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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.

To improve the maneuverability and energy consumption of an electrical vehicle, a two-level speed control method based on model predictive control (MPC) is proposed for accurate control of the vehicle during downhill coasting. The targeted acceleration is planned using the anti-interference speed filter and MPC algorithm in the upper-level controller and executed using the integrated algorithm with the inverse vehicle dynamics and proportional-integral-derivative control model (PID) in the lower-level controller, improving the algorithm’s anti-interference performance and road adaptability. Simulations and vehicle road tests showed that the proposed method could realize accurate real-time speed control of the vehicle during downhill coasting. It can also achieve a smaller derivation between the actual and targeted speeds, as well as more stable speeds when the road resistance changes abruptly, compared with the conventional PID method.

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.

G-Equation models represent propagating flame fronts with an implicit two-dimensional surface representation (level-set). Level-set methods are fast, as transport source terms for the implicit surface can be solved with finite-volume operators on the finite-volume domain, without having to build the actual surface. However, they include approximations whose practical effects are not properly understood. In this study, we improved the numerics of the FRESCO CFD code’s G-Equation solver and developed a new method to simulate kernel growth using signed distance functions and the analytical sphere-mesh overlap. We analyzed their role for simulating propane/air flames, using three well-established constant-volume configurations: a one-dimensional, freely propagating laminar flame; a disc-shaped, constant-volume swirl combustor; and torch-jet flame development through an orifice from a two-chamber device.

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.

This work explores the effect of the particle matter index (PMI) and aromatic content on fuel wall impingement associated with stochastic pre-ignition (SPI). Statically significant measurements of SPI rates are directly coupled with laser induced florescence (LIF) measurements of fuel dilution from spray-linear impingement. Literature suggests that PMI is could be correlated with the number of SPI events, but the root cause(s) of PMI and SPI are directly causational or are a predicator of SPI. Three fuels have been used in this study with 3 different PMI and two different aromatic contents. The fuels are direct injected at two different injection timings, an earlier injection timing which initially targets the piston crown, 310°CA bTDC, and a later injection timing that the liner, 220°CA bTDC start of injection timings (SOI) respectively. The earlier 310 SOI injection increases soot, whereas the later 220°CA SOI targets the liner and increases wall-wetting.

This work employs a novel laser induced fluorescence (LIF) diagnostic to measure fuel dilution in a running single cylinder research engine operated at stochastic pre ignition (SPI) and non-SPI prone conditions. Measurements of LIF based fuel dilution are quantified over a range of engine loads and fuel injection timings for two fuels. The in situ LIF measurements of fuel/lubricant interactions illustrate regions of increased fuel dilution from fuel-wall interactions and is believed to be a fundamental underpinning to generating top ring zone liquid conditions conducive to SPI. A novel level of dye doped in the fuel, between 50 to 500 ppm was used as the fluorescence source, at engine operating speed of 2000r/min from 5 to 18 bar of IMEPg injection timings was swept for two fuels of varying volatility.

Modern spark ignition internal combustion engines rely on fast combustion rates and high dilution to achieve high brake thermal efficiencies. To accomplish this, new engine designs have moved towards increased tumble ratios and stroke-to-bore ratios. Increased tumble ratios correlate positively with increases in turbulent kinetic energy and improved fuel and residual gas mixing, all of which favor faster and more efficient combustion. Longer stroke-to-bore ratios allow higher geometric compression ratios and use of late intake valve closing to control peak compression pressures and temperatures. The addition of dilution to improve efficiency is limited by the resulting increase in combustion instabilities manifested by cycle-to-cycle variability.

A new analytical method to aid in the understanding of the organic carbon (OC) phase of particulate matter (PM) from advanced compression ignition (ACI) operating modes, is presented. The presence of NO2 and unburned fuel aromatics in ACI emissions, and the low exhaust temperatures that result from this low temperature combustion strategy, provide the right conditions for the formation of carboxylic acids and nitroaromatic compounds. These polar compounds contribute to OC in the PM and are not typically measured using nonpolar solvent extraction methods such as the soluble organic fraction (SOF) method. The new extraction and detection method employs capillary electrophoresis with electrospray ionization mass spectrometry (CE-ESI MS) and was specifically developed to determine polar organic compounds in the ACI PM emissions. The new method identified both nitrophenols and aromatic carboxylic acids in the ACI PM.

This work explores pathways to achieve diesel-like, high-efficiency combustion with stoichiometric 3-way catalyst compatible spark ignition (SI). A high stroke-to-bore engine design (1.5:1) with cooled exhaust gas recirculation (EGR) and high compression ratio (rc) was used to improve engine efficiency by up to 30% compared with a production turbocharged gasoline direct injection spark ignition engine. To achieve efficiency improvements, engine experiments were coupled with computational fluid dynamics simulations to guide and explain experimental trends between the original engine and the high stroke-to-bore ratio design (1.5:1). The effects of EGR and late intake valve closing (IVC) and fuel characteristics are investigated through their effects on knock mitigation. Direct injection of 91 RON E10 gasoline, 99 RON E0 gasoline, and liquified petroleum gas (i.e., propane/autogas) were evaluated with geometric rc ranging from 13.3:1 to 16.8:1.

Low temperature combustion (LTC) strategies present a means of reducing soot and oxides of nitrogen (NOx) emissions while simultaneously increasing efficiency relative to conventional combustion modes. By sufficiently premixing fuel and air before combustion, LTC strategies avoid high fuel-to-air equivalence ratios that lead to soot production. Dilution of the mixture lowers the combustion temperatures to reduce NOx production and offers thermodynamic advantages for improved efficiency. However, issues such as high heat release rates (HRRs), incomplete combustion, and difficulty in controlling the timing of combustion arise with low equivalence ratios and combustion temperatures. Ignition delay (the time until the start of combustion) is a way to quantify the time available for fuel and air to mix inside the cylinder before combustion. Previous studies have used ignition delay to explain trends seen in LTC such as combustion stability and HRRs.

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.

Rapid vehicle powertrain development has become a technological breakthrough for the design and implementation of vehicles that meet and exceed the fuel efficiency, cost, and performance targets expected by today’s consumer. Recently, advances in large scale additive manufacturing have provided the means to bridge hardware-in-the-loop with preproduction mule chassis testing. This paper details a case study from Oak Ridge National Laboratory bridging the powertrain-in-the-loop development process with vehicle systems implementation using big area additive manufacturing (BAAM). For this case study, the use of a component-in-the-loop laboratory with math-based models is detailed for the design of a battery electric powertrain to be implemented in a printed prototype mule. The ability for BAAM to accelerate the mule development process via the concept of computer-aided design to part is explored.

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.

Reactivity Controlled Compression Ignition (RCCI) has been shown to be an attractive concept to achieve clean and high efficiency combustion. RCCI can be realized by applying two fuels with different reactivities, e.g., diesel and gasoline. This motivates the idea of using a single low reactivity fuel and direct injection (DI) of the same fuel blended with a small amount of cetane improver to achieve RCCI combustion. In the current study, numerical investigation was conducted to simulate RCCI and HCCI combustion and emissions with various fuels, including gasoline/diesel, iso-butanol/diesel and iso-butanol/iso-butanol+di-tert-butyl peroxide (DTBP) cetane improver. A reduced Primary Reference Fuel (PRF)-iso-butanol-DTBP mechanism was formulated and coupled with the KIVA computational fluid dynamic (CFD) code to predict the combustion and emissions of these fuels under different operating conditions in a heavy duty diesel engine.