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In the present work, five surrogate components (n-Hexadecane, n-Tetradecane, Heptamethylnonane, Decalin, 1-Methylnaphthalene) are proposed to represent liquid phase of diesel fuel, and another different five surrogate components (n-Decane, n-Heptane, iso-Octane, MCH (methylcyclohexane), Toluene) are proposed to represent vapor phase of diesel fuel. For the vapor phase, a 5-component surrogate chemical kinetic mechanism has been developed and validated. In the mechanism, a recently updated H2/O2/CO/C1 detailed sub-mechanism is adopted for accurately predicting the laminar flame speeds over a wide range of operating conditions, also a recently updated C2-C3 detailed sub-mechanism is used due to its potential benefit on accurate flame propagation simulation. For each of the five diesel vapor surrogate components, a skeletal sub-mechanism, which determines the simulation of ignition delay times, is constructed for species C4-Cn.

This study investigated the potential of generating reactive chemical species (including radicals) through pilot fuel injection in negative valve overlap for improving the combustion and emissions performances of spark ignition gasoline engines under low load and low speed operating conditions. Several Ford sub-models were used for simulating the physics and chemistry processes of injecting a small amount of fuel in NVO (negative valve overlap). Effects of different NVO degrees and different pilot injection timings, factors for fuel conversion were simulated and investigated. CO and H2 conversions during NVO, CO and H2 amounts before spark timing were used for comparing different schemes.

In order to decarbonize and lower the overall emissions of the transport sector, immediate and cost-effective powertrain solutions are needed. Natural gas offers the advantage of a direct reduction of carbon dioxide (CO2) emissions due to its better Carbon to Hydrogen ratio (C/H) compared to common fossil fuels, e.g. gasoline or diesel. Moreover, an optimized engine design suiting the advantages of natural gas in knock resistance and lean mixtures keeping in mind the challenges of power density, efficiency and cold start manoeuvres. In the public funded project MethMag (Methane lean combustion engine) a gasoline fired three-cylinder-engine is redesigned based on this change of requirements and benchmarked against the previous gasoline engine.

This paper analyzes the use of an ammonia sensor for feedback control in diesel exhaust systems. We build our case around the specific example of the heavy duty transient cycle, and an exhaust system with an SCR catalyst, a single urea injector and an upstream and downstream NOx sensor. A key component in our analysis is the inclusion of the tolerance of the ammonia sensor. We show that with the current understanding of the sensor tolerance, the ammonia sensor has limited benefit for controls.

Connected vehicles (CVs) have situational awareness that can be exploited for control and optimization of the powertrain system. While extensive studies have been carried out for energy efficiency improvement of CVs via eco-driving and planning, the implication of such technologies on the thermal responses of CVs (including those of the engine and aftertreatment systems) has not been fully investigated. One of the key challenges in leveraging connectivity for optimization-based thermal management of CVs is the relatively slow thermal dynamics, which necessitate the use of a long prediction horizon to achieve the best performance. Long-term prediction of the CV speed, unlike the short-range prediction based on vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications-based information, is difficult and error-prone.

There are a variety of test protocols associated with vehicle fuel economy and emissions testing. As a result, a number of test protocols currently exist to measure axle efficiency and spin loss. The intent of this technical paper is to describe a methodology that uses a singular axle efficiency and spin loss procedure. The data can then be used to predict the effects on vehicle FE and GHG for a specific class of vehicles via simulation. An accelerated break-in method using a comparable energy approach has been developed, and can be used to meet the break-in requirements of different vehicle emission test protocols. A “float to equilibrium” sump temperature approach has been used to produce instantaneous efficiency data, which can be used to more accurately predict vehicle FE and GHG, inclusive of Cold CO2. The “Float to Equilibrium” approach and “Fixed Sump Temperature” approach has been compared and discussed.

The introduction of a physics-based zero-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of future compression-ignited engines. The stochastic reactor model mimics mixture and temperature inhomogeneities induced by turbulence, direct injection and heat transfer. Thus, it is possible to improve the prediction of NOx emissions compared to common mean-value models. To reduce the number of designs to be evaluated during the simulation-based multi-objective optimization, genetic algorithms are proven to be an effective tool. Based on an initial set of designs, the algorithm aims to evolve the designs to find the best parameters for the given constraints and objectives. The extension by response surface models improves the prediction of the best possible Pareto Front, while the time of optimization is kept low.

