基于北斗的节能型智能公交电子站牌的开发及应用

解决“市民出行难”问题一直是政府部门关注的民生问题,实现公交信息化是解决“出行难”问题的重要环节和出路.本文提出了一种基于北斗导航系统的节能型智能公交电子站牌系统结构设计方案,有利于市民选择公交作为出行方式.同时,能提升公交公司的服务水平和质量。     

温拌沥青混合料性能评价

从温拌的机理、价值、技术特点、路用性能、生产和施工工艺等方面论述了温拌沥青混合料技术。     

Public regulation and passengers importance in port infrastructure costs

Because ports are conceived and designed mainly to be the transfer point of various types of freight, passengers tend to be forgotten in the analysis of port costs. In this paper first we investigate the importance of passengers in port infrastructure costs by means of a multi-output cost function estimated from 20 annual observations (1986-2005) for 26 Spanish Port Authorities. Results show that, although a passenger weights on average less than one tenth of a ton, he or she represents as much as two tons of solid bulk and about three tons of containerized general cargo in terms of marginal costs. Secondly, we compare the marginal costs of different cargoes with their price caps established by law. Results suggest that some type of second best pricing is induced by present regulation.     

A review and analysis of the investment in,and cost structure of,intermodal rail terminals

The results presented in this article identify the role of costs in the scientific and grey freight terminal handling literature and analyses the handling costs of different terminal sizes. The literature review shows that handling costs only play a marginal role in the scientific research in intermodal rail freight terminals (IRT). This is remarkable given the large role costs occupy in decision-making in freight transport. Furthermore, the used cost levels show a wide range of proposed amounts and terminal sizes or handling technologies are seldom addressed. Finally, many of the scientific papers do not make it clear whether the average transhipment cost or market price is referred to. Next, the analysis of the investment in, and cost structure of, IRTs shows that IRT investments are very capital-intensive leading to relatively high average costs per handling. However, given the cost characteristics of IRTs, the average cost per handling represents the underlying cost structure and are – in this sense – representative. The cost analysis demonstrates that extra-large IRTs actually have the lowest average handling costs, followed by small IRTs.     

An energy-efficient scheduling approach to improve the utilization of regenerative energy for metro systems

Regenerative braking is an energy recovery mechanism that converts the kinetic energy during braking into electricity, also known as regenerative energy. In general, most of the regenerative energy is transmitted backward along the pantograph and fed back into the overhead contact line. To reduce the trains’ energy consumption, this paper develops a scheduling approach to coordinate the arrivals and departures of all trains located in the same electricity supply interval so that the energy regenerated from braking trains can be more effectively utilized to accelerate trains. Firstly, we formulate an integer programming model with real-world speed profiles to minimize the trains’ energy consumption with dwell time control. Secondly, we design a genetic algorithm and an allocation algorithm to find a good solution. Finally, we present numerical examples based on the real-life operation data from the Beijing Metro Yizhuang Line in Beijing, China. The results show that the proposed scheduling approach can reduce energy consumption by 6.97% and save about 1,054,388 CNY (or 169,223 USD) each year in comparison with the current timetable. Compared to the cooperative scheduling (CS) approach, the proposed scheduling approach can improve the utilization of regenerative energy by 36.16% and reduce the total energy consumption by 4.28%.     

Real-time optimization of ship energy efficiency based on the prediction technology of working condition

Ship energy efficiency management and control is an effective strategy to improve the marine economy and reduce CO₂ emission. The determination of the best navigation speed under different working conditions is the basis and premise for real-time improvement of ship energy efficiency. In this paper, the working condition in short distance ahead of the ship related to navigation environment factors was predicted by the method of wavelet neural network, and then the best engine speed for the optimal energy efficiency under different working conditions could be determined through the established ship energy efficiency real-time optimization model. Further, by presetting the ship engine at this optimal speed, the ship energy efficiency could be guaranteed at the optimal state when the ship arrived at the navigation environment ahead of the ship, thus achieving real-time optimization of ship energy efficiency under different navigation environment factors. Experimental studies showed that the proposed optimization model was effective in energy saving and emission reduction, which could provide theoretical guidance for optimal sailing of the ship in service. Compared to traditional setting speed navigation methods, our proposed method has more practical significance to the improvement of ship energy efficiency.     

