Eco-driving: An economic or ecologic driving style?

In this work the trade-off between economic, therefore fuel saving, and ecologic, pollutant emission reducing, driving is discussed. The term eco-driving is often used to refer to a vehicle operation that minimizes energy consumption. However, for eco-driving to be environmentally friendly not only fuel consumption but also pollutant emissions should be considered. In contrast to previous studies, this paper will discuss the advantages of eco-driving with respect to improvements in fuel consumption as well as pollutant gas emissions. Simulating a conventional passenger vehicle and applying numerical trajectory optimization methods best vehicle operation for a given trip is identified. With hardware-in-the-loop testing on an engine test bench the fuel and emissions are measured. An approach to integrate pollutant emission and dynamically choose the ecologically optimal gear is proposed.     

Fuel saving and other benefits of dynamic advisory speeds on a multi-lane arterial road

Current traffic control systems which customarily give no direct information to the driver could benefit by the addition of dynamic advisory speed signs. Such signs, first introduced in the 1950s, can enable drivers to pass through successive green signals and give reduced fuel consumption, stops, travel time, emissions, noise and accidents. To attempt to quantify these reductions, a discrete vehicle simulation using program MULTSIM has been run on a 6 km idealized road and also on 2.3 km of the multi-lane arterial, Military Road, Sydney. Typically, with all drivers complying, fuel savings of the order of 10% and a halving of stops have been predicted. Travel time reductions and fuel savings depend on the coordination speed. Higher coordination speeds favour travel time savings over fuel consumption reductions, whilst lower coordination speeds favour fuel savings. Operation near the minimum fuel consumption speed is desirable. Traffic management could benefit from the change in shape of platoons. This should allow more stringent signal timing in adaptively controlled networks, giving greater flexibility for operational designs.     

Comparison of emerging ground propulsion systems for electrified aircraft taxi operations

Aviation is a mode with high fuel consumption per passenger mile and has significant environmental impacts. It is important to seek ways to reduce fuel consumption by the aviation sector, but it is difficult to improve fuel efficiency during the en-route cruise phase of flight because of technology barriers, safety requirements, and the mode of operations of air transportation. Recent efforts have emphasized the development of innovative Aircraft Ground Propulsion Systems (AGPS) for electrified aircraft taxi operations. These new technologies are expected to significantly reduce aircraft ground-movement-related fuel burn and emissions. This study compares various emerging AGPS systems and presents a comprehensive review on the merits and demerits of each system, followed with the local environmental impacts assessment of these systems. Using operational data for the 10 busiest U.S. airports, a comparison of environmental impacts is performed for four kinds of AGPS: conventional, single engine-on, external, and on-board systems. The results show that there are tradeoffs in fuel and emissions among these emerging technologies. On-board system shows the best performance in the emission reduction, while external system shows the least fuel burn. Compared to single-engine scenario, external AGPS shows the reduction of HC and CO emissions but the increase of NO_x emission. When a general indicator is considered, on-board AGPS shows the best potential of reducing local environmental impacts. The benefit-cost analysis shows that both external and on-board systems are worth being implemented and the on-board system appeals to be more beneficial.     

Fuel saving and ridesharing in the US: Motivations,limitations, and opportunities

Ridesharing can reduce the fuel consumed in noncommercial passenger highway vehicles by grouping individuals into fewer vehicles and reducing the number of miles that vehicles must travel. We estimate the potential fuel savings that could result from an increase in ridesharing in the US. If no additional travel is required to pick up passengers, adding one additional passenger for every 100 vehicles would reduce annual fuel consumption by 0.80–0.82 billion gallons of gasoline per year; if one passenger were added in every 10 vehicles, the potential savings would be 7.54–7.74 billion gallons per year. However, ridesharing may require extra travel to pick up additional passengers, which can reduce and possibly eliminate potential fuel savings. The tradeoff between saving fuel and spending time to pick up additional passengers is investigated, finding that, on average, ridesharing may not be attractive to travelers, but can be made more attractive by increasing per-vehicle-trip costs such as parking and tolls.     

