Environmental Potential of Natural Gas Fuel for Light-Duty Vehicles: An Engine-Dynamometer Study of Exhaust-Emission-Control Strategies and Fuel Consumption

1993 ◽  
Author(s):  
Robert M. Siewert ◽  
Patricia J. Mitchell ◽  
Patricia A. Mulawa
Keyword(s):  
Natural Gas ◽  
Fuel Consumption ◽  
Control Strategies ◽  
Emission Control ◽  
Exhaust Emission ◽  
Light Duty ◽  
Gas Fuel ◽  
Light Duty Vehicles

scholarly journals Analysis and Prediction Model of Fuel Consumption and Carbon Dioxide Emissions of Light-Duty Vehicles

2022 ◽  
Vol 12 (2) ◽  
pp. 803
Author(s):  
Ngo Le Huy Hien ◽  
Ah-Lian Kor
Keyword(s):  
Carbon Dioxide ◽  
Fuel Consumption ◽  
Carbon Dioxide Emissions ◽  
Polynomial Regression ◽  
Control Strategies ◽  
Future Research ◽  
Light Duty ◽  
The Government ◽  
Government Of Canada ◽  
Light Duty Vehicles

Due to the alarming rate of climate change, fuel consumption and emission estimates are critical in determining the effects of materials and stringent emission control strategies. In this research, an analytical and predictive study has been conducted using the Government of Canada dataset, containing 4973 light-duty vehicles observed from 2017 to 2021, delivering a comparative view of different brands and vehicle models by their fuel consumption and carbon dioxide emissions. Based on the findings of the statistical data analysis, this study makes evidence-based recommendations to both vehicle users and producers to reduce their environmental impacts. Additionally, Convolutional Neural Networks (CNN) and various regression models have been built to estimate fuel consumption and carbon dioxide emissions for future vehicle designs. This study reveals that the Univariate Polynomial Regression model is the best model for predictions from one vehicle feature input, with up to 98.6% accuracy. Multiple Linear Regression and Multivariate Polynomial Regression are good models for predictions from multiple vehicle feature inputs, with approximately 75% accuracy. Convolutional Neural Network is also a promising method for prediction because of its stable and high accuracy of around 70%. The results contribute to the quantifying process of energy cost and air pollution caused by transportation, followed by proposing relevant recommendations for both vehicle users and producers. Future research should aim towards developing higher performance models and larger datasets for building APIs and applications.

Powertrain Waste Heat Recovery: A Systems Approach to Maximize Drivetrain Efficiency

2012 ◽  
Author(s):  
Kevin Laboe ◽  
Marcello Canova
Keyword(s):  
Fuel Consumption ◽  
Waste Heat Recovery ◽  
Systems Approach ◽  
Waste Heat ◽  
Combustion Engine ◽  
Heat Energy ◽  
Engine Oils ◽  
Engine Cooling ◽  
Light Duty ◽  
Light Duty Vehicles

Up to 65% of the energy produced in an internal combustion engine is dissipated to the engine cooling circuit and exhaust gases [1]. Therefore, recovering a portion of this heat energy is a highly effective solution to improve engine and drivetrain efficiency and to reduce CO2 emissions, with existing vehicle and powertrain technologies [2,3]. This paper details a practical approach to the utilization of powertrain waste heat for light vehicle engines to reduce fuel consumption. The “Systems Approach” as described in this paper recovers useful energy from what would otherwise be heat energy wasted into the environment, and effectively distributes this energy to the transmission and engine oils thus reducing the oil viscosities. The focus is on how to effectively distribute the available powertrain heat energy to optimize drivetrain efficiency for light duty vehicles, minimizing fuel consumption during various drive cycles. To accomplish this, it is necessary to identify the available powertrain heat energy during any drive cycle and cold start conditions, and to distribute this energy in such a way to maximize the overall efficiency of the drivetrain.

