国内外铁路交通事故和事故征候管理研究

为促进我国铁路技术和安全管理与国际接轨,持续提升我国铁路的国际影响力,研究欧盟、美国、日本、澳大利亚等组织和国家铁路交通事故及事故征候管理模式,分析其机构设置、事故或事故征候的定义及等级划分、调查理念等方面的特点,提出改进我国铁路交通事故管理的建议.建议明确我国铁路交通事故征候的定义及范围划分标准,建立完善管理制度和事...     

基于SOC估算的船用锂电池组健康管理研究

船用锂电池是新能源船舶的重要设备,如何精确的估计锂电池的荷电状态以及根据船舶运行工况进行对锂电池组的健康管理是保障船舶安全经济运营的关键。通过Vmin无迹卡尔曼滤波法对船用锂电池组的荷电状态(SOC)估计,仿真验证了Vmin无迹卡尔曼滤波法在估算电池组SOC时有较高精度;同时,结合船舶运行工况研发锂电池组健康管理策略,对船用锂电池组的SOC,单体电压,电流,光伏发电功率多参数综合分析,把电池状态分为健康,亚健康,不健康三种状态。实船运行表明,该电池组健康管理能保障锂电池组工作在安全范围内,有效促进船舶的安全运行。     

Comparison of energy demands of drone-based and ground-based parcel delivery services

Drones are one of the most intensively studied technologies in logistics in recent years. They combine technological features matching current trends in transport industry and society like autonomy, flexibility, and agility. Among the various concepts for using drones in logistics, parcel delivery is one of the most popular application scenarios. Companies like Amazon test drones particularly for last-mile delivery intending to achieve both reducing total cost and increasing customer satisfaction by fast deliveries. As drones are electric vehicles, they are also often claimed to be an eco-friendly mean of transportation.In this paper an energy consumption model for drones is proposed to describe the energy demand for drone deliveries depending on environmental conditions and the flight pattern. The model is used to simulate the energy demand of a stationary parcel delivery system which serves a set customers from a depot. The energy consumed by drones is compared to the energy demand of Diesel trucks and electric trucks serving the same customers from the same depot.The results indicate that switching to a solely drone-based parcel delivery system is not worthwhile from an energetic perspective in most scenarios. A stationary drone-based parcel delivery system requires more energy than a truck-based parcel delivery system particularly in urban areas where customer density is high and truck tours are comparatively short. In rather rural settings with long distances between customers, a drone-based parcel delivery system creates an energy demand comparable to a parcel delivery system with electric trucks provided environmental conditions are moderate.     

Modelling energy consumption of electric freight vehicles in urban pickup/delivery operations: analysis and estimation on a real-world dataset

Electric Freight Vehicles (EFVs) are a promising and increasingly popular alternative to conventional trucks in urban pickup/delivery operations. A key concerned research topic is to develop trip-based Tank-to-Wheel (TTW) analyses/models for EFVs energy consumption: notably, there are just a few studies in this area. Leveraging an earlier research on passenger electric vehicles, this paper aims at filling this gap by proposing a microscopic backward highly-resolved power-based EFVs energy consumption model (EFVs-ECM). The model is estimated and validated against real-world data, collected on a fleet of five EFVs in the city centre of Rome, for a total of 144 observed trips between subsequent pickup/delivery stops. Different model specifications are tested and contrasted, with promising results, in line with previous findings on electric passenger vehicles.     

Evaluation of energy consumption of vehicles in EU Trans-European Transport Network

The paper presents the results of field tests evaluating energy consumption in the vehicles of Trans-European Transport Network (TEN-T) of selected EU countries: Poland, Germany and France. The energy consumption of vehicles in a highway system was assessed based on the telemetry analysis systems for traction parameters, tachograph record of digital speed waveform and their statistical analysis. The empirical cumulative distribution functions of speed transitions (acceleration, deceleration) were used to determine the kinetic energy losses of the vehicle (fuel consumption). To assess the statistical significance of differences between cumulative distribution functions the Smirnov–Kolmogorov test was used.     

The importance of the use phase on the LCA of environmentally friendly solutions for asphalt road pavements

In order to assess sustainability of products and processes, different methodologies have been developed and used in the last years. In the road pavement construction area, most methodologies used for Life Cycle Assessment (LCA) are essentially focused in the construction phase. The present paper analyses the importance of the use phase of a road in the LCA of different paving alternatives, namely by evaluating energy consumption and gaseous emissions throughout the road pavement’s life. Therefore, a new LCA methodology for road pavements was developed, and the results of its application to a case study involving the construction of alternative pavement structures are discussed. The study intends to assess the influence of using more sustainable paving construction alternatives (asphalt recycling vs. conventional asphalt mixtures), and/or different surface course materials (which have a higher influence on the rolling resistance and, therefore, affect the performance during the use phase). The LCA results obtained for this case study showed that the reductions in energy consumption and gaseous emissions obtained during the use phase, for pavement alternatives with a lower rolling resistance surface course, are higher than the total amount of energy consumption and gas emissions produced during construction. It is therefore clear that some improvements in the characteristics of the surface course may have an effect over the road use phase that will rapidly balance the initial costs and gas emissions of those interventions. The LCA results obtained also showed that the sustainability of pavement construction may also be improved using recycled asphalt mixtures.     

