共查询到20条相似文献，搜索用时 15 毫秒
1.
This research identifies key variables that influence fuel consumption that might be improved through eco-driving training programs under three circumstances that have been scarcely studied before: (a) heavy- and medium-duty truck fleets, (b) long-distance freight transport, and (c) the Latin American region. Based on statistical analyses that include multivariate regression of operational variables on fuel consumption, the impacts of an eco-driving training campaign were measured by comparing ex ante and ex post data. Operational variables are grouped into driving errors, trip conditions, driver behavior, driver profile, and vehicle attributes.The methodology is applied in a freight fleet with nationwide transport operations located in Colombia, where the steepness of its roads plays an important role in fuel consumption. The fleet, composed of 18 trucks, is equipped with state-of-the-art real-time data logger systems. During four months, 517 trips traveling a total distance of 292,512 km and carrying a total of 10,034 tons were analyzed.The results show a baseline average fuel consumption (FC) of 1.716 liters per ton-100 km. A different logistics performance indicator, which measures FC in liters per ton transported each 100 km, shows an average of 3.115. After the eco-driving campaign, reductions of 6.8% and 5.5% were obtained. Drivers’ experience, driving errors, average speed, and weight-capacity ratio, among others, were found to be highly relevant to FC. In particular, driving errors such as acceleration, braking and speed excesses are the most sensitive to eco-driving training, showing reductions of up to 96% on the average number of events per trip. 相似文献
2.
Fuel consumption models have been widely used to predict fuel consumption and evaluate new vehicle technologies. However, due to the uncertainty and high nonlinearity of fuel systems, it is difficult to develop an accurate fuel consumption model for real-time calculations. Additionally, whether the developed fuel consumption models are suitable for eco-routing and eco-driving systems is unknown. To address these issues, a systematic review of fuel consumption models and the factors that influence fuel economy is presented. First, the primary factors that affect fuel economy, including travel-related, weather-related, vehicle-related, roadway-related, traffic-related, and driver-related factors, are discussed. Then, state-of-the-art fuel consumption models developed after 2000 are summarized and classified into three broad types based on transparency, i.e., white-box, grey-box and black-box models. Consequently, the limitations and potential possibilities of fuel consumption modelling are highlighted in this review. 相似文献
3.
This paper questions the relevance of microscopic traffic models for estimating the impact of traffic strategies on fuel consumption. Urban driving cycles from the ARTEMIS database are simplified into piecewise linear speed profiles to mimic the classical outputs of microscopic traffic flow models. Fuel consumption is estimated for real and simplified trajectories and links between kinematics and the fuel consumption errors are investigated. Simplifying trajectories causes fuel consumption underestimation, from −1.2 to −5.2% on average according to the level of simplification; errors can approach −20% for some cycles. A focus on kinematic phases indicates that the maximum speed reached and the time decelerating are the main influences on fuel consumption. Finally, in the case where maximum speeds are estimated correctly, it is shown that errors committed at each kinematic phase when acceleration distributions are approximated by their mean values, converge towards small errors over complete cycles. A method is developed to quantify and reduce these errors. 相似文献
4.
The variance in fuel consumption caused by driving style (DS) difference exceeds 10% and reaches a maximum of 20% under different road conditions, even for experienced bus drivers. To study the influence of DS on fuel consumption, a method for summarizing DS characteristic parameters on the basis of vehicle-engine combined model is proposed. With this method, the author proposes 26 DS characteristic parameters related to fuel consumption in the accelerating, normal running, and decelerating processes of vehicles. The influence of DS characteristic parameters on fuel consumption under different road conditions and vehicle masses is quantitatively analyzed on the basis of real driving data over 100,000 km. Analysis results show that the influence of DS characteristic parameters on fuel consumption changes with road condition and vehicle mass, with road condition serving a more important function. However, the DS characteristics in the accelerating process of vehicles are decisive for fuel consumption under different conditions. This study also calculates the minimum sample size necessary for analyzing the effect of DS characteristics on fuel consumption. The statistical analysis based on the real driving data over 2500 km can determine the influence of DS on fuel consumption under a given power-train configuration and road condition. The analysis results can be employed to evaluate the fuel consumption of drivers, as well as to guide the design of Driver Advisory System for Eco-driving directly. 相似文献
5.
