Energy impact evaluation for eco-routing and charging of autonomous electric vehicle fleet: Ambient temperature consideration

This paper studies the heterogeneous energy cost and charging demand impact of autonomous electric vehicle (EV) fleet under different ambient temperature. A data-driven method is introduced to formulate a two-dimensional grid stochastic energy consumption model for electric vehicles. The energy consumption model aids in analyzing EV energy cost and describing uncertainties under variable average vehicle trip speed and ambient temperature conditions. An integrated eco-routing and optimal charging decision making framework is designed to improve the capability of autonomous EV’s trip level energy management in a shared fleet. The decision making process helps to find minimum energy cost routes with consideration of charging strategies and travel time requirements. By taking advantage of derived models and technologies, comprehensive case studies are performed on a data-driven simulated transportation network in New York City. Detailed results show us the heterogeneous energy impact and charging demand under different ambient temperature. By giving the same travel demand and charging station information, under the low and high ambient temperature within each month, there exist more than 20% difference of overall energy cost and 60% difference of charging demand. All studies will help to construct sustainable infrastructure for autonomous EV fleet trip level energy management in real world applications.     

A three-level framework for performance-based railway timetabling

The performance of railway operations depends highly on the quality of the railway timetable. In particular for dense railway networks it can be challenging to obtain a stable robust conflict-free and energy-efficient timetable with acceptable infrastructure occupation and short journey times. This paper presents a performance-based railway timetabling framework integrating timetable construction and evaluation on three levels: microscopic, macroscopic, and a corridor fine-tuning level, where each performance indicator is optimized or evaluated at the appropriate level. A modular implementation of the three-level framework is presented and demonstrated on a case study on the Dutch railway network illustrating the feasibility of this approach to achieve the highest timetabling design level.     

A framework for estimating traffic emissions: The development of Passenger Car Emission Unit

In this study, we develop a Passenger Car Emission Unit (PCEU) framework for estimating traffic emissions. The idea is analogous to the use of Passenger Car Unit (PCU) for modeling the congestion effect of different vehicle types. In this approach, we integrate emission modeling and cost evaluation. Different emissions, typically speed-dependent, are integrated as an overall cost via their corresponding external costs. We then develop a normalization procedure to obtain a general trend that is applicable for all vehicle types, which is used to derive a standard cost curve. Different vehicle types with different emission standards are then mapped to this standard cost curve through their corresponding PCEUs that are to be calibrated. Once the standard cost curve and PCEUs have been calibrated, to estimate the overall cost of emission for a particular vehicle, we only need to multiply the corresponding PCEU of that vehicle type to the standard cost curve. We apply this PCEU approach to Hong Kong and obtain promising results. Compared with the results obtained by the full-blown emission model COPERT, the approach achieves high accuracy but obviates tedious inputs typically required for emission estimation.     

Experimental testing and simulations of speed variations impact on fuel consumption of conventional gasoline passenger cars

Speed variations are considered as an alternative for reducing fuel consumption during the use phase of passenger cars. It explores vehicle engine operating zones with lower fuel consumption, thus making possible a reduction in fuel consumption when compared to constant speed operation. In this paper, we present an evaluation of two conditions of speed variations: 50–70 km/h and 90–110 km/h using numerical simulations and controlled tests. The controlled tests performed on a test track by a professional pilot show that a reduction in fuel consumption is achievable with a conventional gasoline passenger car, with no adaptations for realizing speed variations. Numerical simulations based on a backward quasi-static powertrain model are used to evaluate the potential of speed variations for reducing fuel consumption in other speed variation conditions. When deceleration is performed with gear in neutral position, simulations show that speed variations are always correlated to a lower fuel consumption. This was suspected through previous numerical tests or evaluation on test bench but not in controlled tests conditions.     

Operational profiles of ships in Norwegian waters: An activity-based approach to assess the benefits of hybrid and electric propulsion

Various regulations are imposed on shipping to increase energy efficiency and reduce environmental impacts. Alternative fuels and power systems are among the solutions for compliance with these regulations. The power system of a ship may not operate optimally because of the diversity of the operational profile during its lifetime. This article uses an activity-based approach and big data from the Automatic Identification System (AIS) to study the operational profiles of eight ship types operating in Norwegian waters around mainland Norway in 2016. The aim is to identify ship types that can benefit from electric and hybrid propulsion through analysis of their operational profiles. Close to shore, the operational profiles of various ship types are similar, and all ships spend a great proportion of their time with lower loads. As the distance from shore increases, the operational profiles of various ship types follow distinct trends. Among the considered ship types, reefers spend more operational time close to the diesel engine design condition. On the other hand, offshore and passenger ships show the most dynamic operational profiles and spend a large percentage of their operational time with a partial load, away from diesel engine design conditions. Such ships can benefit from hybridisation, diesel-electric propulsion, and other electric concepts, such as batteries and fuel cells. Another option is to downsize diesel engines for better operation while fuel cells and batteries supply peak and partial loads. Operational profiles are plotted and details of the approach are presented in the article.     

