Search Results

Gasoline compression ignition shows great potential in reducing NOx and soot emissions with competitive thermal efficiency by leveraging the properties of gasoline fuels and the high compression ratio of compression ignition engines operating air-dilute. Meanwhile, its control becomes challenging due to not only the properties of different gasoline-type fuels but also the impacts of injection strategies on the in-cylinder reactivity. As such, a computationally efficient zero-dimension combustion model can significantly reduce the cost of control development. In this study, a previously developed zero-dimension combustion model for gasoline compression ignition was extended to multiple gasoline-type fuel blends and a port fuel injection/direct fuel injection strategy. Tests were conducted on a 12.4-liter heavy-duty engine with five fuel blends.

Gasoline knock resistance is characterized by the Research and Motor Octane Number (RON and MON), which are rated on the CFR octane rating engine at naturally aspirated conditions. However, modern automotive downsized boosted spark ignition (SI) engines generally operate at higher cylinder pressures and lower temperatures relative to the RON and MON tests. Using the naturally aspirated RON and MON ratings, the octane index (OI) characterizes the knock resistance of gasolines under boosted operation by linearly extrapolating into boosted “beyond RON” conditions via RON, MON, and a linear regression K factor. Using OI solely based on naturally aspirated RON and MON tests to extrapolate into boosted conditions can lead to significant errors in predicting boosted knock resistance between gasolines due to non-linear changes in autoignition and knocking characteristics with increasing pressure conditions.

Gasoline compression ignition using a single gasoline-type fuel has been shown as a method to achieve low-temperature combustion with low engine-out NOx and soot emissions and high indicated thermal efficiency. However, key technical barriers to achieving low temperature combustion on multi-cylinder engines include the air handling system (limited amount of exhaust gas recirculation) as well as mechanical engine limitations (e.g. peak pressure rise rate). In light of these limitations, high temperature combustion with reduced amounts of exhaust gas recirculation appears more practical. Furthermore, for high temperature Gasoline compression ignition, an effective aftertreatment system allows high thermal efficiency with low tailpipe-out emissions. In this work, experimental testing was conducted on a 12.4 L multi-cylinder heavy-duty diesel engine operating with high temperature gasoline compression ignition combustion using EEE gasoline.

This paper describes a configuration and controller, designed using Autonomie,1 for dual-motor battery electric vehicle (BEV) heavy-duty trucks. Based on the literature and current market research, this model was designed with two electric motors, one on the front axle and the other on the rear axle. A rule-based control algorithm was designed for the new dual-motor BEV, based on the model, and the control parameters were optimized by using a genetic algorithm (GA). The model was simulated in diverse driving cycles and gradeability tests. The results show both a good following of the desired cycle and achievement of truck gradeability performance requirements. The simulation results were compared with those of a single-motor BEV and showed reduced energy consumption with the high-efficiency operation of the two motors.

Low-temperature heat release (LTHR) in spark-ignited internal combustion engines is a critical step toward the occurrence of auto-ignition, which can lead to an undesirable phenomenon known as engine knock. Hence, correct predictions of LTHR are of utmost importance to improve the understanding of knock and enable techniques aimed at controlling it. While LTHR is typically obscured by the deflagration following the spark ignition, extremely late ignition timings can lead to LTHR occurrence prior to the spark, i.e., pre-spark heat release (PSHR). In this research, PSHR in a boosted direct-injection SI engine was numerically investigated using three-dimensional computational fluid dynamics (CFD). A hybrid approach was used, based on the G-equation model for representing the turbulent flame front and the multi-zone well-stirred reactor model for tracking the chemical reactions within the unburnt region.

Gasoline compression ignition is a promising strategy to achieve high thermal efficiency and low emissions with limited modifications to the conventional diesel engine hardware. It is a partially premixed concept which derives its superiority from higher volatility and longer ignition delay of gasoline-like fuels combined with higher compression ratio typical of diesel engines. The present study investigates the combustion process in a gasoline compression ignition engine using computational fluid dynamics. Simulations are carried out on a single cylinder of a multi cylinder heavy-duty compression ignition engine which operates at a compression ratio of 17:1 and an engine speed of 1038 rev/min. In this study, a late fuel injection strategy is used because it is less sensitive to combustion kinetics compared to early injection strategies, which in turn is a better choice to assess the performance of the spray model.

