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A program has been completed to evaluate ultra-low sulfur diesel fuels and passive diesel particulate filters (DPFs) in truck and bus fleets operating in southern California. The fuels, ECD and ECD-1, are produced by ARCO (a BP Company) and have less than 15 ppm sulfur content. Vehicles were retrofitted with two types of catalyzed DPFs, and operated on ultra-low sulfur diesel fuel for over one year. Exhaust emissions, fuel economy and operating cost data were collected for the test vehicles, and compared with baseline control vehicles. Regulated emissions are presented from two rounds of tests. The first round emissions tests were conducted shortly after the vehicles were retrofitted with the DPFs. The second round emissions tests were conducted following approximately one year of operation. Several of the vehicles retrofitted with DPFs accumulated well over 100,000 miles of operation between test rounds.

The knock resistance of gasoline is a key factor to decrease the specific fuel consumption and CO2 emissions of modern turbocharged spark ignition engines. For this purpose, high RON and octane sensitivity (S) are needed. This study shows a relevant synergistic effect on RON and S when formulating a fuel with isooctane, cyclopentane and aromatics, the mixtures reaching RON levels well beyond the ones of individual components. The same is observed when measuring their knock resistance on a boosted single cylinder engine. The mixtures were also characterized on a rapid compression machine at 700 K and 850 K, a shock tube at 1000 K, an instrumented and an adapted CFR engine. The components responsible for the synergistic effects are thus identified. Furthermore, the correlations plotted between these experiments results disclose our current understanding on the origin of these synergistic effects.

The goal of this project was to demonstrate a low emissions, high efficiency heavy-duty on-highway natural gas engine. The emissions targets for this project are to demonstrate US 2010 emissions standards on the 13-mode steady state test. To meet this goal, a chemically correct combustion (stoichiometric) natural gas engine with exhaust gas recirculation (EGR) and a three way catalyst (TWC) was developed. In addition, a Sturman Industries, Inc. camless Hydraulic Valve Actuation (HVA) system was used to improve efficiency. A Volvo 11 liter diesel engine was converted to operate as a stoichiometric natural gas engine. Operating a natural gas engine with stoichiometric combustion allows for the effective use of a TWC, which can simultaneously oxidize hydrocarbons and carbon monoxide and reduce NOx. High conversion efficiencies are possible through proper control of air-fuel ratio.

In this work, the influences of ethanol and iso-butanol blended with gasoline on engine-out and post three-way catalyst (TWC) particle size distribution and number concentration were studied using a General Motors (GM) 2.0L turbocharged spark ignition direct injection (SIDI) engine. The engine was operated using the production engine control unit (ECU) with a dynamometer controlling the engine speed and the accelerator pedal position controlling the engine load. A TSI Fast Mobility Particle Sizer (FMPS) spectrometer was used to measure the particle size distribution in the range from 5.6 to 560 nm with a sampling rate of 1 Hz. U.S. federal certification gasoline (E0), two ethanol-blended fuels (E10 and E20), and 11.7% iso-butanol blended fuel (BU12) were tested. Measurements were conducted at 10 selected steady-state engine operation conditions. Bi-modal particle size distributions were observed for all operating conditions with peak values at particle sizes of 10 nm and 70 nm.

Fuel consumption (FC) has always been an important factor in vehicle cost. With the advent of electronically controlled engines, the controller area network (CAN) broadcasts information about engine and vehicle performance, including fuel use. However, the accuracy of the FC estimates is uncertain. In this study, the researchers first compared CAN-broadcasted FC against physically measured fuel use for three different types of trucks, which revealed the inaccuracies of CAN-broadcast fueling estimates. To match precise gravimetric fuel-scale measurements, polynomial models were developed to correct the CAN-broadcasted FC. Lastly, the robustness testing of the correction models was performed. The training cycles in this section included a variety of drive characteristics, such as high speed, acceleration, idling, and deceleration. The mean relative differences were reduced noticeably.

In the frame of tighter emission requirements and environmental protection, future standards will soon lead to the use of an OBD soot sensor to monitor DPF leakage. Such a sensor will first be introduced in the US by MY 2015 and then in Europe for Euro 6.2 in 2017. The resistive ceramic sensing technology has been selected by most OEM as the most appropriate. The sensor collects the soot in a time cumulative manner and has an internal heater to clean the ceramic before each measurement sequence. The actual challenge of the hardware is to design a wide band collecting system with a high sensitivity and repeatability circuit processing. Electricfil has overcome major drawbacks of the resistive technology with an innovative sensor tip, with filtration features and a boosting electronic scheme. This sensor integrates internal diagnostic capability at power on and during operation.

