Fuel-saving Technologies Research Articles

A Novel Energy Management Strategy for Plug-in Hybrid Electric Buses Based on Model Predictive Control and Estimation of Distribution Algorithm

Energy management strategies determine how much energy is consumed by the engine and electric motor of plug-in hybrid electric buses (PHEBs), which represent critical fuel-saving technologies. In this study, a model predictive control (MPC) method with the estimation of distribution algorithm (EDA) as the solver is proposed to optimize the energy flow of PHEBs. Inspired by the recursive mechanism, short-term velocity prediction is achieved based on a Markov chain model with online updates to greatly improve prediction accuracy. Then, the energy-flow control problem of PHEBs is formulated as a discrete-time nonlinear optimization problem. Due to its strong nonlinear multivariable and constrained nature, the control algorithm is implemented by using MPC. To obtain an optimal solution efficiently, the EDA algorithm is incorporated into the MPC-based control framework, in which the Gaussian distribution is selected as a probabilistic model to characterize the candidate solutions and make full use of the statistical information extracted from the search experience. All performance verifications were conducted by theoretical simulation and hardware-in–the-loop. The verification results show that the proposed strategy can greatly improve the fuel economy and the shorten computational time over cycle-based driving.

Quantifying fuel-saving benefit of low-rolling-resistance tyres from heavy goods vehicle in-service operations

It is important to understand real-world performance of fuel-saving technologies for heavy goods vehicles (HGVs). This paper concerns applying data mining to quantify the fuel-saving benefit of a low-rolling-resistance (LRR) tyre using in-service operational data. Two HGVs of the same specification were employed, with one using LRR tyres and the other conventional tyres. A smartphone-based data logger was developed to collect data from the HGVs’ operations on publics roads for three months. Data from vehicle Controller Area Network, smartphone sensors, weather and elevation databases were collected. A data mining methodology was developed to mine data segments representing dynamically similar driving conditions between the two HGVs, and compare their fuel consumption rates through fitting data to a theoretical vehicle fuel consumption model. It was found that at a 95% confidence level the LRR tyres exclusively brought about a fuel-saving benefit between 6.89% and 8.37% in typical UK motorway driving conditions.

Decarbonization of the Cargo Shipping Fleet

Abstract In an effort to combat climate change, the International Maritime Organization (IMO) has set ambitious goals for the reduction of greenhouse gas emissions from ships, with a target of at least a 50% reduction of total annual greenhouse gas (GHG) emissions, including carbon, from 2008 levels by 2050, with a further goal of zero GHG emissions within this century. Numerous technologies are under development to address these new goals, but the implementation of these new technologies is quite uncertain. Cargo ship owners face the challenge of determining how to best employ and possibly upgrade the current fleet to meet interim goals while awaiting the maturation of future technologies. This article describes a methodology and computer code that provide a rapid assessment of the impact of various fuel-saving technologies on an existing cargo ship’s fuel consumption, thus providing the ship owner fundamental data indicating which upgrades and practices warrant further, more detailed investigation. Background According to the National Oceanic and Atmospheric Administration, the amount of carbon dioxide in the atmosphere has increased by 1.78 ppm per year on average since 1980, and the increase is accelerating. Through the 1980s and 1990s, the increase was around 1.5–1.6 ppm per year, but the growth rate has averaged 2.4 ppm per year since 2010 (Tans et al. 2020). Rising levels of carbon dioxide in the atmosphere adversely impact the environment in many ways. For example, increased levels of carbon dioxide dissolving in sea water increase the acidity of the oceans; as pH levels drop, organisms like oysters and corals have trouble maintaining their hard shells and skeletons made from calcium carbonate. If pH levels get too low, the calcium carbonate structures begin dissolving (NOAA 2020). Another example can be found in the NOAA Arctic Report Card in which each year shows an Arctic that is becoming warmer, less frozen, and more fragile; the 2020 report includes data on high land-surface air temperatures, low snow extent, low minimum sea-ice extent, and extreme wildfires (Thoman et al. 2020).

