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。     

Cutting vehicle emissions with regenerative braking

This paper presents an analysis of vehicle regenerative braking systems as a quick and relatively easy means of achieving higher overall fuel efficiency and lowering carbon emissions. The system involves the installation of an additional electric motor/generator in parallel to the vehicle’s internal combustion engine and is used in conjunction with a DCDC converter and ultracapacitor. The system is used to recapture the energy lost in vehicle braking, significantly reducing a vehicle’s overall energy consumption and lowering vehicle emissions. Experimentally-based evidence is collected and compared for two sample vehicles to deduce the potential fuel and emissions saving.     

Optimum routing of battery electric vehicles: Insights using empirical data and microsimulation

This study investigates the energy consumption impact of route selection on battery electric vehicles (BEVs) using empirical second-by-second Global Positioning System (GPS) commute data and traffic micro-simulation data. Drivers typically choose routes that reduce travel time and therefore travel cost. However, BEVs’ limited driving range makes energy efficient route selection of particular concern to BEV drivers. In addition, BEVs’ regenerative braking systems allow for the recovery of energy while braking, which is affected by route choices. State-of-the-art BEV energy consumption models consider a simplified constant regenerative braking energy efficiency or average speed dependent regenerative braking factors. To overcome these limitations, this study adopted a microscopic BEV energy consumption model, which captures the effect of transient behavior on BEV energy consumption and recovery while braking in a congested network. The study found that BEVs and conventional internal combustion engine vehicles (ICEVs) had different fuel/energy-optimized traffic assignments, suggesting that different routings be recommended for electric vehicles. For the specific case study, simulation results indicate that a faster route could actually increase BEV energy consumption, and that significant energy savings were observed when BEVs utilized a longer travel time route because energy is regenerated. Finally, the study found that regenerated energy was greatly affected by facility types and congestion levels and also BEVs’ energy efficiency could be significantly influenced by regenerated energy.     

Comparative analysis of the energy consumption and CO2 emissions of 40 electric,plug-in hybrid electric,hybrid electric and internal combustion engine vehicles

This paper analyses the results of the Royal Automobile Clubhallo’s 2011 RAC Future Car Challenge, an annual motoring challenge in which participants seek to consume the least energy possible while driving a 92 km route from Brighton to London in the UK. The results reveal that the vehicle’s power train type has the largest impact on energy consumption and emissions. The traction ratio, defined as the fraction of time spent on the accelerator in relation to the driving time, and the amount of regenerative braking have a significant effect on the individual energy consumption of vehicles. In contrast, the average speed does not have a great effect on a vehicles’ energy consumption in the range 25–70 km/h.     

Alternative fuels for transportation

The alternatives to the oil based fuels for transportation are considered and analysed. These are the synthetic fuels, made from coal, the liquid petroleum gases of propane and butane, compressed natural gas and methanol. The problems associated with the use of electric vehicles are discussed; the main problem being that of range.

The possible use of hydrogen as a fuel is analysed in some detail. Since its supply can be tied directly to nuclear energy sources, rather than hydrocarbon feed stocks, it could be an alternative in the long term. The main problems of the storage of hydrogen on the vehicle and of its propensity to “back‐fire” into the engine intake are discussed. The first can be ameliorated and the second eliminated by dual fuelling; with petrol. It is advocated that the on‐board storage of hydrogen be by the use of hydrides for private cars. However, it is expected that it may be as liquid hydrogen for some forms of transport and will certainly be in this form for aircraft.     

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.     

Customizing driving cycles to support vehicle purchase and use decisions: Fuel economy estimation for alternative fuel vehicle users