储能系统在分布式发电中的应用

当今以风能、太阳能为代表的可再生能源,因其储量丰富、环境友好等特点,得到人们日益广泛的重视。基于可再生能源的分布式发电是可再生能源利用的一种主要方式,然而,由于可再生能源的间歇性,导致了分布式发电系统的稳定性、可靠性以及电能质量问题,在这种情况下,储能系统应运而生。本文介绍了蓄电池、超级电容、燃料电池以及飞轮等几种常见的储能技术,简要分析各自的工作原理,比较了它们之间的优缺点,并以蓄电池和超级电容为例,分析混合储能系统的构成方式,最后通过Buck/Boost双向变换器与直流母线相连接,给出了一系列适合于分布式发电系统的隔离型Buck/Boost双向变换器,并比较了它们之间的优缺点。     

20.5万吨散货船轴带发电机系统设计研究

为降低大型商业运输船舶无限航区航行时能源消耗,在20.5万吨级大型散货船上采用PWM型轴带发电机,以降低运输成本,提高环保性能,提高经济效益。     

波浪能发电装置水叶轮设计及试验

针对一种海洋波浪能轴流式叶轮波浪能发电装置,结合我国近海波浪特点,对该装置的叶轮进行结构设计、优化选型和实验验证。该海洋波浪能轴流式叶轮波浪能发电装置以水叶轮作为唯一的波浪能转化装置,能量转化效率是影响发电的重要因素。根据浮标的运动状态,结合我国近海水纹特征,得出不同设计参数下叶轮的轴向力、扭矩、相对出口压力、能量损失系数等关键数据。这些数据为制造样机提供力学及能量转化效率方面的指导作用。     

Multi-criteria analysis of optimal signal plans using microscopic traffic models

Increasing concerns on environment and natural resources, coupled with increasing demand for transport, put lots of pressure for improved efficiency and performance on transport systems worldwide. New technology nowadays enables fast innovation in transport, but it is the policy for deployment and operation with a systems perspective that often determines success. Smart traffic management has played important roles for continuous development of traffic systems especially in urban areas. There is, however, still lack of effort in current traffic management and planning practice prioritizing policy goals in environment and energy. This paper presents an application of a model-based framework to quantify environmental impacts and fuel efficiency of road traffic, and to evaluate optimal signal plans with respect not only to traffic mobility performance but also other important measures for sustainability. Microscopic traffic simulator is integrated with micro-scale emission model for estimation of emissions and fuel consumption at high resolution. A stochastic optimization engine is implemented to facilitate optimal signal planning for different policy goals, including delay, stop-and-goes, fuel economy etc. In order to enhance the validity of the modeling framework, both traffic and emission models are fine-tuned using data collected in a Chinese city. In addition, two microscopic traffic models are applied, and lead to consistent results for signal optimization. Two control schemes, fixed time and vehicle actuated, are optimized while multiple performance indexes are analyzed and compared for corresponding objectives. Solutions, representing compromise between different policies, are also obtained in the case study by optimizing an integrated performance index.     

Multi-scale robustness model for highway networks under flood events

Transportation system infrastructure often experiences severe flood-related disruptions such as overtopping, erosion, and scour. The ensuing damages can result in enormous direct and indirect economic losses to the traffic network and consequently the individuals through conditions like inaccessibility to commuters and reduction in traffic safety. Many studies have claimed that a robust transportation system could significantly prevent such consequences from natural hazards such as floods, highlighting the importance of robustness measures that could be used by decision-makers to properly manage flooded transportation system. Most available measures related to network robustness assessment are qualitative, and while some recent studies have focused on such evaluation using quantitative assessment approaches related to environmental or social-economic operations, they lack the holistic view towards robustness under flood events. This study develops a composite multi-scale transportation-system robustness model considering flood hazards by synthesizing geographical damage recognition, topological functionality analysis, network operation evaluation, and traffic-user loss estimation. This integrated model has been applied in a real-world highway network, mainly revealing that a given intensive flood occurrence at different locations may result in a variety of after-flood disruptions in the transportation network. To assist the asset owners with developing more reasonable prevention and recovery plans, the developed multi-scale robustness index presents both visible multi-denominational flood consequences and an overall post-event transportation-system robustness indicator.