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Hydrogen internal combustion engine is considered to be one of the promising ways to achieve zero-carbon emissions in the automotive industry. However, the problem of high NOx emissions from hydrogen engines needs to be addressed. Although homogeneous lean-mixture combustion could reduce engine-out NOx emissions, it is necessary to ensure mixing homogeneity to avoid excessive NOx formation from the rich mixture packets. In this study, large-eddy simulations (LES) of a direct-injection hydrogen engine were carried out to assess the hydrogen-air mixing process in forming homogeneous charges with consideration of cyclic variations. The high-speed hydrogen jet flow was modeled in a constant-volume vessel first to verify the LES model. Engine simulations were then performed to study the effects of the injector location (side vs. central), injection pressure, and injector type (pintle vs. outward opening) on the mixing process, mixture homogeneity, and cyclic variations.

The possibility to operate current diesel engines in dual-fuel mode with the addition of an alternative fuel is fundamental to accelerate the energy transition to achieve carbon neutrality. The simulation of the dual- fuel combustion process with 0D/1D combustion models is fundamental for the performance prediction, but still particularly challenging, due to chemical interactions of the mixture. The authors defined a novel data-driven workflow for the development of combustion reaction mechanisms and used it to generate a dual-fuel mechanism for Ammonia and Diesel Primary Reference Fuels (DPRF) suitable for efficient combustion simulations in heavy duty engines, with variable cetane number Diesel fuels. A baseline reaction mechanism was created by merging the detailed ammonia mechanism by Glarborg et al. with reaction pathways for n- hexadecane and 2,2,4,4,6,8,8-heptamethylnonane from a well-established multi-component fuel mechanism.

We propose a novel dual-fuel combustion model for simulating heavy-duty engines with the G-Equation. Dual-Fuel combustion strategies in such engines features direct injection of a high-reactivity fuel into a lean, premixed chamber which has a high resistance to autoignition. Distinct combustion modes are present: the DI fuel auto-ignites following chemical ignition delay after spray vaporization and mixing; a reactive front is formed on its surroundings; it develops into a well-structured turbulent flame, which propagates within the premixed charge. Either direct chemistry or the flame-propagation approach (G- Equation), taken alone, do not produce accurate results. The proposed Dual-Fuel model decides what regions of the combustion chamber should be simulated with either approach, according to the local flame state; and acts as a “kernel” model for the G- Equation model. Direct chemistry is run in the regions where a premixed front is not present.

The fuel-saving potential of a series hybrid electric vehicle (SHEV) was investigated in this work based on the future goals and technical roadmaps proposed by China's automobile and internal combustion engine (ICE) industry. The genetic algorithm optimization method and dynamic programming energy management strategy are used to optimize the key component parameters of a typical SHEV SUV to improve the fuel economy of the vehicle. Results showed that the fuel consumption of the vehicle would be 3.24 L / 100km in 2035, which is 37.21% less than 5.16 L / 100km in 2020, following the industries’ roadmaps. The results also indicated that the improvement of the ICE’s thermal efficiency is the main reason for the decrease of the vehicle’s fuel consumption. In addition, the improvement of working points and the reduction of energy losses of the key components also contribute to the improvement of the fuel economy.

The driving conditions of commercial logistics vehicles have the characteristics of combined urban and suburban roads with relatively fixed mileage and cargo load alteration, which affect the vehicular fuel economy. To this end, an adaptive equivalent consumption minimization strategy (A-ECMS) with vehicle speed and weight recognition is proposed to improve the fuel economy for a range-extender electric van for logistics in this work. The driving conditions are divided into nine representative groups with different vehicle speed and weight statuses, and the driving patterns are recognized with the use of the bagged trees algorithm through vehicle simulations. In order to generate the reference SOC near the optimal values, the optimal SOC trajectories under the typical driving cycles with different loads are solved by the shooting method and the optimal slopes for these nine patterns are obtained.

Numerical analysis of thermal efficiency improvement up to 45% of an 1.8-liter turbocharged direct-injection (DI) gasoline engine was conducted in this study in response to the need of improving vehicle fuel economy. 1D thermodynamics simulations and 3D computational fluid dynamics (CFD) modeling were carried out to investigate the technical approaches for improving engine thermal efficiency. Effects of various technologies on the improvement in the engine performance were evaluated, and then the technical routes to achieve 41% and 45% brake thermal efficiency were summarized, respectively. It is concluded that 41% thermal efficiency can be reached under stoichiometric combustion conditions, while it is expected lean burn technology is needed for the target of 45% thermal efficiency. The effects of high tumble intake flow on accelerating burning speed and of high compression ratio on intensifying knocking were analyzed.