EFFECT OF VARIABLE CANT ANGLE ON SWEEPBACK WING

Winglets are commonly used drag-reduction and fuel-saving technologies in today’s aviation. The primary purpose of the winglets is to reduce the lift-induced drag, therefore improving fuel efficiency and aircraft performance. Traditional winglets are designed as fixed devices attached at the tips of the wings. However, because they are fixed surfaces, they give their best lift-induced drag reduction at a single design point. In this work, we propose the use of variable cant angle winglets which could potentially allow aircraft to get the best all-around performance (in terms of lift-induced drag reduction), at different angle-of-attack values.This paper describes a XFLR 3-dimensional winglets analysis that was performed on a wing of NACA2412 cross sectional airfoil. The wing has span 2.40 m, root chord 0.180 m, tip chord 0.110 m, sweep angle 5 degree and taper ratio 0.556 and for a winglet NACA 0024 cross-sectional airfoil was considered of max thickness 24 percent at 30 percent chord, max camber 0 percent at 0 percent chord. The present study shows effects of wing without winglet, wing with winglet at cant angle 30, 60, 90.The results obtained from the analysis demonstrate that by carefully adjusting the cant angle, the aerodynamic performance can be improved.

An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications.

Constrained by traditional fuel-saving technologies that have almost reached the limit of fuel-saving potential, the difficulty in changing urban congestion, and the low market penetration rate of new energy vehicles, in the short term, eco-driving seems to be an effective way to achieve energy-saving and emissions reduction in the transportation industry. This paper reviews the energy-saving theory and technology of eco-driving, eco-driving capability evaluation, and the practical application of eco-driving, and points out some limitations of previous studies. Specifically, the research on eco-driving theory mostly focuses on a single vehicle in a single scene, and there is a lack of eco-driving research for fleets or regions. In addition, the parameters used to evaluate eco-driving capabilities mainly focus on speed, acceleration, and fuel consumption, but external factors that are not related to the driver will affect these parameters, making the evaluation results unreasonable. Fortunately, vehicle big data and the Internet of Vehicles (V2I) provides an information basis for solving regional eco-driving, and it also provides a data basis for the study of data-driven methods for the fair evaluation of eco-driving. In general, the development of new technologies provides new ideas for solving some problems in the field of eco-driving.

Smart Policy for Smart Vehicles: Regulatory revisions to incentivize efficient autonomous automobiles

Transportation accounts for nearly 30% of the United States’ annual greenhouse gas emissions and is currently the fastest growing source of emissions by economic sector. National policies are therefore needed to mitigate the climatic impact of vehicular travel. Autonomous vehicle technologies, such as adaptive cruise control and real-time route optimization, can potentially improve fuel efficiency. However, many emerging technologies remain too inefficient to meet federal fuel economy standards set by the U.S. Environmental Protection Agency and the National Highway Traffic Safety Administration. The current regulatory framework therefore hinders vehicle manufacturers from researching and developing greener autonomous technologies. In this analysis, we argue that these federal agencies should adopt policies like technology waivers, regulatory credits, environmentally preferable purchasing, and educational programs to stimulate the development of more efficient autonomous vehicle technologies. These policies would incentivize manufacturers to widely develop and deploy fuel-saving technologies that could potentially realize substantial reductions in greenhouse gas emissions.

The impact of the corporate average fuel economy standards on technological changes in automobile fuel efficiency

This paper empirically examines the effect of the U.S. Corporate Average Fuel Economy (CAFE) standards on the technological progress in automobile fuel efficiency. Using detailed vehicle attributes data from 1978 through 2018, we find that more stringent fuel economy standards increase the rate of technological improvements in new passenger cars, and this effect is primarily driven by the response of U.S. automakers. We do not find evidence that CAFE standards have a similar effect on the technical change in light-duty trucks. Our results also indicate that higher gasoline prices have a significant and positive effect on the improvement of fuel-saving technology in both passenger cars and light trucks. Using our empirical estimates, we project that the recent rollback of Obama-era CAFE standards would forego an approximately 2-percent increase in cars’ fuel economy over the 2021–2025 period as a result of technological progress.

New Sails for Old Ships

Abstract The world’s 100,000 cargo ships produce about as much carbon emissions as Germany. One of the ways to reduce those emissions (and slash fuel costs) is to borrow a technology from the past and harness wind power. By harnessing advanced simulation tools, engineers have developed promising fuel-saving technologies that do not necessarily resemble the tall masted ships of the past. This article shows how Europe is leading the way.