It is widely understood that cold ambient temperatures increase vehicle fuel consumption due to heat transfer losses, increased friction (increased viscosity lubricants), and enrichment strategies (accelerated catalyst heating). However, relatively little effort has been dedicated to thoroughly quantifying these impacts across a large set of real world drive cycle data and ambient conditions. This work leverages experimental dynamometer vehicle data collected under various drive cycles and ambient conditions to develop a simplified modeling framework for quantifying thermal effects on vehicle energy consumption. These models are applied over a wide array of real-world usage profiles and typical meteorological data to develop estimates of in-use fuel economy. The paper concludes with a discussion of how this integrated testing/modeling approach may be applied to quantify real-world, off-cycle fuel economy benefits of various technologies.

This paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone “interlocking” at each junction location deconflicts railway traffic, affirming safe passage.

In previous SAE papers, the initial development and testing of a vacuum-insulated catalytic converter was presented. This paper provides an update of the converter development and an analysis of potential off-cycle emissions savings. Hot vibration, cool-down, and 1975 Federal Test Procedure (FTP-75) emissions test results are provided to demonstrate the effectiveness of design improvements in greatly increasing durability while retaining performance. Using standard drive cycles and “real-world” driving statistics with a vehicle simulator (ADVISOR©), catalyst temperature and vehicle exhaust emissions of a sport utility vehicle (SUV) were predicted for 16 days of driving (107 trips, 770 total miles). Compared to the baseline vehicle with a conventional catalytic converter, the SUV with a vacuum-insulated converter produced 66% less non-methane hydrocarbon (NMHC), 65% less carbon monoxide (CO), and 60% less oxides of nitrogen (NOx).

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts.

The National Renewable Energy Laboratory's (NREL's) Fleet Test and Evaluations team recently conducted chassis dynamometer tests of a class 8 conventional regional delivery truck over the Heavy Heavy-Duty Diesel Truck (HHDDT), West Virginia University City (WVU City), and Composite International Truck Local and Commuter Cycle (CILCC) drive cycles. A quantitative study analyzed the impacts of various factors on fuel consumption (FC) and fuel economy (FE) by modeling and simulating the truck using NREL's Future Automotive Systems Technology Simulator (FASTSim). Factors included vehicle weight and the coefficients of rolling resistance and aerodynamic drag. Simulation results from a single parametric study revealed that FC was approximately a linear function of the weight, coefficient of aerodynamic drag, and rolling resistance over various drive cycles.

The target of substantial CO₂ reductions in the spirit of the Kyoto Protocol as well as higher engine efficiency requirements has increased research efforts into hybridization of passenger cars. In the frame of this hybridization, there is a real need to develop small Internal Combustion Engines (ICE) with high power density. The two-stroke cycle can be a solution to reach these goals, allowing reductions of engine displacement, size and weight while maintaining good NVH, power and consumption levels. Reducing the number of cylinders, could also help reduce engine cost. Taking advantage of a strong interaction between the design office, 0D system simulations and 3D CFD computations, a specific methodology was set up in order to define a first optimized version of a two-stroke uniflow diesel engine. The main geometrical specifications (displacement, architecture) were chosen at the beginning of the study based on a bibliographic pre-study and the power target in terms.

Smart technologies enabling connection among vehicles and between vehicles and infrastructure as well as vehicle automation to assist human operators are receiving significant attention as a means for improving road transportation systems by reducing fuel consumption – and related emissions – while also providing additional benefits through improving overall traffic safety and efficiency. For truck applications, which are currently responsible for nearly three-quarters of the total U.S. freight energy use and greenhouse gas (GHG) emissions, platooning has been identified as an early feature for connected and automated vehicles (CAVs) that could provide significant fuel savings and improved traffic safety and efficiency without radical design or technology changes compared to existing vehicles. A statistical analysis was performed based on a large collection of real-world U.S. truck usage data to estimate the fraction of total miles that are technically suitable for platooning.

Reducing greenhouse gas emissions to limit global warming is becoming one of the key issues of the 21st century. As a growing contributor to this phenomenon, the aeronautic transport sector has recently taken drastic measures to limit its impact on CO2 and pollutants, like the aviation industry entry in the European carbon market or the ACARE objectives. However the defined targets require major improvements in existing propulsion systems, especially on the gas generator itself. Regarding small power engines for business aviation, rotorcrafts or APU, the turboshaft is today a dominant technology, despite quite high specific fuel consumption. In this context, solutions based on Diesel Internal Combustion Engines (ICE), well known for their low specific fuel consumption, could be a relevant alternative way to meet the requirements of future legislations for low and medium power applications (under 1000kW).