Knocking combustion limits the application of high compression ratios in gasoline engines and therefore obstructs the improvement of thermal efficiency. Predicting knock and knock limited spark advance (KLSA) can guide engine upfront design and optimization before the prototype is built. This study employed three-dimensional computational fluid dynamics (CFD) simulations coupled with an accurate and computation-efficient knock model to predict the KLSA of a turbocharged direct-injection spark-ignition engine. The knock model predicted the end-gas auto-ignition based on a Livengood-Wu (L-W) integral transport equation instead of directly using detailed chemical mechanisms, which was able to achieve a fast computation time. To keep the predictability, ignition delay data was calculated using zero-dimensional chemistry simulation and tabulated a priori, which was then used for CFD simulation on the fly.

In this work, the influences of various real-timely available energy management strategies on vehicle fuel consumption (VFC) and energy flow of a range-extender electric vehicle were studied The strategies include single-point, multi-point, speed-following, and equivalent consumption minimization strategy. In addition, the dynamic programming method which cannot be used in real time, but can provide the optimal solution for a known drive situation was used for comparison. VFCs and energy flow characteristics with different strategies under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) were obtained through computer modeling, and the results were verified experimentally on a range-extender test bench. The experimental results are consistent with the modeled ones in general with a maximum deviation of 4.11%, which verifies the accuracy of the simulation models.

Studies were carried out for improvement of combustion performance of an 1.2 L dedicated range-extender gasoline engine which uses a high compression ratio, cooled exhaust-gas-recirculation (EGR) and Atkinson cycle. The intake-charging characteristics were investigated both computationally and experimentally in order to compensate the torque reduction mainly due to the charge pushback in the Atkinson cycle. The design parameters of the intake manifold were refined to increase the intake air charges. 1D simulations were carried out to investigate the effect of the runner lengths and diameters. The results indicated that the increased length and reduced diameter could improve the volumetric efficiency in the most used engine speed range. Furthermore, computational fluid dynamics (CFD) simulations were employed to evaluate the cylinder-to-cylinder charging variations of the proposed manifold and reduced variations were obtained.

Simulation and Optimization of Internal Combustion Engines provides the fundamentals and up-to-date progress in multidimensional simulation and optimization of internal combustion engines. While it is impossible to include all the models in a single book, this book intends to introduce the pioneer and/or the often-used models and the physics behind them providing readers with ready-to-use knowledge. Key issues, useful modeling methodology and techniques, as well as instructive results, are discussed through examples. Readers will understand the fundamentals of these examples and be inspired to explore new ideas and means for better solutions in their studies and work. Topics include combustion basis of IC engines, mathematical descriptions of reactive flow with sprays, engine in-cylinder turbulence, fuel sprays, combustions and pollutant emissions, optimization of direct-injection gasoline engines, and optimization of diesel and alternative fuel engines.

A new range-extension hybrid powertrain concept, namely the Tongji Extended-range Hybrid Technology (TJEHT) was developed and demonstrated in this study. This hybrid system is composed of a direct-injection gasoline engine, a traction motor, an Integrated Starter-Generator (ISG) motor, and a transmission. In addition, an electronically controlled clutch between the ISG motor and engine, and an electronically controlled synchronizer between the ISG motor and transmission are also employed in the transmission case. Hence, this system can provide six basic operating modes including the single-motor driving, dual-motor driving, serial driving, parallel driving, engine-only driving and regeneration mode depending on the engagement status of the clutch and synchronizer. Importantly, the unique dual-motor operation mode can improve vehicle acceleration performance and the overall operating efficiency.

The variability in gasoline energy content, though most frequently not a consumer concern, is an issue of concern for vehicle manufacturers in demonstrating compliance with regulatory requirements. Advancements in both vehicle technology, test methodology, and fuel formulations have increased the level of visibility and concern with regard to the energy content of fuels used for regulatory testing. The R factor was introduced into fuel economy calculations for vehicle certification in the late 1980s as a means of addressing batch-to-batch variations in the heating value of certification fuels and the resulting variations in fuel economy results. Although previous studies have investigated values of the R factor for modern vehicles through experimentation, subsequent engine studies have made clear that it is difficult to distinguish between the confounding factors that influence engine efficiency when R is being studied experimentally.