Improving Fishermens Welfare with Fuel-Saving Technology

The problem of energy for fishermen is indeed very complex. When fuel prices rise, it is very worrying that the poor in Indonesia will increase. The study aimed to find out the development of fishermen, as well as the benefits of using Brown’s Gas Electrolyzer (BG-E) on a fishing boat in Indonesia. This type of data is secondary and sourced from second parties (Government Office and others). Analysis, synthesis methods, and alternative problem solving are prepared based on data, information, and observations to solve fisherman's problems based on research objectives. The application of BG-E technology can be applied to small-scale fishing boats, is Outboard Motorboats and 5-30 GT Motorboats. BG-E is made according to the ship's power requirements. The way it works through an electrolysis process to decompose compounds in the form of solutions melts, or ordinary liquids by the electric current flowing through the compound. From the results of the electrolysis process, it produces oxyhydrogen which will react with gasoline in the boat engine. This reaction will produce an explosion to move the piston on the ship's engine so that the engine can live. With the implementation of BG-E, it can save fuel oil consumption and improve the welfare of Indonesian fishermen. The originality of the research is related to the method used in the framework of estimating Fishermen fuel savings in Indonesia, so that the study will become novelty in the future.

Demonstrating an Empirical Tool to Predict Fleet-Wide Heavy-Duty Vehicle Fuel-Saving Benefits from Low Rolling Resistance Tires

The United States Environmental Protection Agency has identified the use of low rolling resistance (LRR) tires as an effective fuel-saving technology for heavy-duty vehicles (HDV). However, adoption of LRR tires has been less than desired because of potential performance uncertainties under real-world operating conditions. Also, previous decision-support tools developed to help stakeholders have had limited accuracy because of inherent transient speed profiles in real-world operating cycles. This study develops a tool to predict HDV fleet-wide fuel saving from LRR tires. The tool uses empirical models to estimate the fuel-saving benefits of LRR tires as a function of vehicle characteristics, operating cycles, and route characteristics. To facilitate ease-of-use by stakeholders, the empirical models have been transformed into a Microsoft Excel spreadsheet tool. The empirical models were developed with data generated by simulating real-world HDV operating cycles with Autonomie, an advanced model for automotive control-system design, and simulating vehicle energy consumption and performance. Validation analysis of the tool shows an average error of less than 6.5%. Unlike previous tools, the developed tool is applicable to both stabilized and transient speed operations. It allows users to customize it to their specific fleet and operating conditions. This is significant and it is envisaged that the tool will facilitate more investment decisions by fleet operators, as well as help regulatory agencies and policy analysts design key policy incentives.

CFD Study of the Impact of Variable Cant Angle Winglets on Total Drag Reduction

Winglets are commonly used drag-reduction and fuel-saving technologies in today’s aviation. The primary purpose of the winglets is to reduce the lift-induced drag, therefore improving fuel efficiency and aircraft performance. Traditional winglets are designed as fixed devices attached at the tips of the wings. However, because they are fixed surfaces, they give their best lift-induced drag reduction at a single design point. In this work, we propose the use of variable cant angle winglets which could potentially allow aircraft to get the best all-around performance (in terms of lift-induced drag reduction), at different angle-of-attack values. By using computational fluid dynamics, we study the influence of the winglet cant angle and sweep angle in the performance of a benchmark wing at a Mach number of 0.8395. The results obtained demonstrate that by carefully adjusting the cant angle, the aerodynamic performance can be improved at different angles of attack.

Consumer willingness to pay for vehicle attributes: What do we Know?

As standards for vehicle greenhouse gas emissions and fuel economy have become more stringent, concerns have arisen that the incorporation of fuel-saving technologies may entail tradeoffs with other vehicle attributes important to consumers such as acceleration performance. Assessing the effects of these tradeoffs on consumer welfare requires estimates of both the degree of the tradeoffs, and consumer willingness to pay (WTP) for the foregone benefits. This paper has two objectives. The first is to review recent literature that presents, or can be used to calculate, marginal WTP (MWTP) for vehicle attributes to describe the attributes that have been studied and the estimated MWTP values. We found 52 U.S.-focused papers with sufficient data to calculate WTP values for 142 different vehicle attributes, which we organized into 15 general groups of comfort, fuel availability, fuel costs, fuel type, incentives, model availability, non-fuel operating costs, performance, pollution, prestige, range, reliability, safety, size, and vehicle type. Measures of dispersion around central MWTP values typically show large variation in MWTP values for attributes. We explore factors that may contribute to this large variation via analysis of variance (ANOVA) and find that, although most have statistically significant effects, they account for only about one third of the observed variation. Case studies of papers that provide estimates from a variety of model formulations and estimation methods suggest that decisions made by researchers can strongly influence MWTP estimates. The paper’s second objective is to seek consensus estimates for WTP for fuel cost reduction and increased acceleration performance. Meta-analysis of MWTP for reduced fuel cost indicates that estimates based on revealed vs. stated preference data differ, as do estimates from models that account for endogeneity and those that do not. We find greater consistency in estimates of MWTP for acceleration despite substantial uncertainty about the overall mean. We conclude with recommendations for improving the understanding of consumers’ MWTP for vehicle attributes.

