A comparison of technologies for carbon-neutral passenger transport

In this study, the use of energy carriers based on renewable energy sources in battery-powered electric vehicles (BPEVs), fuel-cell electric vehicles (FCEVs), hybrid electric vehicles (HEVs) and internal combustion engine vehicles (ICEVs) is compared regarding energy efficiency, emission and cost. There is the potential to double the primary energy compared with the current level by utilising vehicles with electric drivetrains. There is also major potential to increase the efficiency of conventional ICEVs. The energy and environmental cost of using a passenger car can be reduced by 50% solely by using improved ICEVs instead of ICEVs with current technical standard. All the studied vehicles with alternative powertrains (HEVs, FCEVs, and BPEVs) would have lower energy and environmental costs than the ICEV. The HEVs, FCEVs and BPEVs have, however, higher costs than the future methanol-fuelled ICEV, if the vehicle cost is added to the energy and environmental costs, even if significant cost reductions for key technologies such as fuel cells, batteries and fuel storages are assumed. The high-energy efficiency and low emissions of these vehicles cannot compensate for the high vehicle cost. The study indicates, however, that energy-efficiency improvements, combined with the use of renewable energy, would reduce the cost of CO₂ reduction by 40% compared with a strategy based on fuel substitution only.     

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.     

齐齐哈尔市中心城区电动汽车及充电设施需求预测研究

在目前能源危机和环境保护的双重制约下,发展电动汽车已经成为解决能源环境问题的新途径。为适应未来电动汽车快速发展的需要及充电设施的合理规划布局,电动汽车及充电设施的需求预测就显得尤为重要。文中分析了影响齐齐哈尔市电动汽车发展规模的影响因素,结合国内其他省市的经验,考虑齐齐哈尔市实际情况,对齐齐哈尔市中心城区的电动汽车和充电设施发展规模进行了合理预测。     

基于ADVISOR的纯电动汽车动力系统匹配及仿真

纯电动汽车作为新能源汽车行业发展的主要方向,在发展其核心技术中,动力系统的匹配对于发展纯电动汽车具有重要的意义,合理的动力系统匹配影响着汽车的动力性和续航里程等因素。根据纯电动汽车的整车参数和性能指标,计算选择动力系统的基本参数,并利用ADVISOR仿真软件进行仿真分析,为改进技术提供依据,验证了设计的有效性。     

Impacts of driving patterns on tank-to-wheel energy use of plug-in hybrid electric vehicles

We evaluate the implications of a range of driving patterns on the tank-to-wheel energy use of plug-in hybrid electric vehicles. The driving patterns, which reflect short distance, low speed, and congested city driving to long distance, high speed, and uncongested highway driving, are estimated using an approach that involves linked traffic assignment and vehicle motion models. We find substantial variation in tank-to-wheel energy use of plug-in hybrid electric vehicles across driving patterns. Tank-to-wheel petroleum energy use on a per kilometer basis is lowest for the city and highest for the highway driving, with the opposite holding for a conventional internal combustion engine vehicle.     

Impacts of replacement of engine powered vehicles by electric vehicles on energy consumption and CO2 emissions

This paper evaluates the impacts on energy consumption and carbon dioxide (CO₂) emissions from the introduction of electric vehicles into a smart grid, as a case study. The AVL Cruise software was used to simulate two vehicles, one electric and the other engine-powered, both operating under the New European Driving Cycle (NEDC), in order to calculate carbon dioxide (CO₂) emissions, fuel consumption and energy efficiency. Available carbon dioxide data from electric power generation in Brazil were used for comparison with the simulated results. In addition, scenarios of gradual introduction of electric vehicles in a taxi fleet operating with a smart grid system in Sete Lagoas city, MG, Brazil, were made to evaluate their impacts. The results demonstrate that CO₂ emissions from the electric vehicle fleet can be from 10 to 26 times lower than that of the engine-powered vehicle fleet. In addition, the scenarios indicate that even with high factors of CO₂ emissions from energy generation, significant reductions of annual emissions are obtained with the introduction of electric vehicles in the fleet.     