Six blendstocks identified by the Co-Optimization of Fuels & Engines Program were used to prepare fuel blends using a fixed blendstock for oxygenate blending and a target RON of 97. The blendstocks included ethanol, n-propanol, isopropanol, isobutanol, diisobutylene, and a bioreformate surrogate. The blends were analyzed and used to establish interaction factors for a non-linear molar blending model that was used to predict RON and MON of volumetric blends of the blendstocks up to 35 vol%. Projections of efficiency increase, volumetric fuel economy increase, and tailpipe CO2 emissions decrease were produced using two different estimation techniques to evaluate the potential benefits of the blendstocks. Ethanol was projected to provide the greatest benefits in efficiency and tailpipe CO2 emissions, but at intermediate levels of volumetric fuel economy increase over a smaller range of blends than other blendstocks.

Natural gas is a promising alternative fuel for internal combustion engines due to its rich reserves and low price, as well as good physical and chemical properties. Its low carbon structure and high octane number are beneficial for CO2 reduction and knock mitigation, respectively. Diesel and natural gas dual fuel combustion is a viable pathway to utilize natural gas in diesel engines. To achieve high efficiency and low emission combustion in a practical diesel engine over a wide range of operating conditions, understanding the performance responses to engine system parameter variations is needed. The controllability of two combustion strategies, diesel pilot ignition (DPI) and single injection reactivity controlled compression ignition (RCCI), were evaluated using the multi-dimension CFD simulation in this paper.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

The latent heat-of-vaporization (HoV) of blends of biofuel and hydrocarbon components into gasolines has recently experienced expanded interest because of the potential for increased HoV to increase fuel knock resistance in direct-injection (DI) engines. Several studies have been conducted, with some studies identifying an additional anti-knock benefit from HoV and others failing to arrive at the same conclusion. Consideration of these studies holistically shows that they can be grouped according to the level of fuel octane sensitivity variation within their fuel matrices. When comparing fuels of different octane sensitivity significant additional anti-knock benefits associated with HoV are sometimes observed. Studies that fix the octane sensitivity find that HoV does not produce additional anti-knock benefit. New studies were performed at ORNL and NREL to further investigate the relationship between HoV and octane sensitivity.

New regulations requiring increases in vehicle fuel economy are challenging automotive manufacturers to identify fuel-efficient engines for future vehicles. Lean gasoline direct injection (GDI) engines offer significant increases in fuel efficiency over the more common stoichiometric GDI engines already in the marketplace. However, particulate matter (PM) emissions from lean GDI engines, particularly during stratified combustion modes, are problematic for lean GDI technology to meet U.S. Environmental Protection Agency Tier 3 and other future emission regulations. As such, the control of lean GDI PM with wall-flow filters, referred to as gasoline particulate filter (GPF) technology, is of interest. Since lean GDI PM chemistry and morphology differ from diesel PM (where more filtration experience exists), the functionality of GPFs needs to be studied to determine the operating conditions suitable for efficient PM removal.

The recirculation of gases from the crankcase and valvetrain can potentially lead to the entrainment of lubricant in the form of aerosols or mists. As boost pressures increase, the blow-by flow through both the crankcase and the valve cover increases. The resulting lubricant can then become part of the intake charge, potentially leading to fouling of intake components such as the intercooler and the turbocharger. The entrained aerosol which can contain the lubricant and soot may or may not have the same composition as the bulk lubricant. The complex aerodynamic processes that lead to entrainment can strip out heavy components or volatilize light components. Similarly, the physical size and numbers of aerosol particles can be dependent upon the lubricant formulation and engine speed and load. For instance, high rpm and load may increase not only the flow of gases but the amount of lubricant aerosol.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

Due to the new challenge of meeting number-based regulations for particulate matter (PM), a numerical and experimental study has been conducted to better understand particulate formation in engines fuelled with compressed natural gas. The study has been conducted on a Heavy-Duty, Euro VI, 4-cylinder, spark ignited engine, with multipoint sequential phased injection and stoichiometric combustion. For the experimental measurements two different instruments were used: a condensation particle counter (CPC) and a fast-response particle size spectrometer (DMS) the latter able also to provide a particle size distribution of the measured particles in the range from 5 to 1000 nm. Experimental measurements in both stationary and transient conditions were carried out. The data using the World Harmonized Transient Cycle (WHTC) were useful to detect which operating conditions lead to high numbers of particles. Then a further transient test was used for a more detailed and deeper analysis.