Wider deployment of alternative fuel vehicles (AFVs) can help with increasing energy security and transitioning to clean vehicles. Ideally, adopters of AFVs are able to maintain the same level of mobility as users of conventional vehicles while reducing energy use and emissions. Greater knowledge of AFV benefits can support consumers’ vehicle purchase and use choices. The Environmental Protection Agency’s fuel economy ratings are a key source of potential benefits of using AFVs. However, the ratings are based on pre-designed and fixed driving cycles applied in laboratory conditions, neglecting the attributes of drivers and vehicle types. While the EPA ratings using pre-designed and fixed driving cycles may be unbiased they are not necessarily precise, owning to large variations in real-life driving. Thus, to better predict fuel economy for individual consumers targeting specific types of vehicles, it is important to find driving cycles that can better represent consumers’ real-world driving practices instead of using pre-designed standard driving cycles. This paper presents a methodology for customizing driving cycles to provide convincing fuel economy predictions that are based on drivers’ characteristics and contemporary real-world driving, along with validation efforts. The methodology takes into account current micro-driving practices in terms of maintaining speed, acceleration, braking, idling, etc., on trips. Specifically, using a large-scale driving data collected by in-vehicle Global Positioning System as part of a travel survey, a micro-trips (building block) library for California drivers is created using 54 million seconds of vehicle trajectories on more than 60,000 trips, made by 3000 drivers. To generate customized driving cycles, a new tool, known as Case Based System for Driving Cycle Design, is developed. These customized cycles can predict fuel economy more precisely for conventional vehicles vis-à-vis AFVs. This is based on a consumer’s similarity in terms of their own and geographical characteristics, with a sample of micro-trips from the case library. The AFV driving cycles, created from real-world driving data, show significant differences from conventional driving cycles currently in use. This further highlights the need to enhance current fuel economy estimations by using customized driving cycles, helping consumers make more informed vehicle purchase and use decisions.     

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.     

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.     

Trends in life cycle greenhouse gas emissions of future light duty electric vehicles

The majority of previous studies examining life cycle greenhouse gas (LCGHG) emissions of battery electric vehicles (BEVs) have focused on efficiency-oriented vehicle designs with limited battery capacities. However, two dominant trends in the US BEV market make these studies increasingly obsolete: sales show significant increases in battery capacity and attendant range and are increasingly dominated by large luxury or high-performance vehicles. In addition, an era of new use and ownership models may mean significant changes to vehicle utilization, and the carbon intensity of electricity is expected to decrease. Thus, the question is whether these trends significantly alter our expectations of future BEV LCGHG emissions.To answer this question, three archetypal vehicle designs for the year 2025 along with scenarios for increased range and different use models are simulated in an LCGHG model: an efficiency-oriented compact vehicle; a high performance luxury sedan; and a luxury sport utility vehicle. While production emissions are less than 10% of LCGHG emissions for today’s gasoline vehicles, they account for about 40% for a BEV, and as much as two-thirds of a future BEV operated on a primarily renewable grid. Larger battery systems and low utilization do not outweigh expected reductions in emissions from electricity used for vehicle charging. These trends could be exacerbated by increasing BEV market shares for larger vehicles. However, larger battery systems could reduce per-mile emissions of BEVs in high mileage applications, like on-demand ride sharing or shared vehicle fleets, meaning that trends in use patterns may countervail those in BEV design.     

Air quality impacts of electric vehicle adoption in Texas

Widespread adoption of plug-in electric vehicles (PEVs) may substantially reduce emissions of greenhouse gases while improving regional air quality and increasing energy security. However, outcomes depend heavily on the electricity generation process, power plant locations, and vehicle use decisions. This paper provides a clear methodology for predicting PEV emissions impacts by anticipating battery-charging decisions and power plant energy sources across Texas. Life-cycle impacts of vehicle production and use and Texans’ exposure to emissions are also computed and monetized. This study reveals to what extent PEVs are more environmentally friendly, for most pollutant species, than conventional passenger cars in Texas, after recognizing the emissions and energy impacts of battery provision and other manufacturing processes. Results indicate that PEVs on today’s grid can reduce GHGs, NO_x, PM₁₀, and CO in urban areas, but generate significantly higher emissions of SO₂ than existing light-duty vehicles. Use of coal for electricity production is a primary concern for PEV growth, but the energy security benefits of electrified vehicle-miles endure. As conventional vehicle emissions rates improve, it appears that power grids must follow suit (by improving emissions technologies and/or shifting toward cleaner generation sources) to compete on an emissions-monetized basis with conventional vehicles in many locations. Moreover, while PEV pollution impacts may shift to more remote (power plant) locations, dense urban populations remain most strongly affected by local power plant emissions in many Texas locations.     