The WLTC vs NEDC: A Case Study on the Impacts of Driving Cycle on Engine Performance and Fuel Consumption

2021 ◽  
Vol 18 (3) ◽  
pp. 9071-9081
Author(s):  
Jakub Lasocki
Keyword(s):  
Fuel Consumption ◽  
Combustion Engine ◽  
Engine Performance ◽  
Driving Cycle ◽  
Performance Characteristics ◽  
Pollutant Emission ◽  
Strong Impact ◽  
Light Duty ◽  
Light Duty Vehicles

The World-wide harmonised Light-duty Test Cycle (WLTC) was developed internationally for the determination of pollutant emission and fuel consumption from combustion engines of light-duty vehicles. It replaced the New European Driving Cycle (NEDC) used in the European Union (EU) for type-approval testing purposes. This paper presents an extensive comparison of the WLTC and NEDC. The main specifications of both driving cycles are provided, and their advantages and limitations are analysed. The WLTC, compared to the NEDC, is more dynamic, covers a broader spectrum of engine working states and is more realistic in simulating typical real-world driving conditions. The expected impact of the WLTC on vehicle engine performance characteristics is discussed. It is further illustrated by a case study on two light-duty vehicles tested in the WLTC and NEDC. Findings from the investigation demonstrated that the driving cycle has a strong impact on the performance characteristics of the vehicle combustion engine. For the vehicles tested, the average engine speed, engine torque and fuel flow rate measured over the WLTC are higher than those measured over the NEDC. The opposite trend is observed in terms of fuel economy (expressed in l/100 km); the first vehicle achieved a 9% reduction, while the second – a 3% increase when switching from NEDC to WLTC. Several factors potentially contributing to this discrepancy have been pointed out. The implementation of the WLTC in the EU will force vehicle manufacturers to optimise engine control strategy according to the operating range of the new driving cycle.

Analysis of emissions from various driving cycles based on real driving measurements obtained in a high-altitude city

2020 ◽  
Vol 234 (6) ◽  
pp. 1563-1571 ◽  
Author(s):  
Meng Lyu ◽  
Xiaofeng Bao ◽  
Yunjing Wang ◽  
Ronald Matthews
Keyword(s):  
High Altitude ◽  
Real World ◽  
Vehicle Emissions ◽  
Control Strategies ◽  
Driving Cycle ◽  
Specific Power ◽  
Test Cycle ◽  
Light Duty ◽  
And Control ◽  
Light Duty Vehicles

Vehicle emissions standards and regulations remain weak in high-altitude regions. In this study, vehicle emissions from both the New European Driving Cycle and the Worldwide harmonized Light-duty driving Test Cycle were analyzed by employing on-road test data collected from typical roads in a high-altitude city. On-road measurements were conducted on five light-duty vehicles using a portable emissions measurement system. The certification cycle parameters were synthesized from real-world driving data using the vehicle specific power methodology. The analysis revealed that under real-world driving conditions, all emissions were generally higher than the estimated values for both the New European Driving Cycle and Worldwide harmonized Light-duty driving Test Cycle. Concerning emissions standards, more CO, NOx, and hydrocarbons were emitted by China 3 vehicles than by China 4 vehicles, whereas the CO2 emissions exhibited interesting trends with vehicle displacement and emissions standards. These results have potential implications for policymakers in regard to vehicle emissions management and control strategies aimed at emissions reduction, fleet inspection, and maintenance programs.

Smart rule-based diesel engine control strategies by means of predictive driving information

2019 ◽  
Vol 20 (10) ◽  
pp. 1047-1058 ◽  
Author(s):  
Giovanni Vagnoni ◽  
Markus Eisenbarth ◽  
Jakob Andert ◽  
Giuseppe Sammito ◽  
Joschka Schaub ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Control Strategies ◽  
Control Unit ◽  
Future Research ◽  
Engine Control ◽  
Test Cycle ◽  
Rule Based ◽  
Prediction Horizon ◽  
Light Duty ◽  
Path Control

