirements for the HOTS model. Single and multi-track case studies test and demonstrate the model’s train conflict resolution and timetable compression capabilities, and the model’s results are validated by using RailSys simulation package. The HOTS model performs well in each tested scenario, providing comparable results (either improved or similar) to the commercial packages.     

A model and optimization-based heuristic for the operational aircraft maintenance routing problem

This paper investigates the Operational Aircraft Maintenance Routing Problem (OAMRP). Given a set of flights for a specific homogeneous fleet type, this short-term planning problem requires building feasible aircraft routes that cover each flight exactly once and that satisfy maintenance requirements. Basically, these requirements enforce an aircraft to undergo a planned maintenance at a specified station before accumulating a maximum number of flying hours. This stage is significant to airline companies as it directly impacts the fleet availability, safety, and profitability. The contribution of this paper is twofold. First, we elucidate the complexity status of the OAMRP and we propose an exact mixed-integer programming model that includes a polynomial number of variables and constraints. Furthermore, we propose a graph reduction procedure and valid inequalities that aim at improving the model solvability. Second, we propose a very large-scale neighborhood search algorithm along with a procedure for computing tight lower bounds. We present the results of extensive computational experiments that were carried out on real-world flight networks and attest to the efficacy of the proposed exact and heuristic approaches. In particular, we provide evidence that the exact model delivers optimal solutions for instances with up to 354 flights and 8 aircraft, and that the heuristic approach consistently delivers high-quality solutions while requiring short CPU times.     

船用柴油机混合能源系统配置优化

考虑新能源的间歇性以及船舶电力系统负载的突变性和波动性,本文首先根据船舶航行中经纬度和海上环境的变化对新能源的参数进行修正,然后构造同时计及成本与使用寿命的船用柴油机混合能源系统优化配置目标函数,再利用人工蜂群算法进行优化,从而获得最佳的系统配置。船舶航行实测试验验证该方法的可行性,同时表明了它比陆地上传统方法具有更好的优化配置性能。