货车自动驾驶技术及标准法规发展分析

目前,自动驾驶技术在乘用车领域已获得突破性发展;为提高通行效率和出行安全起到了极大的作用。自动驾驶技术在商用车领域的应用,有望较好解决高昂的人力成本和难以提高的效率等问题。然而,目前自动驾驶技术在货车的应用大多采用跟乘用车同样的标准进行规范,这在实际应用中存在着诸多的问题;例如,在FCW和AEB功能中货车在相同车速的制动距离要远大于乘用车,而其所采用标准规定的碰撞预警时间却并无多大不同,这在实际场景中存在着较大的安全隐患[1,2]。此外,货车质量和体积较大,且较多应用于长途运输,运输过程中会经历包括高温、严寒、山区等多种复杂气候场景,这些都将对货车自动驾驶技术在车辆制动效能、能耗以及多场景应用等方面提出更有针对性规范的要求。本文针对货车的应用场景特点,为其自动驾驶技术应用标准化提出了建议。     

Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles

Driving volatility captures the extent of speed variations when a vehicle is being driven. Extreme longitudinal variations signify hard acceleration or braking. Warnings and alerts given to drivers can reduce such volatility potentially improving safety, energy use, and emissions. This study develops a fundamental understanding of instantaneous driving decisions, needed for hazard anticipation and notification systems, and distinguishes normal from anomalous driving. In this study, driving task is divided into distinct yet unobserved regimes. The research issue is to characterize and quantify these regimes in typical driving cycles and the associated volatility of each regime, explore when the regimes change and the key correlates associated with each regime. Using Basic Safety Message (BSM) data from the Safety Pilot Model Deployment in Ann Arbor, Michigan, two- and three-regime Dynamic Markov switching models are estimated for several trips undertaken on various roadway types. While thousands of instrumented vehicles with vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication systems are being tested, nearly 1.4 million records of BSMs, from 184 trips undertaken by 71 instrumented vehicles are analyzed in this study. Then even more detailed analysis of 43 randomly chosen trips (N = 714,340 BSM records) that were undertaken on various roadway types is conducted. The results indicate that acceleration and deceleration are two distinct regimes, and as compared to acceleration, drivers decelerate at higher rates, and braking is significantly more volatile than acceleration. Different correlations of the two regimes with instantaneous driving contexts are explored. With a more generic three-regime model specification, the results reveal high-rate acceleration, high-rate deceleration, and cruise/constant as the three distinct regimes that characterize a typical driving cycle. Moreover, given in a high-rate regime, drivers’ on-average tend to decelerate at a higher rate than their rate of acceleration. Importantly, compared to cruise/constant regime, drivers’ instantaneous driving decisions are more volatile both in “high-rate” acceleration as well as “high-rate” deceleration regime. The study contributes to analyzing volatility in short-term driving decisions, and how changes in driving regimes can be mapped to a combination of local traffic states surrounding the vehicle.     

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%.     

The treatment of capital costs of vehicles in evaluating road schemes

There are two ways in which new road schemes may influence capital expenditure on vehicles. Firstly, by improving utilisation of existing vehicles, the size of fleet needed to perform a given volume of work may be reduced. This will clearly reduce the amount of capital tied up in motor vehicles at any point in time, and to the extent that vehicle life is determined by age rather than mileage run, will also yield savings in terms of investment in new vehicles. Secondly, by generating additional road traffic, road schemes may lead to an increase in the stock of vehicles in use.This paper argues that the current treatment of vehicle depreciation and interest charges in U.K. cost data fails to allow correctly for either of these items. Errors of logic occur in the way in which the capital stock of vehicles is valued, and in the fact that certain overheads are ignored even when fleet size changes. Moreover, the empirical evidence supporting the current partitioning of depreciation into overhead and running cost components, and the assumption of constant hours in service after an increase in journey speed seems of doubtful validity.An alternative method of calculating vehicle capital costs, based on the concept of annual capital charge, and making explicit the assumptions with respect to vehicle utilisation, is advocated, and the sensitivity of results to the view taken of the latter is demonstrated by means of specimen calculations.     

