Search Results

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 paper presents experimental results that validate eco-driving and eco-heating strategies developed for connected and automated vehicles (CAVs). By exploiting vehicle-to-infrastructure (V2I) communications, traffic signal timing, and queue length estimations, optimized and smoothed speed profiles for the ego-vehicle are generated to reduce energy consumption. Next, the planned eco-trajectories are incorporated into a real-time predictive optimization framework that coordinates the cabin thermal load (in cold weather) with the speed preview, i.e., eco-heating. To enable eco-heating, the engine coolant (as the only heat source for cabin heating) and the cabin air are leveraged as two thermal energy storages. Our eco-heating strategy stores thermal energy in the engine coolant and cabin air while the vehicle is driving at high speeds, and releases the stored energy slowly during the vehicle stops for cabin heating without forcing the engine to idle to provide the heating source.

Engine research has increasingly focused on emission of sub 23 nm particulates in recent years. Likewise, current legislative efforts are being made for particulate number (PN) emission limits to include this previously omitted size range. In Europe, PN measurement equipment and procedures for regulatory purposes are defined by the particle measurement programme (PMP). Latest regulation drafts for sub 23 nm measurements specify counting efficiencies with a 65% cut-off size at 10 nm (d65) and a minimum of 90% above 15 nm (d90). Even though alternative instruments, such as differential mobility spectrometers (DMS), are widely used in laboratory environments, the interpretation of their sub 23 nm measurements has not yet been widely discussed. For this study, particulate emissions of a 1.0L gasoline direct injection (GDI) engine have been measured with a DMS system for low to medium speeds with two load steps.

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.

Real world emissions are increasingly the standard of comparison for motor vehicle exhaust impact on the environment. The ability to collect such data has thus far relied primarily on full portable emissions measurement systems (PEMS) that are bulky, expensive, and time consuming to set up. The present work examines four compact, low cost, miniature PEMS (mPEMS) that offer the potential to expand our ability to record real world exhaust emissions over a larger number of operating conditions and combustion engine applications than currently possible within laboratory testing. It specifically addresses the particulate matter (PM) capabilities of these mPEMS, which employ three different methodologies for particle measurement: diffusion charger, optical scattering, and a multi-sensor approach that combines scattering, opacity, and ionization. Their performance is evaluated against solid particle number and PM mass with both vehicle tests and flame generated soot.

In this work we studied the effects of piston bowl design on combustion in a small-bore direct-injection diesel engine. Two bowl designs were compared: a conventional, omega-shaped bowl and a stepped-lip piston bowl. Experiments were carried out in the Sandia single-cylinder optical engine facility, with a medium-load, mild-boosted operating condition featuring a pilot+main injection strategy. CFD simulations were carried out with the FRESCO platform featuring full-geometric body-fitted mesh modeling of the engine and were validated against measured in-cylinder performance as well as soot natural luminosity images. Differences in combustion development were studied using the simulation results, and sensitivities to in-cylinder flow field (swirl ratio) and injection rate parameters were also analyzed.

Characterization of soot nanoparticle morphology can be used to develop understanding of nanoparticle interaction with engine lubricant oil and its additives. It can be used to help direct modelling of soot-induced thickening, and in a more general sense for combatting reductions in engine efficiency that occur with soot-laden oils. Traditional 2D transmission electron microscopy (TEM) characterization possesses several important shortcomings related to accuracy that have prompted development of an alternative 3D characterization technique utilizing electron tomography, known as 3D-TEM. This work details progress made towards facilitating semi-automated image acquisition and processing for location of structures of interest on the TEM grid. Samples were taken from a four cylinder 1.4 L gasoline turbocharged direct injection (GTDI) engine operated in typically extra-urban driving conditions for 20,284 km, with automatic cylinder deactivation enabled.