This research developed an eco-driving feedback system based on a driving simulator to support eco-driving training. This support system could provide both dynamic and static feedback to improve drivers’ eco-driving behavior. In the process of driving, drivers could get voice prompts (e.g., please avoid accelerating rapidly) once non-eco-driving behavior appeared, and also could see the real-time CO2 emissions curves. After driving, drivers could receive an eco-driving evaluation report including their fuel consumption rank, potential of fuel saving and driving advice corresponding to their driving behavior. In this support system, five items of non-eco-driving behavior (i.e., quick accelerate, rapid decelerate, engine revolutions at a high level, too fast or unstable speed on freeways and idling for a longer time) were defined and could be detected. To validate this support system’s effectiveness in reducing fuel consumption and emissions, 22 participants were recruited and three driving tests were conducted, first without using the support system, then static feedback and then dynamic feedback utilized respectively. A reduction of 5.37% for CO2 emissions and 5.45% for fuel consumption was obtained. The results indicated that the developed eco-driving support system was an effective training tool to improve drivers’ eco-driving behavior in reducing emissions and fuel consumption. 相似文献
6.
Vehicles travelling in actual urban areas are mostly in idle, low or medium speeds, which reflects engine part-load condition. These regularly visited engine conditions, in reality affect the fuel economy during actual driving. Thus, understanding the characteristics of the actual driving conditions will enable many other benefits besides legislation. This paper presents the development of a preliminary Malaysian urban drive cycle with the inclusion of the engine parameters and characteristics, acquired through an actual urban driving on numerous urban roads in Malaysia that represents the actual consumer’s daily driving experience. The actual engine parameters and its characteristics are integrated into the assessment measures in an attempt to formulate representable drive cycle and fuel consumption data. The initial drive cycle is composed of 17 sequences selected from the actual on-the-road conditions to represent the Malaysian urban driving. The average fuel economy of the established Malaysian urban drive cycle was then measured on a test bench using the same engine from the vehicle. The recorded fuel economy with Malaysian urban drive cycle is 8.5% below the actual Malaysian urban driving which is closer estimation to the actual driving compared to the current in-practice NEDC which shows to be 43.1% below the actual Malaysian urban driving. Thus, Malaysian urban drive cycle is better in representing the Malaysian urban driving conditions compared to the NEDC in terms of the average fuel economy measurements. 相似文献
7.
The United States transportation sector consumes 5 billion barrels of petroleum annually to move people and freight around the country by car, truck, train, ship and aircraft, emitting significant greenhouse gases in the process. Making the transportation system more sustainable by reducing these emissions and increasing the efficiency of this multimodal system can be achieved through several vehicle-centric strategies. We focus here on one of these strategies – reducing vehicle mass – and on collecting and developing a set of physics-based expressions to describe the effect of vehicle mass reduction on fuel consumption across transportation modes in the U.S. These expressions allow analysts to estimate fuel savings resulting from vehicle mass reductions (termed fuel reduction value, FRV), across modes, without resorting to specialized software or extensive modeling efforts, and to evaluate greenhouse gas emission and cost implications of these fuel savings. We describe how FRV differs from fuel intensity (FI) and how to properly use both of these metrics, and we provide a method to adjust FI based on mass changes and FRV. Based on this work, we estimate that a 10% vehicle mass reduction (assuming constant payload mass) results in a 2% improvement in fuel consumption for trains and light, medium, and heavy trucks, 4% for buses, and 7% for aircraft. When a 10% vehicle mass reduction is offset by an increase in an equivalent mass of payload, fuel intensity (fuel used per unit mass of payload) increases from 6% to 23%, with the largest increase being for aircraft. 相似文献
8.
This article presents a fuel consumption model, SEFUM (Semi Empirical Fuel Use Modeling), and its comparison with three models from the literature on a 600 km experimental database. This model is easy to calibrate with only a few required parameters that are provided by car manufacturers. The test database has been built from 21 drivers who drove in two conditions (normal and ecodriving) on a 15 km trip. For the model evaluation, three indicators have been selected: instantaneous fuel use root mean square error, cumulated error and computation time in order to evaluate the accuracy both in cumulated and instantaneous fuel use and to estimate computation time of each model. Results tend to prove that the model is able to compute rapidly (maximum of 1500 simulated kilometers under Matlab) in comparison to all other models while ensuring a high accuracy and precision for cumulated and instantaneous fuel use. 相似文献
9.