山区高速公路危险路段交通安全设施系统研究

本篇以高速公路长下坡危险路段为研究对象,以解决云南蒙新高速公路38km连续长下坡路段行车安全问题为目标,提出了车辆制动失灵概率的预测方法,研发出了长下坡路段制动失灵车辆专用减速带、消能减速护栏、网索式避险车道等三种新型安全设施,并总结分析了长下坡路段安全设施的设计方法及施工工艺技术,编制了《连续长下坡路段安全保障系统设计与施工指南》,可有效提高长下坡危险路段的行车安全。     

Routing aspects of electric vehicle drivers and their effects on network performance

This study investigates the routing aspects of battery electric vehicle (BEV) drivers and their effects on the overall traffic network performance. BEVs have unique characteristics such as range limitation, long battery recharging time, and recuperation of energy lost during the deceleration phase if equipped with regenerative braking system (RBS). In addition, the energy consumption rate per unit distance traveled is lower at moderate speed than at higher speed. This raises two interesting questions: (i) whether these characteristics of BEVs will lead to different route selection compared to conventional internal combustion engine vehicles (ICEVs), and (ii) whether such route selection implications of BEVs will affect the network performance. With the increasing market penetration of BEVs, these questions are becoming more important. This study formulates a multi-class dynamic user equilibrium (MCDUE) model to determine the equilibrium flows for mixed traffic consisting of BEVs and ICEVs. A simulation-based solution procedure is proposed for the MCDUE model. In the MCDUE model, BEVs select routes to minimize the generalized cost which includes route travel time, energy related costs and range anxiety cost, and ICEVs to minimize route travel time. Results from numerical experiments illustrate that BEV drivers select routes with lower speed to conserve and recuperate battery energy while ICEV drivers select shortest travel time routes. They also illustrate that the differences in route choice behavior of BEV and ICEV drivers can synergistically lead to reduction in total travel time and the network performance towards system optimum under certain conditions.     

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.     

Influence of vehicle type and road category on natural resource consumption in road transport

This study calculates the natural resource use of road transport for different road categories and for different vehicle types. Material inputs per service are determined as the life cycle wide consumption of materials by the road and vehicles, and set against person-kilometres and ton-kilometres transported. If the material input of the infrastructure is allocated to the users according to traffic volume, the material input per service values for abiotic resources and for water are much higher for cars than for bus traffic. The material inputs per service unit for air is significantly lower for buses than for cars. For bicycles, abiotic natural resource consumption is between that for cars and buses, while water consumption is in most instances the highest and air consumption the lowest for the modes studied. The material input per service values for the full trailer are significantly lower than for other goods vehicles. The material inputs per service value for air is significantly higher in the case of vans. If the allocation of road infrastructure use is done by gross vehicle weight, the material input per service values for abiotic resources and water of buses and heavy lorries rise.     

Assessment of energy-saving techniques in direct-current-electrified mass transit systems

Railway rapid transit systems are key stones for the sustainability of mass transit in developed countries. The overwhelming majority of these railway systems are direct-current (DC) electrified and several energy-saving techniques have been proposed in the literature for these systems. The use of regenerative-braking in trains is generally recognised as the main tool to improve the efficiency of DC-electrified mass transit railway systems but the energy recovered in braking cannot always be handled efficiently, above all in low traffic-density situations. Several emerging technologies as energy storage systems or reversible traction substations have the potential for making it possible to efficiently use train-braking. However, a systematic evaluation of their effect is missing in the literature.In this paper, a deep, rigorous and comprehensive study on the factors which affect energy issues in a DC-electrified mass transit railway system is carried out. This study clarifies what the actual potential is for energy saving in each situation. Then, a methodology to asses several energy-saving techniques to improve energy efficiency in DC-electrified mass transit systems is presented, constituting the main contribution of this paper. This methodology has been conceived to help operators in assessing the effect of railway-infrastructure emerging technologies in transit systems, so making it possible to shape planning, capacity, etc. It is stepped out in three basic movements. First of all, a traffic-density scan analysis is conducted in order to clarify the effect of the headway on system behaviour. Secondly, several traffic-density scenarios are simulated for a set of infrastructure-expanded cases. Finally, annual energy saving is evaluated by applying a realistic operation timetable. This methodology has been applied to a case study in Madrid Metro (Spain) to illustrate the steps of its application and the effect of several energy-saving techniques on this specific system. Results confirm that regenerative braking generally leads to an important increase of system energy efficiency – especially at high traffic-density scenarios. It has also been proved that infrastructure improvements can also contribute to energy savings and their contributions are more significant at low traffic densities. Annual energy results have been obtained, which may lead to investment decisions by carrying out an appropriate economic assessment based on cost analysis.The main results of the study presented here are likely to apply to other electric traction systems, at least qualitatively.