Benefit of speed reduction for ships in different weather conditions

Currently, the shipping industry is facing a great challenge of reducing emissions. Reducing ship speeds will reduce the emissions in the immediate future with no additional infrastructure. However, a detailed investigation is required to verify the claim that a 10% speed reduction would lead to 19% fuel savings (Faber et al., 2012).This paper investigates fuel savings due to speed reduction using detailed modeling of ship performance. Three container ships, two bulk carriers, and one tanker, representative of the shipping fleet, have been designed. Voyages have been simulated by modeling calm water resistance, wave resistance, propulsion efficiency, and engine limits. Six ships have been simulated in various weather conditions at different speeds. Potential fuel savings have been estimated for a range of speed reductions in realistic weather.It is concluded that the common assumption of cubic speed-power relation can cause a significant error in the estimation of bunker consumption. Simulations in different seasons have revealed that fuel savings due to speed reduction are highly weather dependent. Therefore, a simple way to include the effect of weather in shipping transport models has been proposed.Speed reduction can lead to an increase in the number of ships to fulfill the transport demand. Therefore, the emission reduction potential of speed reduction strategy, after accounting for the additional ships, has been studied. Surprisingly, when the speed is reduced by 30%, fuel savings vary from 2% to 45% depending on ship type, size and weather conditions. Fuel savings further reduce when the auxiliary engines are considered.     

Development of a driving cycle for fuel economy in a developing country

A driving cycle corresponding to the driving conditions of a particular country is of decisive importance for fuel economy evaluation of vehicles and automobile engines. The driving pattern was studied in Delhi along four representative routes using a test car equipped with all the instruments required for recording modes of traffic and measuring fuel consumption. An analysis of the field trials results has shown that relative time spent under different modes (cruising, acceleration, etc.) does not practically depend upon a route and rush-or-non rush conditions. Fuel consumption is a function of the average speed and trip length. A four-mode driving cycle has been developed to simulate actual driving conditions with respect to fuel consumption. In comparison with driving cycles of developed countries, the driving cycle has significantly different average speed and relative time spent under acceleration and deceleration. The cycle may be used as a standardized method to evaluate fuel efficiency of vehicles and automobile engines and effect of various gadgets on its improvement.     

Optimal speed advisory for connected vehicles in arterial roads and the impact on mixed traffic

Connected Vehicles (CV) equipped with a Speed Advisory System (SAS) can obtain and utilize upcoming traffic signal information to manage their speed in advance, lower fuel consumption, and improve ride comfort by reducing idling at red lights. In this paper, a SAS for pre-timed traffic signals is proposed and the fuel minimal driving strategy is obtained as an analytical solution to a fuel consumption minimization problem. We show that the minimal fuel driving strategy may go against intuition of some people; in that it alternates between periods of maximum acceleration, engine shut down, and sometimes constant speed, known in optimal control as bang-singular-bang control. After presenting this analytical solution to the fuel minimization problem, we employ a sub-optimal solution such that drivability is not sacrificed and show fuel economy still improves significantly. Moreover this paper evaluates the influence of vehicles with SAS on the entire arterial traffic in micro-simulations. The results show that SAS-equipped vehicles not only improve their own fuel economy, but also benefit other conventional vehicles and the fleet fuel consumption decreases with the increment of percentage of SAS-equipped vehicles. We show that this improvement in fuel economy is achieved with a little compromise in average traffic flow and travel time.     

Development of a driving simulator based eco-driving support system

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.     

Thermodynamic,environmental and economic analysis of absorption air conditioning unit for emissions reduction onboard passenger ships

In this paper, the waste heat of exhaust gases and jacket cooling water in marine diesel engines are analyzed to operate the absorption refrigeration unit (ARU). Thermo-economic and environmental analysis of the absorption refrigeration cycle operated with the two heat sources that use lithium bromide as an absorbent is carried out. The analysis is performed using Engineering Equation Solver (EES) software package where the thermodynamic properties of the steam and the LiBr-water mixtures are provided. The used EES code is verified by published experimental data. As a case study, high speed passenger vessel operating in the Red Sea area has been investigated. The results show that a considerable specific economic benefit could be achieved from ARU jacket cooling water operated over that gained from main engine exhaust gases. Environmentally, applying ARU machine during cruise will reduce the annual fuel consumption for the diesel generators by 156 ton with a reduction percentage of 23%. This will reduce the exhaust gas emissions by 6.3% from the applied main engine emissions. In addition, this will result in reducing NO_x, SO_x, and CO₂ emissions with cost-effectiveness of 4.99 $/kg, 13.18 $/kg, and 0.08 $/kg, respectively.     