Gasoline particulate filters (GPFs) are extremely effective at reducing tailpipe emissions of particulate mass and particulate number. Especially in the European and Chinese markets, where a particulate number standard is legislated, we see gasoline particulate filters being deployed in production on gasoline direct injected engines. Due to the high temperature in gasoline exhaust, most applications are expected to be passively regenerating without the help of an active regeneration strategy. However, for the few cases where a customer drive cycle has consistently low speed over a long time frame, an active regeneration strategy may be required. This involves increasing the exhaust temperature at the GPF up to around 600 degC so that soot can be combusted. We compare two different ways of achieving these temperatures, namely spark retard and air fuel ratio modulation. The former generates heat in the engine, the latter generates heat in one or more catalysts in the exhaust system.

Morphology plays an important role in determining behaviour and impact of soot nanoparticles, including effect on human health, atmospheric optical properties, contribution to engine wear, and role in marine ecology. However, its nanoscopic size has limited the ability to directly measure useful morphological parameters such as surface area and effective volume. Recently, 3D morphology characterization of soot nanoparticles via electron tomography has been the subject of several introductory studies. So-called ‘3D-TEM’ has been posited as an improvement over traditional 2D-TEM characterization due to the elimination of the error-inducing information gap that exists between 3-dimensional soot structures and 2-dimensional TEM projections. Little follow-up work has been performed due to difficulties with developing methodologies into robust high-throughput techniques.

Gasoline particulate filters (GPF) with high filtration efficiency (>80%) at zero mileage are in growing demand to meet increasingly tight vehicle emission standards for particulate matter being implemented in US, EU, China and elsewhere. Current efforts to achieve high filter performance mainly focus on fine-tuning the filter structure, such as the pore size distribution and porosity of the bare substrate, or the washcoat loading and location of catalyzed substrates. However, high filtration efficiency may have a cost in high backpressure that negatively affects engine power. On the other hand, it has been recognized in a few reports that very low amounts of ash deposits (from non-combustible residue in the exhaust) can significantly increase filtration efficiency with only a mild backpressure increase.

The availability of connectivity and autonomy enabled resources, within the automotive sector, has primarily been considered for driver assist technologies and for extending the levels of vehicle autonomy. It is not a stretch to imagine that the additional information, available from connectivity and autonomy, may also be useful in further improving powertrain functions. Critical powertrain subsystems that must operate with limited or uncertain knowledge of their environment stand to benefit from such new information sources. Unfortunately, the adoption of this new information resource has been slow within the powertrain community and has typically been limited to the obvious problem choices such as battery charge management for electric vehicles and efforts related to fuel economy benefits from adaptive/coordinated cruise control. In this paper we discuss the application of connectivity resources in the management of an aftertreatment sub-system, the Diesel Particulate Filter (DPF).

The airflow that enters the front grille of a ground vehicle for the purpose of component cooling has a significant effect on aerodynamic drag. This drag component is commonly referred to as cooling drag, which denotes the difference in drag measured between open grille and closed grille conditions. When the front grille is closed, the airflow that would have entered the front grille is redirected around the body. This airflow is commonly referred to as cooling interference airflow. Consequently, cooling interference airflow can lead to differences in vehicle component drag; this component of cooling drag is known as cooling interference drag. One mechanism that has been commonly utilized to directly influence the cooling drag, by reducing the engine airflow, is active grille shutters (AGS). For certain driving conditions, the AGS system can restrict airflow from passing through the heat exchangers, which significantly reduces cooling drag.

Metal foam with their high porosity and heat storage capacity can be combined with phase change materials to be a powerful heat storage device. Numerical simulations of metal foam behavior can be challenging due to their complex geometric patterns necessitating high mesh requirements. Furthermore, simulations of the inner workings of a metal foam heat exchanger comprising of a large number of individual metal foam canisters can be impossible. The objective of the current work is to develop a computational model using a proprietary CFD tool Simerics-MP/Simerics-MP+® to simulate the workings of a metal foam heat exchanger with phase change element. A heat transfer coefficient capturing this heat transfer between wax and metal is used to formulate the “simplified” mixture model. The versatility of the proposed model is in the universality of its application to any shape or structure of metal foam. The computational model developed is tested to replicate the results of the 3D simulation.