Expanding upon the authors’ previous work which utilized a GT-Power model of the Cooperative Fuels Research (CFR) engine under Research Octane Number (RON) conditions, this work defines the boundary conditions of the CFR engine under Motored Octane Number (MON) test conditions. The GT-Power model was validated against experimental CFR engine data for primary reference fuel (PRF) blends between 60 and 100 under standard MON conditions, defining the full range of interest of MON for gasoline-type fuels. The CFR engine model utilizes a predictive turbulent flame propagation sub-model, and a chemical kinetic solver for the end-gas chemistry. The validation was performed simultaneously for thermodynamic and chemical kinetic parameters to match in-cylinder pressure conditions, burn rate, and knock point prediction with experimental data, requiring only minor modifications to the flame propagation model from previous model iterations.

In this last decade, non-destructive X-ray measurement techniques have provided unique insights into the internal surface and flow characteristics of automotive injectors. This has in turn contributed to enhancing the accuracy of Computational Fluid Dynamics (CFD) models of these critical injection system components. By employing realistic injector geometries in CFD simulations, designers and modelers have identified ways to modify the injectors’ design to improve their performance. In recent work, the authors investigated the occurrence of cavitation in a heavy-duty multi-hole diesel injector operating with a high-volatility gasoline-like fuel for gasoline compression ignition applications. They proposed a comprehensive numerical study in which the original diesel injector design would be modified with the goal of suppressing the in-nozzle cavitation that occurs when gasoline fuels are used.

Accurate modeling of the internal flow and spray characteristics in fuel injectors is a critical aspect of direct injection engine design. However, such high-fidelity computational fluid dynamics (CFD) models are often computationally expensive due to the requirement of resolving fine temporal and spatial scales. This paper addresses the computational bottleneck issue by proposing a machine learning-based emulator framework, which learns efficient surrogate models for spatiotemporal flow distributions relevant for static coupling injection maps, namely total void fraction, velocity, and mass, within a design space of interest. Different design points involving variations of needle lift, fuel viscosity, and level of non-condensable gas in the fuel were explored in this study. An interpretable Bayesian learning strategy was employed to understand the effect of the design parameters on the void fraction fields at the exit of the injector orifice.

An increase in spark-ignition engine efficiency can be gained by increasing the engine compression ratio, which requires fuels with higher knock resistance. Oxygenated fuel components, such as methanol, ethanol, isopropanol, or iso-butanol, all have a Research Octane Number (RON) higher than 100. The octane numbers (ON) of fuels are rated on the CFR F1/F2 engine by comparing the knock intensity of a sample fuel relative to that of bracketing primary reference fuels (PRF). The PRFs are a binary blend of iso-octane, which is defined to an ON of 100, and n-heptane, which represents an ON of 0. Above 100 ON, the PRF scale continues by adding diluted tetraethyl lead (TEL) to iso-octane. However, TEL is banned from use in commercial gasoline because of its toxicity. The ASTM octane number test methods have a “Fit for Use” test that validate the CFR engine’s compliance with the octane testing method by verifying the defined ON of toluene standardization fuels (TSF).

Multi-mode combustion strategies may provide a promising pathway to improve thermal efficiency in light-duty spark ignition (SI) engines by enabling switchable combustion modes, wherein an engine may operate under advanced compression ignition (ACI) at low load and spark-assisted ignition at high load. The extension from the SI mode to the ACI mode requires accurate control of intake charge conditions, e.g., pressure, temperature and equivalence ratio, in order to achieve stable combustion phasing and rapid mode-switches. This study presents results from computational fluid dynamics (CFD) analysis to gain insights into mixture charge formation and combustion dynamics pertaining to auto-ignition processes. The computational study begins with a discussion of thermal wall boundary condition that significantly impacts the combustion phasing.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

A 500-hour test cycle has been used to evaluate the durability of a prototype high pressure common rail injection system operating up to 1800 bar with E10 gasoline. Some aspects of the original diesel based hardware design were optimized in order to accommodate an opposed-piston, two-stroke engine application and also to mitigate the impacts of exposure to gasoline. Overall system performance was maintained throughout testing as fueling rate and rail pressure targets were continuously achieved and no physical damage was observed in the low-pressure components. Injectors showed no deviation in their flow characteristics after exposure to gasoline and high resolution imaging of the nozzle spray holes and pilot valve assemblies did not indicate the presence of cavitation damage. The high pressure pump did not exhibit any performance degradation during gasoline testing and teardown analysis after 500 hours showed no evidence of cavitation erosion.

