结构系统疲劳可靠性分析的一阶和二阶混合方法

本文提出了复杂结构系统疲劳可靠性分析的一阶和二阶混合方法。引进Ｈｏｈｅｎｂｉｃｈｌｅｒ等提出的并联系统可靠性分析的二阶渐近式计算失效途径的疲劳失效概率;利用并联系统等效线性安全余量的概念,形成由失效途径的等效失效单元组成的串联系统;并最终计算整个系统的疲劳失效概率。计算结果表明,这一方法能有效地提高结构系统疲劳失效概率的计算精度。     

车辆混合动力传动系统开发现状与展望

本文通过对车辆动力传动系统能量分配型式及特点的分析，提出在市区公共汽车等车辆上使用具有良好综合性能的混合动力传动系统。并对各种型式的车辆混合动力传动系统的研究现状进行了分析与总结，展望了未来的发展趋势，对以后的研究，开发具有指导意义。     

并联式混合动力电动汽车模糊控制策略的仿真研究

分析混合动力系统能量流动和功率平衡问题,推导出时间离散条件下能量流的表达式。结合不同的循环工况,从理论上比较电气辅助和模糊控制策略对于并联式混合电动汽车驱动系统工作的影响,并进行仿真研究。仿真结果表明,模糊控制策略明显优于电气辅助控制策略,汽车的油耗和废气排放水平均显著下降,整车效率得到提高,同时汽车动力性亦满足正常的行驶需求。     

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％。     

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.     

赤峰站改进货物运输服务的探讨

从分析赤峰站货运服务存在的主要问题入手,对货物运输服务的改进问题进行深入探讨,提出树立货运服务精品理念、改进服务制度、建立货运服务管理网络、落实安全长效机制等改进货运服务的主要思路和实施内容。