The increasing connectivity of future vehicles allows the prediction of the powertrain operational profiles. This technology will improve the transient control of the engine and its exhaust gas aftertreatment systems. This article describes the development of a rule-based algorithm for the air path control, which uses the knowledge of upcoming driving events to reduce especially [Formula: see text] and particulate (soot) emissions. In the first section of this article, the boosting and the lean [Formula: see text] trap systems of a diesel powertrain are investigated as relevant sub-systems for shorter prediction horizons, suitable for Car-to-X communication range. Reference control strategies, based on state-of-the-art engine control unit algorithms and suitable predictive control logics, are compared for the two sub-systems in a model in the loop simulation environment. The simulation driving cycles are based on Worldwide harmonized Light-duty Test Cycle and Real Driving Emissions regulations. Due to the shorter, and consequently more probable, prediction horizon and the demonstrated emission improvements, a dedicated rule-based algorithm for the air path control is developed and benchmarked in the Worldwide harmonized Light-duty Test Cycle as described in the second part of this article. Worldwide harmonized Light-duty Test Cycle test results show an improvement potential for engine-out soot and [Formula: see text] emissions of up to 5.2% and 1.2%, respectively, for the air path case and a reduction of the average fuel consumption in Real Driving Emissions of up to 1% for the lean NOx trap case. In addition, the developed rule-based algorithm allows the adjustment of the desired NOx–soot trade-off, while keeping the fuel consumption constant. The study concludes with brief recommendations for future research directions, as for example, the introduction of a prediction module for the estimation of the vehicle operational profile in the prediction horizon.

scholarly journals Development of a fuel consumption measurement methodology for light duty vehicles in Colombia, based on metrology principles

DYNA ◽  
2020 ◽  
Vol 87 (212) ◽  
pp. 47-56
Author(s):  
Juan Carlos Castillo Herrera ◽  
Juan Camilo López Restrepo ◽  
David Andrés Serrato Tobón ◽  
Juan Esteban Tibaquirá Giraldo ◽  
Sergio Andrés Carvajal Perdomo
Keyword(s):  
Fuel Consumption ◽  
Fossil Fuels ◽  
The United States ◽  
Ambient Conditions ◽  
Road Transportation ◽  
Uncertainty In Measurement ◽  
Light Duty ◽  
Uncertainty Model ◽  
Measurement Methodology ◽  
Light Duty Vehicles

In this study, a methodology to measure fuel consumption for light duty vehicles (LDV) in Colombia was elaborated based on existing methodologies from road transportation worldwide. This methodology was proposed as a tool for the evaluation of energy efficiency strategies applied to vehicles, as well as establishing the baseline for measurement, control, and regulation of consumption of fossil fuels based on metrological criteria. Additionally, the capacities for measurement within Colombia were analyzed, and procedures stated by the Code of Federal Regulations of the United States of America were adopted for measuring fuel consumption of LDV by gravimetric methods. An uncertainty model based on the Guide to the expression of Uncertainty in Measurement (GUM) was elaborated, and the contribution of different variables associated to the measurement process the instruments, the equipment, and the ambient conditions over the uncertainty of the measurand, were analyzed.

Development of a NOx Sensor Minimization Control Algorithm for Control of Gas Engines With NSCR

2013 ◽  
Author(s):  
John M. Gattoni ◽  
Daniel B. Olsen
Keyword(s):  
Natural Gas ◽  
Control Algorithm ◽  
Combustion Engine ◽  
Control Strategies ◽  
Catalyst System ◽  
Critical Issue ◽  
Exhaust Emission ◽  
Oxides Of Nitrogen ◽  
Nox Sensor ◽  
Lambda Sensor

High exhaust emissions reduction efficiencies from a spark ignited (SI) internal combustion engine utilizing a Non Selective Catalyst Reduction (NSCR) catalyst system require complex fuel control strategies. The allowable equivalence ratio (Φ) operating range is very narrow where NSCR systems achieve high exhaust emission reduction efficiencies of multiple species. Current fuel control technologies utilizing lambda sensor feedback for natural gas spark ignited engines are reported to be unable to sustain these demands for extended operation periods and when transients are introduced. Lambda sensor accuracy is the critical issue with current fuel controllers. The goal of this project was to develop a minimization control algorithm utilizing an oxides of nitrogen (NOx) sensor installed downstream of the NSCR catalyst system for feedback air/fuel ratio control. Testing was performed on a 100kW rated natural gas Cummins-Onan generator set that was reconfigured to operate utilizing an electronic gas carburetor (EGC2) with lambda sensor feedback and high reduction efficiency NSCR catalyst system. The control algorithm was programmed utilizing a Labview interface that communicated with the electronic gas carburetor where the fuel trim adjustment was physically made. Improvement under steady state operation was observed. The system was also evaluated during load and fuel composition transients.

Sign in / Sign up

Export Citation Format

Share Document