During the course of emissions and fuel economy (FE) testing, vehicles that are calibrated to meet Tier 3 emissions requirements currently must demonstrate compliance on Tier 3 E10 fuel while maintaining emissions capability with Tier 2 E0 fuel used for FE label determination. Tier 3 emissions regulations prescribe lower sulfur E10 gasoline blends for the U.S. market. Tier 3 emissions test fuels specified by EPA are required to contain 9.54 volume % ethanol and 8-11 ppm sulfur content. EPA Tier 2 E0 test fuel has no ethanol and has nominal 30 ppm sulfur content. Under Tier 3 rules, Tier 2 E0 test fuel is still used to determine FE. Tier 3 calibrations can have difficulty meeting low Tier 3 emissions targets while testing with Tier 2 E0 fuel. Research has revealed that the primary cause of the high emissions is deactivation of the aftertreatment system due to sulfur accumulation on the catalysts.

Future LEV-III tailpipe (TP) emission regulations pose an enormous challenge forcing the fleet average of light-duty vehicles produced in the 2025 model year to perform at the super ultralow emission vehicle (SULEV-30) certification levels (versus less than 20% produced today). To achieve SULEV-30, regulated TP emissions of non-methane organic gas (NMOG) hydrocarbons (HCs) and oxygenates plus oxides of nitrogen (NOx) must be below a combined 30 mg/mi (18.6 mg/km) standard as measured on the federal emissions certification cycle (FTP-75). However, when flex-fuel vehicles use E85 fuel instead of gasoline, NMOG emissions at cold start are nearly doubled, before the catalytic converter is active. Passive HC traps (HCTs) are a potential solution to reduce TP NMOG emissions. The conventional HCT design was modified by changing the zeolite chemistry so as to improve HC retention coupled with more efficient combustion during the desorption phase.

In the development of HC traps (HCT) for reducing vehicle cold start hydrocarbon (HC)/nitrogen oxide (NOx) emissions, zeolite-based adsorbent materials were studied as key components for the capture and release of the main gasoline-type HC/NOx species in the vehicle exhaust gas. Typical zeolite materials capture and release certain HC and NOx species at low temperatures (<200°C), which is lower than the light-off temperature of a typical three-way catalyst (TWC) (≥250°C). Therefore, a zeolite alone is not effective in enhancing cold start HC/NOx emission control. We have found that a small amount of Pd (<0.5 wt%) dispersed in the zeolite (i.e., BEA) can significantly increase the conversion efficiency of certain HC/NOx species by increasing their release temperature. Pd was also found to modify the adsorption process from pure physisorption to chemisorption and may have played a role in the transformation of the adsorbed HCs to higher molecular weight species.

Passive in-line catalyzed hydrocarbon (HC) traps have been used by some manufacturers in the automotive industry to reduce regulated tailpipe (TP) emissions of non-methane organic gas (NMOG) during engine cold-start conditions. However, most NMOG molecules produced during gasoline combustion are only weakly adsorbed via physisorption onto the zeolites typically used in a HC trap. As a consequence, NMOG desorption occurs at low temperatures resulting in the use of very high platinum group metal (PGM) loadings in an effort to combust NMOG before it escapes from a HC trap. In the current study, a 2.0 L direct-injection (DI) Ford Focus running on gasoline fuel was evaluated with full useful life aftertreatment where the underbody converter was either a three-way catalyst (TWC) or a HC trap. A new HC trap technology developed by Ford and Umicore demonstrated reduced TP NMOG emissions of 50% over the TWC-only system without any increase in oxides of oxygen (NOx) emissions.

It is anticipated that future gasoline engines will have improved mechanical efficiency and consequently lower exhaust temperatures at low load conditions, although the exhaust temperatures at high load conditions are expected to remain the same or even increase due to the increasing use of downsized turbocharged engines. In 2014, a collaborative project was initiated at Ford Motor Company, Oak Ridge National Lab, and the University of Michigan to develop three-way catalysts with improved performance at low temperatures while maintaining the durability of current TWCs. This project is funded by the U.S. Department of Energy and is intended to show progress toward the USDRIVE target of 90% conversion of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) at 150 °C after high mileage aging. The testing protocols specified by the USDRIVE ACEC team for stoichiometric S-GDI engines were utilized during the evaluation of experimental catalysts at all three facilities.

The design of modern diesel-powered vehicles involves optimization and balancing of trade-offs for fuel efficiency, emissions, and noise. To meet increasingly stringent emission regulations, diesel powertrains employ aftertreatment devices to control nitrogen oxides, hydrocarbons, carbon monoxide, and particulate matter emissions and use active exhaust warm-up strategies to ensure those devices are active as quickly as possible. A typical strategy for exhaust warm-up is to operate with retarded combustion phasing, limited by combustion stability and HC emissions. The amount of exhaust enthalpy available for catalyst light-off is limited by the extent to which combustion phasing can be retarded. Diesel cetane number (CN), a measure of fuel ignition quality, has an influence on combustion stability at retarded combustion phasing. Diesel fuel in the United States tends to have a lower CN (both minimum required and average in market) than other countries.