Deploying public charging stations for electric vehicles on urban road networks

This paper explores how to optimally locate public charging stations for electric vehicles on a road network, considering drivers’ spontaneous adjustments and interactions of travel and recharging decisions. The proposed approach captures the interdependency of different trips conducted by the same driver by examining the complete tour of the driver. Given the limited driving range and recharging needs of battery electric vehicles, drivers of electric vehicles are assumed to simultaneously determine tour paths and recharging plans to minimize their travel and recharging time while guaranteeing not running out of charge before completing their tours. Moreover, different initial states of charge of batteries and risk-taking attitudes of drivers toward the uncertainty of energy consumption are considered. The resulting multi-class network equilibrium flow pattern is described by a mathematical program, which is solved by an iterative procedure. Based on the proposed equilibrium framework, the charging station location problem is then formulated as a bi-level mathematical program and solved by a genetic-algorithm-based procedure. Numerical examples are presented to demonstrate the models and provide insights on public charging infrastructure deployment and behaviors of electric vehicles.     

Forward power-train energy management modeling for assessing benefits of integrating predictive traffic data into plug-in-hybrid electric vehicles

In this paper, a forward power-train plug-in hybrid electric vehicle model with an energy management system and a cycle optimization algorithm is evaluated for energy efficiency. Using wirelessly communicated predictive traffic data for vehicles in a roadway network, as envisioned in intelligent transportation systems, traffic prediction cycles are optimized using a cycle optimization strategy. This resulted in a 56-86% fuel efficiency improvements for conventional vehicles. When combined with the plug-in hybrid electric vehicle power management system, about 115% energy efficiency improvements were achieved. Further improvements in the overall energy efficiency of the network were achieved with increased penetration rates of the intelligent transportation assisted enabled plug-in hybrid electric vehicles.     

Combining Intermodal Transport With Electric Vehicles: Towards More Sustainable Solutions

Abstract

This paper analyses the feasibility of incorporating electric or hybrid vehicles in intermodal transport for the transportation of containers in the pre- and post haulage (PPH) operation. In Europe, the intermodal transport market is being strongly supported, as it is seen as one of the keystones of a sustainable mobility system policy. The introduction of environmentally friendly electric/hybrid vehicles for the pre- and post haulage operation would mean a further enhancement leading to a more complete ecological intermodal transport chain. PPH operations are usually no longer than 30 km, and, hence, could possibly be handled by electric or hybrid vehicles.

Hybrid electric vehicles (HEV) combine electric and other drive systems, such as internal combustion engines, gas turbines and fuel cells. Hybrid electric vehicles merge the zero pollution and high efficiency benefits of electric traction with the high fuel energy density benefits of an energy source or thermal engine. The use of electrically driven vehicles for goods distribution has already been successfully proven in international demonstration projects, such as ELCIDIS. Transport of intermodal units (such as ISO containers), however, requires electric/hybrid heavy-duty goods vehicles, which are not readily available on the market, but for which the technology exists.

Different possibilities are assessed as to their technical, financial, organizational and environmental feasibility and suitability. This analysis is based on a typical mission for pre-and post haulage operations, such as type of trips, distance, frequency, urban/suburban, etc.     

To save money or to save time: Intelligent routing design for plug-in hybrid electric vehicle

Electric vehicles (EVs) are promising alternative to conventional vehicles, due to their low fuel cost and low emissions. As a subset of EVs, plug-in hybrid electric vehicles (PHEVs) backup batteries with combustion engines, and thus have a longer traveling range than battery electric vehicles (BEVs). However, the energy cost of a PHEV is higher than a BEV because the gasoline price is higher than the electricity price. Hence, choosing a route with more charging opportunities may result in less fuel cost than the shortest route. Different with the traditional shortest-path and shortest-time routing methods, we propose a new routing choice with the lowest fuel cost for PHEV drivers. Existing algorithms for gasoline vehicles cannot be applied because they never considered the regenerative braking which may result in negative energy consumption on some road segments. Existing algorithms for BEVs are not competent too because PHEVs have two power sources. Thus, even if along the same route, different options of power source will lead to different energy consumption. This paper proposes a cost-optimal algorithm (COA) to deal with the challenges. The proposed algorithm is evaluated using real-world maps and data. The results show that there is a trade-off between traveling cost and time consumed when driving PHEVs. It is also observed that the average detour rate caused by COA is less than 14%. Significantly, the algorithm averagely saves more than 48% energy cost compared to the shortest-time routing.     