Eco-driving key factors that influence fuel consumption in heavy-truck fleets: A Colombian case

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.     

Effects of driving style on the fuel consumption of city buses under different road conditions and vehicle masses

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.     

Evaluation of energy consumption of vehicles in EU Trans-European Transport Network

The paper presents the results of field tests evaluating energy consumption in the vehicles of Trans-European Transport Network (TEN-T) of selected EU countries: Poland, Germany and France. The energy consumption of vehicles in a highway system was assessed based on the telemetry analysis systems for traction parameters, tachograph record of digital speed waveform and their statistical analysis. The empirical cumulative distribution functions of speed transitions (acceleration, deceleration) were used to determine the kinetic energy losses of the vehicle (fuel consumption). To assess the statistical significance of differences between cumulative distribution functions the Smirnov–Kolmogorov test was used.     

Effects of the 80 km/h and variable speed limits on air pollution in the metropolitan area of barcelona

In 2008 the regional government of Catalonia (Spain) reduced the maximum speed limit on several stretches of congested urban motorway in the Barcelona metropolitan area to 80 km/h, while in 2009 it introduced a variable speed system on other stretches of its metropolitan motorways. We use the differences-in-differences method, which enables a policy impact to be measured under specific conditions, to assess the impact of these policies on emissions of NO_x and PM₁₀. Empirical estimation indicate that reducing the speed limit to 80 km/h causes a 1.7–3.2% increase in NO_x and 5.3–5.9% in PM₁₀. By contrast, the variable speed policy reduced NO_x and PM₁₀ pollution by 7.7–17.1% and 14.5–17.3%. As such, a variable speed policy appears to be a more effective environmental policy than reducing the speed limit to a maximum of 80 km/h.     

Well-to-wheel assessment of natural gas vehicles and their fuel supply infrastructures – Perspectives on gas in transport in Denmark

In this paper, potential natural gas and renewable natural gas supply pathways and natural gas vehicles (NGVs) have been selected and evaluated with regards to well-to-wheel energy expended, greenhouse gas (GHG) emissions, and regulated (air pollutant) emissions. The vehicles included in the evaluation are passenger cars, light-duty vehicles (LDVs), and heavy-duty vehicles (HDVs) for road-transport applications, and a short-range passenger vessel for maritime transport applications. The results show that, compared to conventional fuels, in both transport applications and for all vehicle classes, the use of compressed and liquefied natural gas has a 15–27% GHG emissions reduction effect per km travel. The effect becomes large, 81–211%, when compressed and liquefied renewable natural gas are used instead. The results are sensitive to the type and source of feedstock used, the type of vehicle engine, assumed methane leakage and methane slip, and the allocated energy and environmental digestate credits, in each pathway. In maritime applications, the use of liquefied natural gas and renewable natural gas instead of low sulfur marine fuels results in a 60–100% SOx and 90–96% PM emissions reduction. A 1% methane slip from a dedicated LNG passenger vessel results, on average, in 8.5% increase in net GHG emissions.     

Does winter road maintenance help reduce air emissions and fuel consumption?

Winter road maintenance (WRM) has been shown to have significant benefits of improving road safety and reducing traffic delay caused by adverse weather conditions. It has also been suggested that WRM is also beneficial in terms of reducing vehicular air emissions and fuel consumptions because snow and ice on road surface often cause the drivers to reduce their vehicle speeds or to switch to high gears, thus decreasing fuel combustion efficiency. However, there has been very limited information about the underlying relationship, which is important for quantifying this particular benefit of a winter road maintenance program. This research is focused on establishing a quantitative relationship between winter road surface conditions and vehicular air emissions. Speed distribution models are developed for the selected Ontario highways using data from 22 road sites across the province of Ontario, Canada. The vehicular air emissions under different road surface conditions are calculated by coupling the speed models with the engine emission models integrated in the emission estimation model - MOVES. It was found that, on the average, a 10% improvement in road surface conditions could result in approximately 0.6–2% reduction in air emissions. Application of the proposed methodology is demonstrated through a case study to analyse the air emission and energy consumption effects under specific weather events.     