Thermal effectiveness of Exhaust Gas Recirculation (EGR) coolers used in diesel engines can progressively decrease and stabilize over time due to inner fouling layer of the cooler tubes. Thermophoretic force has been identified as the major cause of diesel exhaust soot fouling, and models are proposed in the literature but improvements in simulation are needed especially for the long-term trend of soot deposition. To describe the fouling stabilization behavior, a removal mechanism is required to account for stabilization of the soot layer. Observations from previous experiments on surrogate circular tubes suggest there are three primary factors to determine removal mechanisms: surface temperature, thickness, and shear velocity. Based on this hypothesis, we developed a 1D CFD fouling model for predicting the thermal effectiveness reduction of real EGR coolers. The model includes the two competing mechanisms mentioned that results in fouling balance.

Emissions and fuel economy optimization of internal combustion engines is becoming more challenging as the stringency of worldwide emission regulations are constantly increasing. Aggressive transient characteristics of new emission test cycles result in transient operation where the majority of soot is produced for turbocharged diesel engines. Therefore soot optimization has become a central component of the engine calibration development process. Steady state approach for air-fuel ratio limitation calibration development is insufficient to capture the dynamic behavior of soot formation and torque build-up during transient engine operation. This paper presents a novel methodology which uses transient maneuvers to optimize the air-fuel ratio limitation calibration, focusing on the trade-off between vehicle performance and engine-out soot emissions. The proposed methodology features a procedure for determining candidate limitation curves with smoothness criteria considerations.

Misfire is generally defined as be no or partial combustion during the power stroke of internal combustion engine. Because a misfired engine will dramatically increase the exhaust emission and potentially cause permanent damage to the catalytic converters, California Air Resources Board (CARB), as well as most of other countries’ on-board diagnostic regulations mandates the detection of misfire. Currently almost all the OEMs utilize crankshaft position sensors as the main input to their misfire detection algorithm. The detailed detection approaches vary among different manufacturers. For example, some chooses the crankshaft angular velocity calculated from the raw output of the crankshaft positon sensor as the measurement to distinguish misfires from normal firing events, while others use crankshaft angular acceleration or the associated torque index derived from the crankshaft position sensor readings as the measurement of misfire detection.

The most significant challenge in emission control for compression ignited internal combustion engines is the suppression of NOx. In the US, NOx-levels have faced a progressive reduction for several years, but recently the introduction of the Real Driving Emissions legislation (RDE) in Europe has not only significantly increased the severity of the required emission reduction but now is in the advent of stretching technology to its limits. Emission control is based on engine-internal optimization to reduce the engine-out emissions in conjunction with aftertreatment technologies, that are either Selective Catalytic Reduction (SCR) or Lean NOx Trap (LNT) based systems. Due to its ability to control high amounts of NOx, SCR is widely used in heavy-duty applications and is becoming more popular in light-duty and passenger car applications as well.

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry.

The automotive industry has been witnessing a major shift towards downsized boosted direct injection engines due to diminishing petroleum reserves and increasingly stringent emission targets. Boosted engines operate at a high mean effective pressure (MEP), resulting in higher in-cylinder pressures and temperatures, effectively leading to increased possibility of abnormal combustion events like knock and pre-ignition. Therefore, the compression ratio and boost pressure in modern engines are restricted, which in-turn limits the engine efficiency and power. To mitigate conditions where the engine is prone to knocking, the engine control system uses spark retard and/or mixture enrichment, which decrease indicated work and increase specific fuel consumption. Several researchers have advocated water injection as an approach to replace or supplement existing knock mitigation techniques.

A three-way catalytic converter (TWC) is an emissions control device, used to treat the exhaust gases in a gasoline engine. The conversion efficiency of the catalyst, however, drops with age or customer usage and needs to be monitored on-line to meet the on board diagnostics (OBD II) regulations. In this work, a non-intrusive catalyst monitor is developed to diagnose the track the remaining useful life of the catalyst based on measured in-vehicle signals. Using air mass and the air-fuel ratio (A/F) at the front (upstream) and rear (downstream) of the catalyst, the catalyst oxygen storage capacity is estimated. The catalyst capacity and operating exhaust temperature are used as an input features for developing a Support Vector Machine (SVM) algorithm based classifier to identify a threshold catalyst. In addition, the distance of the data points in hyperspace from the calibrated threshold plane is used to compute the remaining useful life left.