Individual characteristics and stated preferences for alternative energy sources and propulsion technologies in vehicles: A discrete choice analysis for Germany

With respect to the German goal of a transition to a lead market for electromobility within a short time period, this paper empirically examines the preferences for alternative energy sources or propulsion technologies in vehicles and particularly for electric vehicles. The data stem from a stated preference discrete choice experiment with 598 potential German car buyers. In order to simulate a realistic future purchase situation, seven vehicle types were incorporated in each of the six choice sets, i.e. hybrid, gas, biofuel, hydrogen, and electric vehicles besides common gasoline and diesel vehicles. The econometric analysis with flexible multinomial probit models reveals that potential car buyers in Germany currently have a low stated preference for electric, hydrogen, and hybrid vehicles. While our paper also discusses the impact of common vehicle attributes such as purchase price or service station availability, it particularly considers the effect of socio-demographic and environmental awareness variables. The estimation results reveal that younger potential car buyers have a higher stated preference for hydrogen and electric vehicles, males have a higher stated choice of hydrogen vehicles, and environmentally aware potential car buyers have a higher stated preference for hydrogen and electric vehicles. These results suggest that common policy instruments such as the promotion of research and development, taxation, or subsidization in the field of electromobility could be supplemented by strategies to increase the social acceptance of alternative vehicle types that are directly oriented to these population groups. Methodologically, our study highlights the importance of the inclusion of taste persistence across the choice sets and a high number of random draws in the Geweke–Hajivassiliou–Keane simulator in the simulated maximum likelihood estimation of the multinomial probit models.     

Linking Chinese cultural values and the adoption of electric vehicles: The mediating role of ethical evaluation

Electric vehicles (EVs) have been regarded as one of the most prominent green technologies, touted to help reduce global energy consumption and carbon emissions. China advocates the development of EVs to address the increasing challenges of climate change, urban air pollution and energy security, but consumers’ enthusiasm for adopting EVs remains low. In this paper, we present a concept model that hypothesizes Chinese cultural values as a key to understanding Chinese consumers’ intention to adopt EVs. Based on a nationwide online survey in China, this study explores Chinese consumers’ attitudes toward two types of EVs—battery electric vehicles and plug-in hybrid electric vehicles—by identifying the influence of the human–nature relationship, long-term orientation, face consciousness, and risk attitude, as well as the mediating effect of deontological ethical evaluation in decision-making. The results suggest that public policy and social marketing efforts should pay more attention to the role of cultural values when promoting environmentally sustainable technologies, and importantly, that the promotion efforts should differ for different cultural elements and products with different levels of innovativeness.     

Life cycle model of alternative fuel vehicles: emissions,energy, and cost trade-offs

This paper describes a life cycle model for performing level-playing field comparisons of the emissions, costs, and energy efficiency trade-offs of alternative fuel vehicles (AFV) through the fuel production chain and over a vehicle lifetime. The model is an improvement over previous models because it includes the full life cycle of the fuels and vehicles, free of the distorting effects of taxes or differential incentives. This spreadsheet model permits rapid analyses of scenarios in plots of trade-off curves or efficiency frontiers, for a wide range of alternatives with current and future prices and levels of technology. The model is available on request.The analyses indicate that reformulated gasoline (RFG) currently has the best overall performance for its low cost, and should be the priority alternative fuel for polluted regions. Liquid fuels based on natural gas, M100 or M85, may be the next option by providing good overall performance at low cost and easy compatibility with mainstream fuel distribution systems. Longer term, electric drive vehicles using liquid hydrocarbons in fuel cells may offer large emissions and energy savings at a competitive cost. Natural gas and battery electric vehicles may prove economically feasible at reducing emissions and petroleum consumption in niches determined by the unique characteristics of those systems.     

