Fueled Spark Ignition Engine Research Articles

Experimental Study on the Effect of Ammonia on Combustion and Emission Characteristics of a Spark Ignition Engine Fueled with Hydrogen

Experimental Study on the Effect of Ammonia on Combustion and Emission Characteristics of a Spark Ignition Engine Fueled with Hydrogen

Exergy Analysis in Highly Hydrogen-Enriched Methane Fueled Spark-Ignition Engine at Diverse Equivalence Ratios via Two-Zone Quasi-Dimensional Modeling

In the endeavor to accomplish a fully de-carbonized globe, sparkling interest is growing towards using natural gas (NG) having as vastly major component methane (CH4). This has the lowest carbon/hydrogen atom ratio compared to other conventional fossil fuels used in engines and power-plants hence mitigating carbon dioxide (CO2) emissions. Given that using neat hydrogen (H2) containing nil carbon still possesses several issues, blending CH4 with H2 constitutes a stepping-stone towards the ultimate goal of zero producing CO2. In this context, the current work investigates the exergy terms development in high-speed spark-ignition engine (SI) fueled with various hydrogen/methane blends from neat CH4 to 50% vol. fraction H2, at equivalence ratios (EQR) from stoichiometric into the lean region. Experimental data available for that engine were used for validation from the first-law (energy) perspective plus emissions and cycle-by-cycle variations (CCV), using in-house, comprehensive, two-zone (unburned and burned), quasi-dimensional turbulent combustion model tracking tightly the flame-front pathway, developed and reported recently by authors. The latter is expanded to comprise exergy terms accompanying the energy outcomes, affording extra valuable information on judicious energy usage. The development in each zone, over the engine cycle, of various exergy terms accounting too for the reactive and diffusion components making up the chemical exergy is calculated and assessed. The correct calculation of species and temperature histories inside the burned zone subsequent to entrainment of fresh mixture from the unburned zone contributes to more exact computation, especially considering the H2 percentage in the fuel blend modifying temperature-levels, which is key factor when the irreversibility is calculated from a balance comprising all rest exergy terms. Illustrative diagrams of the exergy terms in every zone and whole charge reveal the influence of H2 and EQR values on exergy terms, furnishing thorough information. Concerning the joint content of both zones normalized exergy values over the engine cycle, the heat loss transfer exergy curves acquire higher values the higher the H2 or EQR, the work transfer exergy curves acquire slightly higher values the higher the H2 and slightly higher values the lower the EQR, and the irreversibility curves acquire lower values the higher the H2 or EQR. This exergy approach can offer new reflection for the prospective research to advancing engines performance along judicious use of fully friendly ecological fuel as H2. This extended and in-depth exergy analysis on the use of hydrogen in engines has not appeared in the literature. It can lead to undertaking corrective actions for the irreversibility, exergy losses, and chemical exergy, eventually increasing the knowledge of the SI engines science and technology for building smarter control devices when fueling the IC engines with H2 fuel, which can prove to be game changer to attaining a clean energy environment transition.

Response Surface Optimization of Brake Thermal Efficiency and Specific Fuel Consumption of Spark-Ignition Engine Fueled with Gasoline–Pyrooil and Gasoline–Pyrooil–Ethanol Blends

<div>The present study explores the performance of high-density polyethylene (HDPE) pyrooil and ethanol blends with gasoline in SI engine using statistical modeling and analysis using response surface methodology (RSM) and the Anderson–Darling (AD) residual test. The pyrooil was extracted from HDPE through pyrolysis at 450°C and then distilled to separate the liquid fraction. Two blends were prepared by combining pyrooil and gasoline, and pyrooil–ethanol mixture (volume ratio of 9:1) and gasoline, both at volumetric concentrations ranging from 2% to 8% to evaluate brake thermal efficiency (BTE) and specific fuel consumption (SFC) in a SI engine. An experimental matrix containing speed, torque, and blend ratio as independent variables for both blends were designed, analyzed, and optimized using the RSM. The results show that a 4% blend of pyrooil with gasoline (P4) and a 6% blend of pyrooil–ethanol mixture with gasoline (P6E) were optimum for an SI engine. Also, the experimental findings show that the P6E blend exhibits 11% higher BTE and 11.82% lower SFC compared to base fuel (pure gasoline), and 7.55% higher BTE and 6% lower SFC than P4. From the AD test, the residuals for BTE and SFC follow a normal distribution. The results conclude that distilled HDPE pyrooil could be used in SI engines at concentrations of P4 and P6E without requiring engine modification.</div>

Comparative knock analysis of HCNG fueled spark ignition engine using different heat transfer models and prediction of knock intensity by artificial neural network fitting tool

Hydrogen and its careers have a lot of potential in transportation industry due to lesser emissions and better performance. Performance of hydrogen enriched compressed natural gas (HCNG) fueled engine is limited by Knock. The purpose of this study is to investigate knock intensity (KI) by different convective heat transfer models. This study can be used to train electronic control unit (ECU) of engine operating on different loads from low to high speed. In present study, experimentation have been performed on HCNG fueled spark ignition engine at different operating conditions by varying hydrogen amount in HCNG, by varying load of engine, by varying exhaust gas recirculation (EGR) rate in air and by varying speed of engine to calculate in-cylinder pressure, knock intensity (KI) and heat transfer rate (HTR). Six convective heat transfer models (Assanis, Eichelberg, Han, Hohenberg, Nusselt and Woschni) have been incorporated in quasi dimensional combustion model (QDCM) to calculate the parameters of HCNG engine. Comparative and predictive analysis using artificial neural network fitting tool (ANNFT) of aforementioned simulated models have been performed with experimental findings to attain the efficient model for knock intensity of HCNG engine. Woschni model, predicts the minimum error of 0.37 % & 0.86 % b/w experimental and simulated in-cylinder pressure and indicated mean effective pressure respectively. Han model predicts the minimum error of 3.8 % b/w experimental and simulated knock intensity operating at 11.2 % EGR. Maximum error of 20.3 % at 2.4 % EGR is attained by using Woschni model in knock intensity calculation. The best suited algorithm for present data set is Bayesian regularization utilized in ANNFT to predict knock intensity effectively. The findings of this study can be utilized in the development of HCNG engine.