Assessing the cost-optimal mileage of medium-duty electric vehicles with a numeric simulation approach

Electric freight vehicles have the potential to mitigate local urban road freight transport emissions, but their numbers are still insignificant. Logistics companies often consider electric vehicles as too costly compared to vehicles powered by combustion engines. Research within the body of the current literature suggests that increasing the driven mileage can enhance the competitiveness of electric freight vehicles. In this paper we develop a numeric simulation approach to analyze the cost-optimal balance between a high utilization of medium-duty electric vehicles – which often have low operational costs – and the common requirement that their batteries will need expensive replacements. Our work relies on empirical findings of the real-world energy consumption from a large German field test with medium-duty electric vehicles. Our results suggest that increasing the range to the technical maximum by intermediate (quick) charging and multi-shift usage is not the most cost-efficient strategy in every case. A low daily mileage is more cost-efficient at high energy prices or consumptions, relative to diesel prices or consumptions, or if the battery is not safeguarded by a long warranty. In practical applications our model may help companies to choose the most suitable electric vehicle for the application purpose or the optimal trip length from a given set of options. For policymakers, our analysis provides insights on the relevant parameters that may either reduce the cost gap at lower daily mileages, or increase the utilization of medium-duty electric vehicles, in order to abate the negative impact of urban road freight transport on the environment.     

Energy consumption in China’s logistics industry: A decomposition analysis using the LMDI approach

The logistics industry plays a critical role in boosting China’s economic development, although at significant externality costs. Using the 1980–2010 data, we examine the historical evolution of energy consumption in China’s logistics industry. The logarithmic mean Divisia index (LMDI) method was used to analyze the key factors that drove the chronicle changes in logistics energy consumption in China. Changes in energy consumption of China’s logistics industry are attributed to growth in logistics activity, modal shift in freight transportation, increases in transport intensity, and overall improvements in energy intensity: (1) China’s logistics industry enjoyed fast growth with an average annual growth rate of 9.65% from 1980 to 2010. Increase in logistics activity has been the major force driving up logistics energy consumption (accounting for 48.8% of logistics energy increase); (2) Logistics energy consumption increased by 22.91 times, averaging at 11.9% growth per year. Fuel consumption in highway transportation has become more dominant in logistics energy consumption; (3) While changes in logistics activities, transportation modes and transport intensity pushed up logistics energy consumptions, improvements in energy intensity helped significantly to curb the energy rise in China’s logistics industry.     

A computationally efficient simulation model for estimating energy consumption of electric vehicles in the context of route planning applications

The fact that electric vehicles (EVs) are characterized by relatively short driving range not only signifies the importance of routing applications to compute energy efficient or optimal paths, but also underlines the necessity for realistic simulation models to estimate the energy consumption of EVs. To this end, the present paper introduces an accurate yet computationally efficient energy consumption model for EVs, based on generic high-level specifications and technical characteristics. The proposed model employs a dynamic approach to simulate the energy recuperation capability of the EV and takes into account motor overload conditions to represent the vehicle performance over highly demanding route sections. To validate the simulation model developed in this work, its output over nine typical driving cycles is compared to that of the Future Automotive Systems Technology Simulator (FASTSim), which is a simulation tool tested on the basis of real-world data from existing vehicles. The validation results show that the mean absolute error (MAE) of cumulative energy consumption is less than 45 W h on average, while the computation time to perform each driving cycle is of the order of tens of milliseconds, indicating that the developed model strikes a reasonable balance between efficacy of representation and computational efficiency. Comprehensive simulation results are presented in order to exemplify the key features of the model and analyze its output under specific highly aggressive driving cycles for road gradients ranging from −6% to 6%, in support of its usability as a practical solution for estimating the energy consumption in EV routing applications.     

Vehicle energy efficiency evaluation from well-to-wheel lifecycle perspective

Given a fundamental role of automobiles in human society, evaluation of vehicle energy efficiency is of utmost importance. Various reports have been published hitherto concerning well-to-wheel (WTW) fuel consumption at the vehicle operation phase. On the other hand, WTW energy consumption at other lifecycle phases has been scarcely integrated in the assessment of vehicle energy efficiency. Particularly, WTW energy consumption for material structure is significantly associated with fuel economy. As such, this paper firstly analyzes the lifecycle WTW vehicle energy efficiency from the perspective of both material structures at the manufacture phase and fuel consumption at the operation phase for conventional vehicle (CV), electric vehicle (EV), hybrid vehicle (HV) and fuel cell vehicle (FCV). Then, an expected transition of vehicle weight and energy consumption arising from material structural shift through the replacement of steel with aluminum is evaluated. Finally, the overall vehicle energy efficiency in Japan in 2020–2050 is projected. It is discovered that the inclusion of energy consumption for material structure has a significant impact on the determination of the vehicle energy efficiency, particularly for new generation vehicles. WTW analysis at the multiple lifecycle phases may be of use in establishing more comprehensive principles of vehicle energy efficiency.