The use of CNG in modern spark ignition turbocharged engine offers many advantages such as high knocking resistance, low CO₂ emissions and high specific power outputs. On the other hand, compared to gasoline, the volumetric efficiency is significantly decreased when CNG is port-injected due to its low energy density. In order to address this issue, recent studies have successfully highlighted the advantages on port-injection engines of the CIGAL™ concept (Concomitant Injection of Gas And Liquid fuels) from IFP Energies Nouvelles. However, the combination of port-injection of CNG with direct injection of gasoline remains unexplored. This paper investigates this novel injection concept on the four-cylinder 1.6L turbocharged GDI engine with inlet variable valve timing resulting from the cooperation between PSA Peugeot-Citroen and the BMW Group.

In this study, a 15-L heavy-duty diesel engine and an emission control system consisting of diesel oxidation catalysts, NOx adsorber catalysts, and diesel particle filters were evaluated over the course of a 2000 hour aging study. The work is a follow-on to a previously documented development effort to establish system regeneration and sulfur management strategies. The study is one of five projects being conducted as part of the U.S. Department of Energy's Advanced Petroleum Based Fuels - Diesel Emission Control (APBF-DEC) activity. The primary objective of the study was to determine if the significant NOx and PM reduction efficiency (>90%) demonstrated in the development work could be maintained over time with a 15-ppm sulfur diesel fuel. The study showed that high NOx reduction efficiency can be restored after 2000 hours of operation and 23 desulfation cycles.

Current progress in the development of diesel engines substantially contributes to the reduction of NOx and Particulate Matter (PM) emissions but will not succeed to eliminate the application of Diesel Particulate Filters (DPFs) in the future. In the past we have introduced a Multi-Functional Reactor (MFR) prototype, suitable for the abatement of the gaseous and PM emissions of the Low Temperature Combustion (LTC) engine operation. In this work the performance of MFR prototypes under both conventional and advanced combustion engine operating conditions is presented. The effect of the MFR on the fuel penalty associated to the filter regeneration is assessed via simulation. Special focus is placed on presenting the performance assessment in combination with the existing differences in the morphology and reactivity of the soot particles between the different modes of diesel engine operation (conventional and advanced). The effect of aging on the MFR performance is also presented.

This paper describes the results of Phase 1 of the Diesel Emission Control - Sulfur Effects (DECSE) Program. The objective of the program is to determine the impact of fuel sulfur levels on emissions control systems that could be used to lower emissions of nitrogen oxides (NOx) and particulate matter (PM) from vehicles with diesel engines. The DECSE program has now issued four interim reports for its first phase, with conclusions about the effect of diesel sulfur level on PM and total hydrocarbon (THC) emissions from the high-temperature lean-NOx catalyst, the increase of engine-out sulfate emissions with higher sulfur fuel levels, the effect of sulfur content on NOx adsorber conversion efficiencies, and the effect of fuel sulfur content on diesel oxidation catalysts, causing increased PM emissions above engine-out emissions under certain operating conditions.

Alternative compression ignition engine fuels are of interest both to reduce emissions and to reduce U.S. petroleum fuel demand. A Malaysian Fischer-Tropsch gas-to-liquid fuel was compared with California #2 diesel by characterizing emissions from over the road Class 8 tractors with Caterpillar 3176 engines, using a chassis dynamometer and full scale dilution tunnel. The 5-Mile route was employed as the test schedule, with a test weight of 42,000 lb. Levels of oxides of nitrogen (NOx) were reduced by an average of 12% and particulate matter (PM) by 25% for the Fischer-Tropsch fuel over the California diesel fuel. Another distillate fuel produced catalytically from Fischer-Tropsch products originally derived from natural gas by Mossgas was also compared with 49-state #2 diesel by characterizing emissions from Detroit Diesel 6V-92 powered transit buses, three of them equipped with catalytic converters and rebuilt engines, and three without.

In this paper, an integrated simulation-based methodology demonstrating feasibility and performance of several electric-hybrid concepts is developed. Several advanced tools are coupled to define the specifications of each component of the hybrid powertrain, to select the most promising hybrid architecture and finally to assess the proposed powertrain with regard to CO2 and pollutants emissions. Concurrent minimization of NOx and CO2 emissions enables to find the best compromise to fulfil Euro 6 standards while lowering fuel consumption. This stage consists in an iterative co-optimization of the power split strategies between the electric drive and the Diesel engine and of the engine settings (injection pressure, EGR rate, etc.). The methodology combines optimal control laws and optimization methodology based on global statistical models using single-cylinder design of experiments. After several iterations, this method allows to find the optimal NOx/CO2 trade-off curve.