Modeling the effect of electric vehicle adoption on pedestrian traffic safety: An agent-based approach

When operated at low speeds, electric and hybrid vehicles have created pedestrian safety concerns in congested areas of various city centers, because these vehicles have relatively silent engines compared to those of internal combustion engine vehicles, resulting in safety issues for pedestrians and cyclists due to the lack of engine noise to warn them of an oncoming electric or hybrid vehicle. However, the driver behavior characteristics have also been considered in many studies, and the high end-prices of electric vehicles indicate that electric vehicle drivers tend to have a higher prosperity index and are more likely to receive a better education, making them more alert while driving and more likely to obey traffic rules. In this paper, the positive and negative factors associated with electric vehicle adoption and the subsequent effects on pedestrian traffic safety are investigated using an agent-based modeling approach, in which a traffic micro-simulation of a real intersection is simulated in 3D using AnyLogic software. First, the interacting agents and dynamic parameters are defined in the agent-based model. Next, a 3D intersection environment is created to integrate the agent-based model into a visual simulation, where the simulation records the number of near-crashes occurring in certain pedestrian crossings throughout the virtual time duration of a year. A sensitivity analysis is also carried out with 9000 subsequent simulations performed in a supercomputer to account for the variation in dynamic parameters (ambient sound level, vehicle sound level, and ambient illumination). According to the analysis, electric vehicles have a 30% higher pedestrian traffic safety risk than internal combustion engine vehicles under high ambient sound levels. At low ambient sound levels, however, electric vehicles have only a 10% higher safety risk for pedestrians. Low levels of ambient illumination also increase the number of pedestrians involved in near-crashes for both electric vehicles and combustion engine vehicles.     

Dynamic charging-while-driving systems for freight delivery services with electric vehicles: Traffic and energy modelling

This paper presents a research on traffic modelling developed for assessing traffic and energy performance of electric systems installed along roads for dynamic charging-while-driving (CWD) of fully electric vehicles (FEVs).The logic adopted by the developed traffic model is derived from a particular simulation scenario of electric charging: a freight distribution service operated using medium-sized vans. In this case, the CWD service is used to recover the state of charge of the FEV batteries to shortly start with further activities after arrival at the depot.The CWD system is assumed to be implemented in a multilane ring road with several intermediate on-ramp entrances, where the slowest lane is reserved for the dynamic charging of authorized electric vehicles. A specific traffic model is developed and implemented based on a mesoscopic approach, where energy requirements and charging opportunities affect driving and traffic behaviours. Overtaking manoeuvres as well as new entries in the CWD lane of vehicles that need to charge are modelled according to a cooperative driving system, which manages adequate time gaps between consecutive vehicles. Finally, a speed control strategy is simulated at a defined node to create an empty time-space slot in the CWD lane, by delaying the arriving vehicles. This simulated control, implemented to allow maintenance operations for CWD that may require clearing a charging zone for a short time slot, could also be applied to facilitate on-ramp merging manoeuvres.     

公共充电站在基础设施建设中的规划与研究

随着我国社会经济发展水平的不断提高,汽车使用量持续攀高。大力发展新能源汽车,能够促进资源充分利用,减少汽车尾气排放,对保障能源安全、促进节能减排、防治大气污染、推动我国能源可持续发展具有重要意义。随着电动汽车的推广使用,电动汽车对充电站的基础设施建设以及服务网络的完善等需求日益紧迫。充电基础设施的建设,用以满足电动汽车的发展需求,并以充电设施、充电系统的适度超前发展引导电动汽车的业务发展。     

Energy conservation in urban public transport

Urban public transport energy use is determined largely by the weight of the vehicle, and frequency of intermediate stops, imposing repeated acceleration/steady running/braking cycles, in which much of the kinetic energy is dissipated. Energy consumed for the same capacity and vehicle performance may be reduced by coasting, cutting vehicle weight, and use of regenerative braking, on electrically‐powered systems, to convert the otherwise wasted braking energy into useful form. Particular attention is paid to the last‐named, identifying results of past experience and recent simulations. Practical constraints limiting the amount of energy actually recovered are discussed, including proportion of vehicle weight braked electrically, receptivity of the supply system, stop spacing and number of vehicles operated simultaneously. Reference is also made to battery vehicles and flywheel energy storage.