This paper presents a railroad energy efficiency model used to estimate the fuel economies for classes of trains transporting various commodities. Comparable procedures are used to estimate truck and waterway fuel consumption. The results show that coal unit trains are 4.5–5.0 times more energy efficient than movements in the largest trucks allowed in the eastern and western regions of the US, unit grain train movements in the central US are 4.6 times more fuel efficient, soda ash unit train and non-unit train shipments are 4.9 and 3.2 times more efficient, and ethanol unit train and non-unit train movements are 4.8 and 3.0 times more efficient. In terms of barge traffic, coal unit train and non-unit train are 1.3 and 0.9 times as energy efficient in the eastern US, grain unit train and non-unit train movements are 1.7 and 1.0 times more efficient from Minneapolis to the Gulf of Mexico, and grain unit train and non-unit train movements are 1.0 and 0.7 times more fuel efficient from the Upper Ohio River to the Gulf of Mexico. 相似文献
10.
Improved Air Traffic Management (ATM) leading to reduced en route and gate delay, greater predictability in flight planning, and reduced terminal inefficiencies has a role to play in reducing aviation fuel consumption. Air navigation service providers are working to quantify this role to help prioritize and justify ATM modernization efforts. In the following study we analyze actual flight-level fuel consumption data reported by a major U.S. based airline to study the possible fuel savings from ATM improvements that allow flights to better adhere to their planned trajectories both en route and in the terminal area. To do so we isolate the contribution of airborne delay, departure delay, excess planned flight time, and terminal area inefficiencies on fuel consumption using econometric techniques. The model results indicate that, for two commonly operated aircraft types, the system-wide averages of flight fuel consumption attributed to ATM delay and terminal inefficiencies are 1.0–1.5% and 1.5–4.5%, respectively. We quantify the fuel impact of predicted delay to be 10–20% that of unanticipated delay, reinforcing the role of flight plan predictability in reducing fuel consumption. We rank terminal areas by quantifying a Terminal Inefficiency metric based on the variation in terminal area fuel consumed across flights. Our results help prioritize ATM modernization investments by quantifying the trade-offs in planned and unplanned delays and identifying terminal areas with high potential for improvement. 相似文献
11.
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. 相似文献
12.
This paper evaluates the effectiveness of feedback, based on In-Vehicle Data Recorders (IVDR), to improve driving behavior, increase driving safety, and reduce fuel consumption. We developed a framework for driving-behavior measurement, incorporating second-by-second data collected by IVDRs. IVDR units were installed in over 150 vehicles driven by more than 350 drivers for over a year. The experiment was divided into three stages. The first stage was a “blind”, control stage, with no feedback. The second stage incorporated verbal feedback given only to riskiest drivers. In the third stage all drivers received a bi-weekly written report about their driving performance. Safety events, such as braking, lateral acceleration or speeding, were recorded. Supplementary data regarding safety related events and fuel consumption were also collected. Safety incidents and fuel consumption were modeled as a function of IVDR measurement-based events, in order to identify which events best reflect safety incidents and excessive fuel consumption. Our results show that braking events best explain safety incidents, and all events together best explain fuel consumption. In addition, we found that for the riskiest drivers, feedback significantly reduced the IVDR events. Our models show that feedback can lead to a reduction of 8% in safety incidents, and 3–10% in fuel consumption, with a larger reduction obtained for large vehicles. 相似文献
13.
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. 相似文献
14.
The Time-Dependent Pollution-Routing Problem (TDPRP) consists of routing a fleet of vehicles in order to serve a set of customers and determining the speeds on each leg of the routes. The cost function includes emissions and driver costs, taking into account traffic congestion which, at peak periods, significantly restricts vehicle speeds and increases emissions. We describe an integer linear programming formulation of the TDPRP and provide illustrative examples to motivate the problem and give insights about the tradeoffs it involves. We also provide an analytical characterization of the optimal solutions for a single-arc version of the problem, identifying conditions under which it is optimal to wait idly at certain locations in order to avoid congestion and to reduce the cost of emissions. Building on these analytical results we describe a novel departure time and speed optimization algorithm for the cases when the route is fixed. Finally, using benchmark instances, we present results on the computational performance of the proposed formulation and on the speed optimization procedure. 相似文献
15.