Re-searching for hidden costs: Evidence from the adoption of fuel-saving technologies in light-duty vehicles

A variety of fuel-saving technologies have been implemented in light-duty vehicles since 2012 under the U.S. Environmental Protection Agency’s (EPA) and Department of Transportation (DOT)’s light-duty vehicle greenhouse gas emissions and fuel economy standards. Questions have arisen whether there are hidden costs that have not been included in the net benefit calculations as a result of adoption of the new technologies. In this paper, we replicate and expand results from Helfand et al. (2016). We define hidden costs of the new technologies as problems with operational characteristics such as acceleration, handling, ride comfort, noise, braking feel, and vibration, not all of which are easily measured by objective criteria. We overcome the empirical challenge by using data coded from online professional auto reviews that qualitatively evaluate fuel-saving technologies and operational characteristics for model years 2014 and 2015 vehicles. We estimate relationships of fuel-saving technologies and operational characteristics, including an overall vehicle assessment, and find little correlation of hidden costs with the technologies themselves. Variable quality of implementation of technologies across automakers may better explain negatively evaluated operational characteristics. The results imply that automakers have typically been able to implement fuel-saving technologies without harm to vehicle operational characteristics.

Dynamic Eco-Driving’s Fuel Saving Potential in Traffic: Multi-Vehicle Simulation Study Comparing Three Representative Methods

Dynamiceco-driving is a well-known umbrella term describing speed control schemes that utilize connected and automated vehicle technology for the purpose of saving fuel. If dynamic eco-driving is to be widely prescribed as an integral part of widespread fuel-saving endeavors, its expected performance as part of the overall traffic system must be analyzed. Specifically, it must be determined to what extent this type of control remains effective in the presence of dense traffic. This paper presents a series of multi-vehicle traffic simulations, which begin to answer important questions surrounding the effects of dynamic eco-driving on traffic and its potential for fuel savings in a mixed traffic environment. Three representative methods of dynamic eco-driving are tested in various high traffic scenarios and the estimated fuel economy, trip time, and average speed results are compared. Independent variables include technology penetration rate and amount of traffic, quantified by the delay level of service of the road network’s traffic light facility. It is shown that, for the given test cases, average mpg increases linearly with technology penetration rate and dynamic eco-driving causes an average increase in mpg regardless of traffic amount. Overall results are promising for the usefulness of this clever class of fuel-saving technologies, in high traffic as well as low.

Consumer inattention and the demand for vehicle fuel cost savings

Consumer undervaluation of energy cost savings is a common explanation for the energy efficiency gap, where markets fail to adopt fuel-saving technologies even though the value of the savings exceeds the costs. This paper presents empirical evidence on the relationship between a possible cause of empirical studies finding undervaluation – consumer inattention – and the demand for fuel cost savings in automobiles. Using survey data on respondents’ attention to automobile fuel costs, attribute preferences, and discrete choice experiments, I find heterogeneity in inattention toward and willingness to pay for fuel cost savings. Estimates from discrete choice models suggest that inattentive consumers make choices as if they undervalue fuel cost savings and attentive consumers make choices as if they fully value these savings. The data show that respondent-specific characteristics that influence fuel costs, such as vehicle miles traveled, partly explain the degree of inattention, a finding that is consistent with models of rational inattention. The results imply that designing energy efficiency policies requires careful consideration of consumer inattention.

