Search Results

Internal combustion engines are becoming ever more efficient as mankind seeks to mitigate the effects of climate change while still maintaining the benefits that a mechanized society has brought to the global economy. As peak values, mass production spark-ignition engines can now achieve approximately 40% brake thermal efficiency and heavy-duty truck compression-ignition engines can approach 50%. While commendable, the unfortunate truth is that the remainder gets emitted as waste heat and is sent to the atmosphere to no useful purpose. Clearly, if one could recover some of this waste heat for beneficial use then this is likely to become important as new means of mitigating fossil CO2 emissions are demanded. A previous study by the authors has identified that the closed Joule cycle (or complications of it beginning to approximate the closed Ericsson cycle) could reasonably be developed to provide a practical means of recovering exhaust heat when applied to a large ship engine.

1Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure.

This work for the Coordinating Research Council (CRC) explores dependencies on the opportunity for fuel to impinge on internal engine surfaces (i.e., fuel–wall impingement) as a function of fuel properties and engine operating conditions and correlates these data with measurements of stochastic preignition (SPI) propensity. SPI rates are directly coupled with laser–induced florescence measurements of dye-doped fuel dilution measurements of the engine lubricant, which provides a surrogate for fuel–wall impingement. Literature suggests that SPI may have several dependencies, one being fuel–wall impingement. However, it remains unknown if fuel-wall impingement is a fundamental predictor and source of SPI or is simply a causational factor of SPI. In this study, these relationships on SPI and fuel-wall impingement are explored using 4 fuels at 8 operating conditions per fuel, for 32 total test points.

Ammonia as a fuel suffers from a high ignition energy requirement making it hard to ignite in stoichiometric mixtures, especially with normal spark plugs. On the other hand, pre-chambers are proven to provide high ignition energy by producing multiple ignition spots in the main chamber. A pre-chamber is usually categorized as “active” if it has a dedicated fueling system, and as “passive” if it depends solely on the air- fuel mixture being introduced from the main chamber and is therefore simpler than the active type. In this study, an SI light-duty engine was tested with a conventional spark plug with fuel mixtures of gasoline and gaseous ammonia (0%, 25%, 50%, 75%, 90%, and 100% NH3). The test was then repeated with a passive pre-chamber under the same operating conditions for comparison. Moreover, the engine exhaust was fitted with a fast response analyzer to measure NOX. The use of the conventional spark plug showed stable combustion throughout the fuel mixture sweep.

With increasingly stringent regulations mandating the improvement of vehicle fuel economy, automotive manufacturers face growing pressure to develop and implement technologies that improve overall system efficiency. One such technology is an automatic (auto) stop-start feature. Auto stop-start reduces idle time and reduces fuel use by temporarily shutting the engine off when the vehicle comes to a stop and automatically re-starting it when the brake is released, or the accelerator is pressed. As mandated by the U.S. Congress, the U.S. Environmental Protection Agency (EPA) is required to keep the public informed about fuel saving practices. This is done, in partnership with the U.S. Department of Energy (DOE), through the fueleconomy.gov website. The “Fuel-Saving Technologies” and “Gas Mileage Tips” sections of the website are focused on helping the public make informed purchasing decisions and encouraging fuel-saving driving habits.

The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This paper develops a long-term plan for refueling infrastructure deployment using the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy duty (HD) fuel cell electric commercial vehicles (FCEV).

To achieve carbon neutrality by 2060, the Chinese government has put effort into decarbonizing the transportation sector. Consequently, China elaborated a new energy vehicle strategy promoting the production of electric vehicles and expanding into hydrogen (H2) vehicle technologies including fuel cell electric vehicles and H2 internal combustion engine vehicles. The Transportation Energy Analysis Model (TEAM) projects the market penetration as well as energy demand and greenhouse gas emissions in China up to 2050. By integrating the Monte Carlo simulation, this study tests the robustness of TEAM and investigates the key parameters that will shape passenger vehicle sales and emissions in the future. The results show that fuel cell cost, H2 price, and battery cost are the most sensitive parameters for H2 vehicle technologies.

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025).

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.

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance.

With ever stricter legislative requirements for CO2 and other exhaust emissions, significant efforts by OEMs have launched a number of different technological strategies to meet these challenges such as Battery Electric Vehicles (BEVs). However, a multiple technology approach is needed to deliver a broad portfolio of products as battery costs and supply constraints are considerable concerns hindering mass uptake of BEVs. Therefore, further investment in Internal Combustion (IC) engine technologies to meet these targets are being considered, such as lean burn gasoline technologies alongside other high efficiency concepts such as dedicated hybrid engines. Hence, it becomes of sound reason to further embrace diversity and develop complementary technologies to assist in the transition to the next generation hybrid powertrain. One such approach is to provide increased valvetrain flexibility to afford new degrees of freedom in engine operating strategies.

Compared to conventional diesel combustion (CDC), isobaric combustion can achieve higher thermal efficiency while lowering heat transfer losses and nitrogen oxides (NOx). However, isobaric combustion suffers from higher soot emissions. While the aforementioned trends are well established, there is limited literature about the high-temperature reaction zones, the liquid-phase penetration distance, and the flame tip propagation velocity of isobaric combustion. In the present study, the line-of-sight integrated imaging of Mie-scattering, combustion luminosity, and CH* chemiluminescence were conducted in an optically accessible single-cylinder heavy-duty diesel engine. The engine was equipped with a flat-bowl-shaped optical piston to allow bottom-view imaging of the combustion chamber. The experiments were conducted using n-heptane fuel for CDC and isobaric combustion modes.