It is suggested that considerable scope exists in urban electric rail operation for reduced energy consumption, as existing fleets are replaced by lighter weight vehicles, fitted for regenerative braking. Further savings may come from use of inverter equipment. Rate of fleet renewal may be an important factor. Buses are already much more energy efficient, and dramatic gains are unlikely. However, there is some scope for use of flywheel energy storage, and regenerative braking on trolleybuses.     

Eco-driving advisory strategies for a platoon of mixed gasoline and electric vehicles in a connected vehicle system

As electric vehicles (EVs) have gained an increasing market penetration rate, the traffic on urban roads will tend to be a mix of traditional gasoline vehicles (GVs) and EVs. These two types of vehicles have different energy consumption characteristics, especially the high energy efficiency and energy recuperation system of EVs. When GVs and EVs form a platoon that is recognized as an energy-friendly traffic pattern, it is critical to holistically consider the energy consumption characteristics of all vehicles to maximize the energy efficiency benefit of platooning. To tackle this issue, this paper develops an optimal control model as a foundation to provide eco-driving suggestions to the mixed-traffic platoon. The proposed model leverages the promising connected vehicle technology assuming that the speed advisory system can obtain the information on the characteristics of all platoon vehicles. To enhance the model applicability, the study proposes two eco-driving advisory strategies based on the developed optimal control model. One strategy provides the lead vehicle an acceleration profile, while the other provides a set of targeted cruising speeds. The acceleration-based eco-driving advisory strategy is suitable for platoons with an automated leader, and the speed-based advisory strategy is more friendly for platoons with a human-operated leader. Results of numerical experiments demonstrate the significance when the eco-driving advisory system holistically considers energy consumption characteristics of platoon vehicles.     

What is the market potential of plug-in electric vehicles as commercial passenger cars? A case study from Germany

Commercial passenger cars are a possible early market segment for plug-in electric vehicles (PEVs). Compared to privately owned vehicles, the commercial vehicle segment is characterized by higher mileage and a higher share of vehicle sales in Germany. To this point, there are only few studies which analyze the commercial passenger car sector and arrive at contradictory results due to insufficient driving profile data with an observation period of only one day. Here, we calculate the market potential of PEVs for the German commercial passenger car sector by determining the technical and economical potential for PEVs in 2020 from multi-day driving profiles. We find that commercial vehicles are better suited for PEVs than private ones since they show higher average annual mileage and drive more regularly. About 87% of the analyzed three-week vehicle profiles can technically be fulfilled by battery electric vehicles (BEVs) with an electric driving range of about 110 km while plug-in hybrid electric vehicles (PHEVs) with an electric range of 40 km could obtain an electric driving share of 60% on average. In moderate energy price scenarios, PEVs can reach a market share of 2–4% in the German commercial passenger car sales by 2020 and especially the large commercial branches (Trade, Manufacturing, Administrative services and Other services) are important. However, our analysis shows a high sensitivity of results to energy and battery prices as well as electric consumptions.     

纯电动汽车制动能量回收及储能策略研究

为解决纯电动汽车存在的制动能量耗损及续航里程不足等问题,通过对行车能量流分析的基础上,提出一种制动能量回收及储能策略,并利用ADVISOR软件建立整车制动能量回收策略仿真模型。选取UDDS城市道路工况进行仿真,结果表明所建立的控制策略可以对制动能量进行回收和储存,对于提高纯电动汽车续航里程提供了理论基础。