APPLYING OPTIMAL CHOICES FOR REAL POWERTRAIN AND LIGHTWEIGHTING TECHNOLOGY OPTIONS TO PASSENGER VEHICLES UNDER UNCERTAINTY

This paper illustrates how cost-constrained optimization based on a set of real lightweighting and powertrain efficiency options can be used to guide decision-making for automotive manufacturers. The paper provides a method for answering the question posed by Original Equipment Manufacturers (OEMs): ‘given a maximum amount additional cost which can be passed on to consumers for fuel-saving technology with uncertain manufacturing cost, to what degree should it be spent on lightweighting versus powertrain efficiency improving technology’. The optimization is formulated as a 0–1 knapsack problem, and dynamic programming is used to find the global optimum technology combination at various levels of maximum up-front technology cost. This paper builds on previous work, which showed that for continuous marginal cost functions under uncertainty, a decision heuristic to either implement lightweighting technology or efficiency technology but not both under cost constraints was preferable. This work extends that result to provide more quantitative strategies for dealing with uncertainty, and finds that, despite uncertainty, optimum lightweighting and efficiency technology selections can be made for the real discrete cases studied. It is found that while the optimum efficiency technology set is highly sensitive to the up-front cost a consumer is willing to pay for future operational savings, lightweighting options are often selected preferentially to efficiency reduction measures. In the same sense, although both technologies are very sensitive to discount rate, lightweighting technologies are less sensitive. Fully hybridized vehicles emerge as a robust option, and, surprisingly, rank highly together with fully electric powertrains.

The Effect of Market Size on Fuel-Saving Technology Adoption in Passenger Vehicles

This paper looks at market size changes and fuel-saving technology adoption in the US new passenger vehicle market. An empirical analysis combines vehicle characteristics and sales from 1997 to 2013 with purchasing patterns by demographic group. The authors find that a 10% increase in market size raises power train efficiency by .3 percentage points. The report discusses the implications of these results including fuel price influence on the introduction of new vehicle technology; the effect of shifts in demographics; and impacts of fuel tax, feebate, or fuel economy standard increases.

Searching for hidden costs: A technology-based approach to the energy efficiency gap in light-duty vehicles

The benefit-cost analysis of standards to reduce vehicle greenhouse gas emissions and improve fuel economy by the U.S. Environmental Protection Agency (EPA) and the Department of Transportation (DOT) displays large net benefits from fuel savings for new vehicle buyers. This finding points to an energy efficiency gap: the energy-saving technology provided in private markets appears not to include all the technologies that produce net private benefits. The gap exists if the costs of energy-saving technologies are lower than the present value of fuel reductions, and “hidden costs” – undesirable aspects of the new technologies – do not exceed the net financial benefits. This study examines the existence of hidden costs in energy-saving technologies through a content analysis of auto reviews of model-year 2014 vehicles.Results suggest that it is possible to use fuel-saving technologies on vehicles without imposing hidden costs. For each technology examined, reviews with positive evaluations outnumbered those with negative evaluations. Evidence is scant of a robust relationship between vehicles’ use of energy-saving technologies and negatively rated operational characteristics, such as handling or acceleration. Results do not provide evidence for hidden costs as the explanation of the efficiency gap for vehicle fuel-saving technologies.

Novel large scale simulation process to support dot’s cafe modeling system

This paper demonstrates a new process that has been specifically designed for the support of the U.S. Department of Transportation’s (DOT’s) Corporate Average Fuel Economy (CAFE) standards. In developing the standards, DOT’s National Highway Traffic Safety Administration made use of the CAFE Compliance and Effects Modeling System (the “Volpe model” or the “CAFE model”), which was developed by DOT’s Volpe National Transportation Systems Center for the 2005–2007 CAFE rulemaking and has been continuously updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The Volpe model relies on numerous technology-related and economic inputs, such as market forecasts, technology costs, and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees”. Part of the model’s function is to estimate CAFE improvements that a given manufacturer could achieve by applying additional technology to specific vehicles in its product line. A significant number of inputs to the Volpe decision-tree model are related to the effectiveness (fuel consumption reduction) of each fuel-saving technology. Argonne National Laboratory has developed a fullvehicle simulation tool named Autonomie, which has become one of the industry’s standard tools for analyzing vehicle energy consumption and technology effectiveness. Full-vehicle simulation tools use physics-based mathematical equations, engineering characteristics (e.g., engine maps, transmission shift points, and hybrid vehicle control strategies), and explicit drive cycles to predict the effectiveness of individual and combined fuel-saving technologies. The Large-Scale Simulation Process accelerates and facilitates the assessment of individual technological impacts on vehicle fuel economy. This paper will show how Argonne efficiently simulates hundreds of thousands of vehicles to model anticipated future vehicle technologies.

Medium-Duty Vehicle Fuel Saving Technology Analysis to Support Phase 2 Regulations

Medium-Duty Vehicle Fuel Saving Technology Analysis to Support Phase 2 Regulations