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. 相似文献
16.
The continuously variable hydromechanical transmission is an interesting solution for high power vehicles subject to frequent changes of speed, in which the comfort is a significant requirement.Despite their low average efficiency with respect to the mechanical transmissions, the hydromechanical transmissions allow to release the engine speed by the vehicle speed, and to open the possibility for the optimal control of the engine. It follows that the performance and emissions of the powertrain is heavily affected by the logic control.The aim of the paper is to investigate the emission reductions that can be obtained using a Power-Split transmission.Therefore, a hydromechanical transmission has been sized and tested on a 12-ton-city bus by using a one-dimensional model developed in an AMESim environment. Four different control strategies of the powertrain were applied to the model. The CUEDC-ME standard cycle for the characterization of emissions in heavy vehicles was used as a reference mission.The simulation results showed that the hydromechanical transmission reduces consumption or the emission levels with respect to the traditional transmission when managed according to appropriate control strategies. By means of emission values normalized with respect to the standard limits, it is possible to identify a control strategy that allows the reduction of emissions in every usage condition of the vehicle at the expense of a slight increase of consumption.The suggested procedure could help the manufacturer to satisfy the emission standard requirements. 相似文献
17.
In a case study of a Norwegian heavy-duty truck transport company, we analyzed data generated by the online fleet management system Dynafleet. The objective was to find out what influenced fuel consumption. We used a set of driving indicators as explanatory variables: load weight, trailer type, route, brake horsepower, average speed, automatic gearshift use, cruise-control use, use of more than 90% of maximum torque, a dummy variable for seasonal variation, use of running idle, use of driving in highest gear, brake applications, number of stops and rolling without engine load. We found, via multivariate regression analysis and corresponding mean elasticity analysis, that with driving on narrow mountainous roads, variables associated with infrastructure and vehicle properties have a larger influence than driver-influenced variables do. However, we found that even under these challenging infrastructure conditions, driving behavior matters. Our findings and analysis could help transport companies decide how to use fleet management data to reduce fuel consumption by choosing the right vehicle for each transportation task and identifying environmentally and economically benign ways of driving. 相似文献
18.
The aviation community is actively investigating initiatives to reduce aircraft fuel consumption from surface operations, as surface management strategies may face fewer implementation barriers compared with en route strategies. One fuel-saving initiative for the air transportation system is the possibility of holding aircraft at the gate, or the spot, until the point at which they can taxi unimpeded to the departure runway. The extent to which gate holding strategies have financial and environmental benefits hinges on the quantity of fuel that is consumed during surface operations. A pilot of an aircraft may execute the taxi procedure on a single engine or utilize different engine thrust rates during taxi because of a delay. In the following study, we use airline fuel consumption data to estimate aircraft taxi fuel consumption rates during the “unimpeded” and “delayed” portions of taxi time. We find that the fuel consumption attributed to a minute of taxi-out delay is less than that attributed to minute of unimpeded taxi time; for some aircraft types, the fuel consumption rate for a minute of taxi delay is half of that for unimpeded taxi. It is therefore not appropriate, even for rough calculations, to apply nominal taxi fuel consumption rates to convert delayed taxi-out time into fuel burn. On average we find that eliminating taxi delay would reduce overall flight fuel consumption by about 1%. When we consider the savings on an airport-by-airport basis, we find that for some airports the potential reduction from reducing taxi delay is as much as 2%. 相似文献
19.
This paper introduces the fleet size and mix pollution-routing problem which extends the pollution-routing problem by considering a heterogeneous vehicle fleet. The main objective is to minimize the sum of vehicle fixed costs and routing cost, where the latter can be defined with respect to the cost of fuel and CO2 emissions, and driver cost. Solving this problem poses several methodological challenges. To this end, we have developed a powerful metaheuristic which was successfully applied to a large pool of realistic benchmark instances. Several analyses were conducted to shed light on the trade-offs between various performance indicators, including capacity utilization, fuel and emissions and costs pertaining to vehicle acquisition, fuel consumption and drivers. The analyses also quantify the benefits of using a heterogeneous fleet over a homogeneous one. 相似文献
20.
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. 相似文献