并联混合动力汽车ECMS的时变等效因子提取算法的研究

为解决当前等效燃油消耗最小控制策略(ECMS)未能根据实际工况选取最优等效因子的问题,利用动态规划算法(DP)和ECMS各自的优点,构建并联混合动力汽车能量算法模型,即采用动态规划算法的等效燃油消耗最小控制策略(ECMSwDP),将等效因子作为全局最优算法的控制变量,通过对等效因子的离散全局优化,获得基于工况的最佳时变等效因子。在标准工况下对时变等效因子实时控制策略与全局最优控制策略DP的各项性能参数进行了数值仿真,验证了时变等效因子提取算法的有效性和等效因子初始值选取方法的可行性。     

集装箱装卸设备采购项目管理中的约束条件和质量管理

以集装箱装卸设备采购工作为例,探讨项目管理中的约束条件(范围、费用、时间)与质量管理之间的关系,分析它们之间的相互作用和影响.     

竖向动荷载下桩尖附近应力场研究

在合理假设桩侧摩阻力在桩尖平面应力分布的基础上,推导了桩尖附近应力场公式,得出了在桩长、桩径、桩周土内摩擦角一定的情况下,桩尖地基应力与桩顶竖向动荷载的时程反应规律。并对影响桩尖地基应力的各因素进行了敏感分析,为桩尖附近其他地下结构的验算提供依据。     

土压平衡盾构到达钢套筒辅助施工接收技术

针对南京地铁3号线TA08标浮大区间土压平衡盾构法隧道施工遇到的特殊工程地质条件,采用土压平衡盾构到达钢套筒辅助工艺解决了施工难题。该技术不仅有效避免盾构到达接收过程中涌水、涌砂等风险,确保出洞安全,而且,钢套筒盾构接收方法的成功使用,提高了盾构到达接收洞门的密封质量及管片的拼装质量。     

Modelling parking choices considering user heterogeneity

We examine car driver’s behaviour when choosing a parking place; the alternatives available are free on-street parking, paid on-street parking and parking in an underground multi-storey car park. A mixed logit model, allowing for correlation between random taste parameters and estimated using stated choice data, is used to infer values of time, both when looking for a parking space and for accessing the final destination. Apart from the cost of parking, we found that vehicle age was a key variable when choosing where to park in Spain. We also found that the perception of the parking charge was fairly heterogeneous, depending both on the drivers’ income levels and whether or not they were local residents. Our results can be generalised for personalised policy making related with parking demand management.     

User perspectives in public transport timetable optimisation

The present paper deals with timetable optimisation from the perspective of minimising the waiting time experienced by passengers when transferring either to or from a bus. Due to its inherent complexity, this bi-level minimisation problem is extremely difficult to solve mathematically, since timetable optimisation is a non-linear non-convex mixed integer problem, with passenger flows defined by the route choice model, whereas the route choice model is a non-linear non-continuous mapping of the timetable. Therefore, a heuristic solution approach is developed in this paper, based on the idea of varying and optimising the offset of the bus lines. Varying the offset for a bus line impacts the waiting time passengers experience at any transfer stop on the bus line.In the bi-level timetable optimisation problem, the lower level is a transit assignment calculation yielding passengers’ route choice. This is used as weight when minimising waiting time by applying a Tabu Search algorithm to adapt the offset values for bus lines. The updated timetable then serves as input in the following transit assignment calculation. The process continues until convergence.The heuristic solution approach was applied on the large-scale public transport network in Denmark. The timetable optimisation approach yielded a yearly reduction in weighted waiting time equivalent to approximately 45 million Danish kroner (9 million USD).     

A time‐staged multi‐objective network‐design model

A multi‐objective, time‐staged network‐design problem is formulated. Through transformation, the problem is decomposed into a set of single‐period, single‐objective problems. Lexicographic ordering is instrumental in effecting this transformation; it also allows a backward‐recursion algorithm to be applied using strong pruning criteria. Furthermore, monotonicity properties enable us to solve the problem using the familiar tree‐search algorithms. The solution method has several desirable properties — as shown by an example and a case study of Tripoli Province, Libya. First, the algorithm ensures continuity of project implementation over the multi time‐periods and provides optimality in later computational stages irrespective of the decision at an interim stage. Second, the algorithm tends to provide accessibility to unconnected regions in the study area at low user‐cost without employing weights to the two objective functions of accessibility and user‐cost efficiency. Such a property is deemed advantageous for suggesting transportation investments based purely on purchasing the greatest benefit for each dollar, with political neutrality strictly maintained.     

Evaluating the effects of bus design on passenger flow: Is agent-based simulation a feasible approach?

In this paper, we propose an agent-based simulation approach that is capable of simulating the flow of passengers on board buses and at bus stops. The intention is that it will be applied during vehicle development to analyze how vehicle design affects passenger flow, and thus also how it affects system performance such as dwell time. In turn, this could aid the developers in making design decisions early in the development process. Besides introducing the simulation tool itself, the paper explores the realism of the data generated by the tool. A number of passenger flow experiments featuring a full-scale bus mockup and 50 participants were carried out. The setup of these experiments mirrored a number of ‘bus journeys’ (regarding vehicle design, number of passengers boarding/alighting at each stop and so on) that had previously been simulated using the simulation tool. When the data from the simulations were compared with the data from the passenger flow experiments, it could be concluded that the tool is indeed able to generate realistic passenger flows, although with some errors when a large number of passengers board/alight. The simulated dwell times were rationally affected by the tested bus layout aspects. It was concluded that the tool makes it possible to evaluate how variations in bus layouts affect passenger flow, providing data of sufficiently high quality to be useful in early phases of vehicle design.     

Forecasting bunker prices; A nonstationary,multivariate methodology

This paper suggests a methodological approach for the forecasting of marine fuel prices. The prediction of the bunker prices is of outmost importance for operators, as bunker prices affect heavily the economic planning and financial viability of ventures and determine decisions related to compliance with regulations. A multivariate nonstationary stochastic model available in the literature is being retrieved, after appropriate adjustment and testing. The model belongs to the class of periodically correlated stochastic processes with annual periodic components. The time series are appropriately transformed to become Gaussian, and then are decomposed to deterministic seasonal characteristics (mean value and standard deviation) and a residual time series. The residual part is proved to be stationary and then is modeled as a Vector AutoRegressive Mooving Average (VARMA) process. Finally, using the methodology presented, forecasts of a tetra-variate and an octa-variate time series of bunker prices are produced and are in good agreement with actual values. The obtained results encourages further research and deeper investigation of the driving characters of the multivariate time series of bunker prices.