The measurement of train noise: a case study in northern Italy

This paper analyses the interactions between vehicles, infrastructure and environment for rail traffic. It identifies variables having a significant influence on sound levels, defines a standard procedure for measuring noise, and develops a database for setting up and calibrating train noise models. A pilot study looks at two railway lines passing through Vercelli, a medium sized town in the north-west of Italy. Four main conclusions were drawn. First, in certain conditions, variables that normally influence noise production can be neglected (e.g. when surrounding environmental conditions are constant, different types of train do not cause a significant variation in noise level). Secondly, when diesel trains are travelling at less than 70 km/h, a speed change of 30–40 km/h significantly affects the maximum noise level (Lmax). However, for electrified lines, when speed is below 80 km/h, a change of 20–30 km/h does not cause significant variations in Lmax. Thirdly, for diesel trains transiting at low speeds––e.g. near stations––noise emissions are strongly affected by acceleration/deceleration. Lastly, an approach based on ‘sites types’ is able to produce useful results because site configuration and the presence of building significantly affect Lmax. High buildings along the line can increase noise levels and may nullify the advantages derived from technological advance in the vehicles.     

Estimation of nitrogen oxides emissions from petrol and diesel passenger cars by means of on-board monitoring: Effect of vehicle speed,vehicle technology,engine type on emission rates

NO_X emission rates of 13 petrol and 3 diesel passenger cars as a function of average speed from 10 to 120 km/h, emission class (pre-Euro 1 – Euro 5), engine type were investigated by on-board monitoring on roads and highways of St. Petersburg using a portative Testo XXL 300 gas analyzer. The highest level of NO_X emission 0.5–2.5 g/km was inherent to old pre-Euro 1 petrol cars without a catalytic converter. NO_X emissions rates of Euro 1 and Euro 2 petrol cars changed within 0.15–0.9 g/km, Euro 3 – 0.015–0.27 g/km, Euro 4 – 0.013–0.1 g/km, Euro 5 – 0.002–0.043 g/km. Euro 3 – Euro 4 petrol cars generally satisfied corresponding NO_X Emission Standards (ES), except cold-start period, Euro 5 petrol cars did not exceed ES. Warmed, stabilized engines of Euro 3 – Euro 5 petrol cars showed 5–10 times lower NO_X emission rates than corresponding ES in the range of speed from 20 to 90 km/h. NO_X emission rates of diesel Euro 3 and Euro 4 cars varied from 0.45 to 1.1 g/km and from 0.31 to 1.1 g/km, respectively. Two examined diesel Euro 3 and one Euro 4 passenger vehicles did not satisfy NO_X ES at real use. Euro 3 diesel cars showed 28.9 times higher NO_X emissions than Euro 3 petrol cars and Euro 4 diesel car demonstrated 17.6 times higher NO_X emissions than Euro 4 petrol cars at warmed and stabilized engine at a cruise speed ranging from 30 to 60 km/h.     

Fast computing and approximate fuel consumption modeling for Internal Combustion Engine passenger cars

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.     

Improving fuel consumption and CO2 emissions calculations in urban areas by coupling a dynamic micro traffic model with an instantaneous emissions model

Τhis study demonstrates the combination of a microscopic traffic simulator (AIMSUN) with an instantaneous emissions model (AVL CRUISE) to investigate the impact of traffic congestion on fuel consumption on an urban arterial road. The micro traffic model was enhanced by an improved car-following law according to Morello et al. (2014) and was calibrated to replicate measured driving patterns over an urban corridor in Turin, Italy, operating under adaptive urban traffic control (UTC). The method was implemented to study the impact of congestion on fuel consumption for the category of Euro 5 diesel <1.4 l passenger cars. Free flow and congested conditions led to respective consumption differences of −25.8% and 20.9% over normal traffic. COPERT 5 rather well predicted the impact of congestion but resulted to a much lower relative reduction in free flow conditions. Start and stop system was estimated to reduce consumption by 6% and 11.9% under normal and congested conditions, respectively. Using the same modelling approach, UTC was found to have a positive impact on CO₂ emissions of 8.1% and 4.5% for normal and congested conditions, respectively, considering the Turin vehicle fleet mix for the year 2013. Overall, the study demonstrates that the combination of detailed and validated micro traffic and emissions models offers a powerful combination to study traffic and powertrain impacts on greenhouse gas and fuel consumption of on road vehicles over a city network.