An accurate prediction of internal nozzle flow in fuel injector offers the potential to improve predictions of spray computational fluid dynamics (CFD) in an engine, providing a coupled internal-external calculation or by defining better rate of injection (ROI) profile and spray angle information for Lagrangian parcel computations. Previous research has addressed experiments and computations in transparent nozzles, but less is known about realistic multi-hole diesel injectors compared to single axial-hole fuel injectors. In this study, the transient injector opening and closing is characterized using a transparent multi-hole diesel injector, and compared to that of a single axial hole nozzle (ECN Spray D shape). A real-size five-hole acrylic transparent nozzle was mounted in a high-pressure, constant-flow chamber. Internal nozzle phenomena such as cavitation and gas exchange were visualized by high-speed long-distance microscopy.

The modeling of fuel jet atomization is key in the characterization of Internal Combustion (IC) engines, and 3D Computational Fluid Dynamics (CFD) is a recognized tool to provide insights for design and control purposes. Multi-hole injectors with counter-bored nozzle are the standard for Gasoline Direct Injection (GDI) applications and the Spray-G injector from the Engine Combustion Network (ECN) is considered the reference for numerical studies, thanks to the availability of extensive experimental data. In this work, the behavior of the Spray-G injector is simulated in a constant volume chamber, ranging from sub-cooled (nominal G) to flashing conditions (G2), validating the models on Diffused Back Illumination and Phase Doppler Anemometry data collected in vaporizing inert conditions.

This paper presents a computational fluid dynamics (CFD) study of the Engine Combustion Network (ECN) Spray G under non-vaporizing condition, focusing on the impacts of fuel properties as well as realistic geometry on the atomization process. The large-eddy-simulation method, coupled with the volume-of-fluid method, is used to model the high-speed turbulent two-phase flow. A moving-needle boundary condition is applied to capture the internal flow boundary condition accurately. The injector geometry was measured with micron-level resolution using x-ray tomographic imaging at the Advanced Photon Source at Argonne National Laboratory, providing detailed machining tolerance and defects from manufacturing and a realistic rough surface. A 2.5-μm fine mesh is used to sufficiently resolve the details of liquid-gas interface and the breakup process.

Advanced compression ignition (ACI) operation in gasoline direct injection (GDI) engines is a promising concept to reduce fuel consumption and emissions at part load conditions. However, combustion phasing control and the limited operating range in ACI mode are a perennial challenge. In this study the combined impact of fuel properties and engine control strategies in ACI operation are investigated. A design of experiments method was implemented using a three level orthogonal array to determine the sensitivity of engine control parameters on the engine load, combustion noise and stability under low load ACI operation for three RON 98 gasoline fuels, each exhibiting disparate chemical composition. Furthermore, the thermodynamic state of the compression histories was studied with the aid of the pressure-temperature framework.

A zero-dimensional heat release model was developed for compression ignition engines. This type of model can be utilized for parametric studies, off-line optimization to reduce experimental efforts as well as model-based control strategies. In this particular case, the combustion model, in a simpler form, will be used in future efforts to control the combustion in compression ignition engines operating on gasoline-like fuels. To allow for a realistic representation of the in-cylinder combustion process, a spray model has been employed to allow for the quantification of fuel distribution as well as turbulent kinetic energy within the injection spray. The combustion model framework is capable of reflecting premixed as well as mixing controlled combustion. Fuel is assigned to various combustion events based on the air-fuel mixture within the spray.

As emerging automated vehicle technology is making advances in safety and reliability, engineers are also exploring improvements in energy efficiency with this new paradigm. Powertrain efficiency receives due attention, but also impactful is finding ways to reduce driving losses in coordinated-driving scenarios. Efforts focused on simulation to quantify road load improvements require a sufficient amount of background validation work to support them. This study uses a practical approach to directly quantify road load changes by testing the coordinated driving of two vehicles on a test track at various speeds (64, 88, 113 km/h) and vehicle time gaps (0.3 to 1.3 s). Axle torque sensors were used to directly measure the load required to maintain steady-state speeds while following a lead vehicle at various gap distances.

Currently there is a significant research effort being made in gasoline spark/ignition (SI) engines to understand and reduce cycle-to-cycle variations. One of the phenomena that presents this cycle-to-cycle variation is combustion knock, which also happens to have a very stochastic behavior in modern SI engines. Conversely, the CFR octane rating engine presents much more repeatable combustion knock activity. The aim of this study is to assess the impact of fuel composition on the cycle to cycle variation of the pressure and timing of end gas autoignition. The variation of cylinder conditions at the timing of end-gas autoignition (knock point) for a wide selection of cycle ensembles have been analyzed for several constant RON 98 fuels on the CFR engine, as well as in a modern single-cylinder gasoline direct injection (GDI) SI engine operated at RON-like intake conditions.