There is an ongoing effort in the industry to develop an accelerated corrosion test for automotive heat exchangers. This has become even more important as automakers are focusing on corrosion durability of 15 years in the field versus current target of 10 years. To this end an acid immersion test was developed and reported in a previous paper for condensers (1). This paper extends those results to evaporators and establishes the efficacy of the test using these results and those reported in the literature. The paper also discusses variability in corrosion test results as observed in tests such as ASTM G85:A3 Acidified Synthetic Sea Water Test (SWAAT), and its relation to field durability.

The size and morphology of soot particles and agglomerates extracted from lubricating oil drawn from the sump of a diesel engine have been investigated and compared using Transmission Electron Microscopy (TEM) and Nanoparticle Tracking Analysis (NTA). Samples were prepared for electron microscopy imaging by both centrifugation and solvent extraction to investigate the impact of these procedures on the morphological characteristics, such as skeleton length and width and circularity, of the obtained soot. It was shown that centrifugation increases the extent of agglomeration within the sample, with 15% of the agglomerates above 200 nm compared to only 11% in the solvent extracted soot. It was also observed that the width of centrifugation extracted soot was typically 10 nm to 20 nm larger than that of solvent extracted soot, suggesting that centrifugation forces the individual agglomerate chains together.

The need for gasoline particulate filter (GPF) technology is expected to grow with increasingly tight particle emissions standards being implemented in US, EU, China and elsewhere. Derived from the successful experience with diesel particulate filters (DPF), GPFs adopted the characteristic alternately plugged honeycomb structure that provides a large area of porous cordierite wall for filtering particles with minimal additional backpressure. However, unlike DPFs, continuous soot regeneration in GPFs makes it difficult to grow and sustain the soot cake on the filter wall that gives DPFs their high filtration efficiency. Therefore, filtration performance of low mileage GPFs relies heavily on the porous structure of filter media, which depends on both the substrate and the applied washcoat. In this work, a blank, two fresh washcoated filters and two washcoated filters with 3000 km mileage accumulation were characterized to compare their filtration performance.

Gasoline particulate filters (GPF) are used as an efficient solution to reduce particulate matter (PM) emissions on gasoline vehicles. GPFs are ceramic wall-flow filters and are normally located downstream of conventional three-way catalysts (TWC) [1]. The study in this paper is intended to evaluate the impact of drive cycle and ambient temperature on modelled GPF soot accumulation and regeneration. The test data were obtained through real road testing in Chinese cities including Nanjing, Hainan and Harbin. Five 2.0 L gasoline turbo direct-injection (GTDI) prototype vehicles from several China Stage 6 applications were employed for the road tests. The results of the testing indicated that a drive cycle with low engine speed and engine load, like a typical city road in rush hour traffic in Nanjing, had a low probability of generating high GPF temperatures (> 600 °C) and sufficient oxygen to regenerate the GPF.

Environmental authorities such as EPA, VCA have enforced stringent emissions legislation governing air pollutants released into the atmosphere. Of particular interest is the challenge introduced by the limit on particulate number (PN) counting (#/km) and real driving emissions (RDE) testing; with new emissions legislation being shortly introduced for the gasoline direct injection (GDI) engines, gasoline particulate filters (GPF) are considered the most immediate solution. While engine calibration and testing over the Worldwide harmonized Light vehicles Test Cycle (WLTC) allow for the limits to be met, real driving emission and cold start constitute a real challenge. The present work focuses on an experimental durability study on road under real world driving conditions. Two sets of experiments were carried out. The first study analyzed a gasoline particulate filter (GPF) (2.4 liter, diameter 5.2” round) installed in the underfloor (UF) position and driven up to 200k km.

Control of vehicle powertrain thermal management systems is becoming more challenging as the number of components is growing, and as a result, advanced control methods are being investigated. Model predictive control (MPC) is particularly interesting in this application because it provides a suitable framework to manage actuator and temperature constraints, and can potentially leverage preview information if available in the future. In previous SAE publications (2015-01-0336 and 2016-01-0215), a robust MPC control formulation was proposed, and both simulation and powertrain thermal lab test results were provided. In this work, we discuss the controller deployment in a vehicle; where controller validation is done through road driving and on a wind tunnel chassis dynamometer. This paper discusses challenges of linear MPC implementation related to nonlinearities in this over-actuated thermal system.

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.