Investigating combustion characteristics of oxygenated gasoline and gasoline blended ethanol is a subject of recent interest. The non-linearity in the interaction of fuel components in the oxygenated gasoline can be studied by developing chemical kinetics of relevant surrogate of fewer components. This work proposes a new reduced four-component (isooctane, heptane, toluene, and ethanol) oxygenated gasoline surrogate mechanism consisting of 67 species and 325 reactions, applicable for dynamic CFD applications in engine combustion and sprays. The model introduces the addition of eight C1-C3 species into the previous model (Li et al; 2019) followed by extensive tuning of reaction rate constants of C7 - C8 chemistry. The current mechanism delivers excellent prediction capabilities in comprehensive combustion applications with an improved performance in lean conditions.

To elucidate the complex characteristics of pre-chamber combustion engines, the interaction of the hot gas jets initiated by an active narrow throated pre-chamber with lean premixed CH4/air in a heavy-duty engine was studied computationally. A twelve-hole KAUST proprietary pre-chamber geometry was investigated using CONVERGE software. The KAUST pre-chamber has an upper conical part with the spark plug, and fuel injector, followed by a straight narrow region called the throat and nozzles connecting the chambers. The simulations were run for an entire cycle, starting at the previous cycle's exhaust valve opening (EVO). The SAGE combustion model was used with the chemistry modeled using a reduced methane oxidation mechanism based on GRI Mech 3.0, which was validated against in-house OH chemiluminescence data from the optical engine experiments.

Pre-chamber combustion (PCC) has re-emerged in recent last years as a potential solution to help to decarbonize the transport sector with its improved engine efficiency as well as providing lower emissions. Research into the combustion process inside the pre-chamber is still a challenge due to the high pressure and temperatures, the geometrical restrictions, and the short combustion durations. Some fundamental studies in constant volume combustion chambers (CVCC) at low and medium working pressures have shown the complexity of the process and the influence of high pressures on the turbulence levels. In this study, the pre-chamber combustion process was investigated by combustion visualization in an optically-accessible pre-chamber under engine relevant conditions and linked with the jet emergence inside the main chamber. The pre-chamber geometry has a narrow-throat. The total nozzle area is distributed in two six-hole rows of nozzle holes.

Downsized turbocharged engines have been increasingly popular in modern light-duty vehicles due to their fuel efficiency benefits. However, high power density in such engines is achieved thanks to high in-cylinder pressure and temperature conditions that increase knock propensity. Next-cycle control has been studied as a method to reduce the damaging effects of knock by operating the engine in a low knock probability condition. This exploratory study looks at the feasibility of in-cycle knock prediction as a tool for advanced knock control algorithms. A methodology is proposed to 1) choose in-cycle features of the pressure trace that highly correlate with knock events and 2) train artificial neural networks to predict in-cycle knock events before knock onset. The methodology was validated at different operating conditions and different levels of generalization. Precision and recall were used as metrics to evaluate the binary classifier.

In this study the volume and hardness were measured for thermoplastics and thermosetting resins with diesel containing up to 30% of the following blend stocks: biodiesel, renewable diesel, n-undecane, dibutoxymethane, 1-octanol, hexyl hexanoate, and 2-nonanone. Thermoplastics included polyphenylene sulfide (PPS), polyethylene terephthalate (PET), polytetrafluoroethylene (PTFE), polyvinylidene fluoride (PVDF), polyoxymethylene (POM), polybutylene terephthalate (PBT), polypropylene (PP), high density polyethylene (HDPE), nylons, acetals, polyetherimide (PEI), polyetheretherketone (PEEK), a PET co-polymer, polyphthalamides (PPAs), polyarylamide (PARA) and ethylene tetrafluoroethylene (ETFE). Three thermosetting resins were also evaluated. The material specimens were exposed to the test fuels under ambient conditions for 16 weeks.

In spark-ignition combustion, knocking combustion inherently presents an interaction between the main flame front and end gas autoignition. Conventionally, it generates a high amplitude pressure wave traveling across the chamber that can be responsible for reducing the performance of the engine, and can cause heavy damage to engine components. In order to study the phenomenon in a controllable way, experiments were performed on a specialized single-cylinder research engine fitted with a liner equipped with four equi-spaced spark plugs in the side so as to propagate various flame topologies from those locations, and hence achieve more controlled knock events. In addition, six pressure transducers were employed at distinct locations to precisely record details of the autoignition event by monitoring the pressure oscillations, and with them the combustion characteristics and knock intensity.

Prior research studies have investigated a wide variety of gasoline compression ignition (GCI) injection strategies and the resulting fuel stratification levels to maintain control over the combustion phasing, duration, and heat release rate. Previous GCI research at the US Department of Energy’s Oak Ridge National Laboratory has shown that for a combustion mode with a low degree of fuel stratification, called “partial fuel stratification” (PFS), gasoline range fuels with anti-knock index values in the range of regular-grade gasoline (~87 anti-knock index or higher) provides very little controllability over the timing of combustion without significant boost pressures. On the contrary, heavy fuel stratification (HFS) provides control over combustion phasing but has challenges achieving low temperature combustion operation, which has the benefits of low NOX and soot emissions, because of the air handling burdens associated with the required high exhaust gas recirculation rates.

In order to maximize the efficiency of light-duty gasoline engines, the Co-Optimization of Fuels and Engines (Co-Optima) initiative from the U.S. Department of Energy is investigating multi-mode combustion strategies. Multi-mode combustion can be describe as using conventional spark-ignited combustion at high loads, and at the part-load operating conditions, various advanced compression ignition (ACI) strategies are being investigated to increase efficiency. Of particular interest to the Co-Optima initiative is the extent to which optimal fuel properties and compositions can enable higher efficiency ACI combustion over larger portions of the operating map. Extending the speed-load range of these ACI modes can enable greater part-load efficiency improvements for multi-mode combustion strategies.