Analysis of energy consumption of food transit in an urban agglomeration in Poland

The paper presents the results of research on operational energy consumption of a vehicle in conditions of urban transit in Poland. An important role in Intelligent Transportation Systems in the road transport is played by transit in urban agglomerations. The analysis was based on the use of telemetry systems and statistical analysis of the waveform of digital speed recording. The resulting empirical cumulative distribution functions of phases of acceleration and deceleration speeds allowed to determine the kinetic losses of the vehicle (fuel consumption). The statistical significance of differences between cumulative distribution functions was tested using the Smirnov–Kolmogorov test.     

Increased energy efficiency in short sea shipping through decreased time in port

According to a range of assessments, there exists a large cost-effective potential to increase energy efficiency in shipping through reduced speed at sea enabled by shorter time in port. This means that the energy needed can be reduced whilst maintaining the same transport service. However, the fact that a large cost-effective potential has been identified that is not being harnessed by decision-makers in practice suggests that there is more to this potential to understand. In this paper, the possibilities for increasing energy efficiency by reducing waiting time in port are explored and problematised through a case study of a short sea bulk shipping company transporting dry bulk goods mainly in the North and Baltic seas. Operational data from two ships in the company’s fleet for one year showed that the ships spent more than 40% of their time in ports and that half of the time in port was not productive. The two most important reasons for the large share of unproductive time were that ports were closed on nights and weekends and that ships arrived too early before the stevedores were ready to load or unload the cargo. Reducing all of the unproductive time may be difficult, but the results also show that even a conservative estimate of one to four hours of reduced time per port call would lead to a reduction in energy use of 2–8%. From in-depth interviews with employees of the shipping company, ports and ship agencies, a complex picture is painted when attempting to understand how this potential arises. Aspects such as a lack of effective ship-shore-port communication, little time for ship operators, an absence of means for accurately predicting energy use of voyages as a function of speed, perceived risk of arriving too late, and relationships with third-party technical management may all play a role.     

Inference on mode preferences,vehicle purchases,and the energy paradox using a Bayesian structural choice model

Discrete choice modeling is experiencing a reemergence of research interest in the inclusion of latent variables as explanatory variables of consumer behavior. There are several reasons that motivate the integration of latent attributes, including better-informed modeling of random consumer heterogeneity and treatment of endogeneity. However, current work still is at an early stage and multiple simplifying assumptions are usually imposed. For instance, most previous applications assume all of the following: independence of taste shocks and of latent attributes, exclusion restrictions, linearity of the effect of the latent attributes on the utility function, continuous manifest variables, and an a priori bound for the number of latent constructs. We derive and apply a structural choice model with a multinomial probit kernel and discrete effect indicators to analyze continuous latent segments of travel behavior, including inference on the energy paradox. Our estimator allows for interaction and simultaneity among the latent attributes, residual correlation, nonlinear effects on the utility function, flexible substitution patterns, and temporal correlation within responses of the same individual. Statistical properties of the Bayes estimator that we propose are exact and are not affected by the number of latent attributes.     

Reducing the energy consumption of heavy goods vehicles through the application of lightweight trailers: Fleet case studies

Reducing the empty weight of articulated heavy goods vehicle trailers is one avenue that needs to be explored in reducing the carbon footprint of the road freight industry as a whole. A statistical analysis of two heavy goods vehicle fleets operating in the United Kingdom has helped to identify double-deck trailers used in grocery haulage and ‘walking-floor’ trailers used in bulk haulage as two examples of trailers that can benefit significantly from lightweighting. Energy consumption of numerous articulated heavy goods vehicles is quantified through an idealised drive cycle analysis reflecting a long haul journey over a highway. This energy analysis allows for a mass energy performance index to be established. The analysis has shown that reducing the empty weight of trailers by 30% can cause reductions of up to 18% and 11% in mass energy performance index for double-deck trailers and ‘walking-floor’ trailers respectively. Using this approach, trailers that will benefit the most from weight reduction can be identified systematically, allowing for lightweighting strategies to be implemented more effectively. Strategies to reduce empty trailer weight and improve vehicle utilisation are also discussed.