The criteria for qualifying fuels as a replacement fuels for internal combustion engines

The article presents the classification of motor fuels into conventional and unconventional. The concept of replacement fuels is formalized as fuels that can replace conventional petroleum fuels for spark ignition and self-ignition engines without any structural or regulatory changes. The criteria for qualification unconventional fuels as replacement fuels are presented. This article also introduces the results of empirical research conducted on a single-cylinder research engine powered by diesel fuel and rapeseed methyl esters (RME) in summer version and winter version. The engine was tested and the combustion phenomenon in the cylinder was analyzed. Very similar engine properties were observed for diesel fuel and rapeseed methyl esters (RME) in the summer version, while greater differences were found for rapeseed methyl esters (RME) with winter additives. In light of the empirical research and the physicochemical properties of the fuels, it is concluded that RME warrants consideration as replacement fuel for engines with self-ignition, especially in the case of biofuel in the summer version.

Experimental investigation of the effect of CO2 dilution on the performance and hydrogen knock limit of a hydrogen–gasoline dual fuel spark ignition engine 1

This study investigates the effect of CO2 dilution on the performance and hydrogen knock limit of a spark ignition engine fueled with hydrogen–gasoline mixtures. The experimental runs were performed on a Ricardo single-cylinder engine with direct gasoline injection and hydrogen port induction. The hydrogen flow rate was increased at a step size of 2 L per minute (LPM) until the onset of knock, and the CO2 gas was introduced to the intake manifold with flow rates of 2, 4, and 6 LPM. The results revealed that CO2 dilution deteriorated the engine performance regarding the brake mean effective pressure and brake thermal efficiency. The hydrogen enrichment shortens the combustion duration, enhancing the performance and combustion characteristics. Increasing CO2 dilution levels decreased NOx emissions and increased CO emissions. Moreover, CO2 dilution extended the hydrogen knock limit to 10 and 16 LPM for spark timings of 12° and 4° crank angles before top dead center, respectively.

An experimental investigation on the lean-burn characteristics of a novel hydrogen fueled spark ignition engine: Hydrogen injection via a micro-hole on the spark plug

Hydrogen addition in SI engines has been a subject of extensive research over the years, primarily owing to its environmentally friendly attributes and its potential to optimize combustion, especially in lean-burn conditions. However, the use of hydrogen as a gaseous fuel presents challenges due to its high mass-to-volume ratio, which can substantially reduce engine power density, whether in direct injection (DI) or port injection PI conditions. Thus, how to maximum hydrogen's benefits on combustion while minimizing its consumption has become a topic worthy to be studied. In this research, a novel concept where hydrogen direct injected through an aperture on edge of the spark plug (SHDI) was proposed and experimentally investigated on a 1.5 L turbocharged gasoline direct injection (GDI) engine under lean-burn condition. Experiments were conducted at 1600 rpm and medium load conditions with hydrogen injection ratios φH2 varying from 0 % to 5.5 % and excess air coefficients (λ) up to 1.5. Hydrogen port injection (HPI) strategy was also employed as a reference to gauge the performance enhancement achieved through SHDI. The experimental results reveal that, in comparison to HPI, SHDI exhibited more pronounced effects in enhancing initial flame propagation and assisting to formation of stable flame nucleus which, in turn, extended the lean-burn limit substantially. Moreover, SHDI strategy also resulted in a more substantial improvement in mean effective pressure (IMEP) and brake thermal efficiency (BTE) compared to the HPI. However, emissions of NOX, HC and CO were higher in the SHDI mode as opposed to the HPI mode This disparity may be attributed to the elevated local temperatures in the vicinity of the spark plug and the interference caused by the hydrogen jet flow, which disrupted the in-cylinder flow pattern, consequently leading to increased levels of unburnt mixture.

Combustion and emission characteristics of CNG/gasoline DFSI engine with CNG direct injection

CNG was a low-carbon alternative fuel for engines, which also had the advantages of higher engine knock resistance and better fuel/air mixing. The CNG injection and ignition timing was of significant importance for the performance of Dual Fuel Spark Ignition (DFSI) engines. In this paper, the coordinated effects of CNG injection strategy and ignition timing on the combustion and emission characteristics of CNG/gasoline DFSI engines were investigated. The results showed that the CNG/gasoline engine can achieve a comparable level of BMEP to that of a pure gasoline engine by using the CNGDI plus GPI injection approach with an optimal combination of injection and igniting timing. The cyclic variations of CNG/gasoline engines were increased with the advancing of ignition timing, and these variations can be ceased by using proper CNG injection strategies (early or mild). The gaseous emissions (HC, CO, and NOx) of CNG/gasoline engines were equivalent to those of pure gasoline engines; but the PN emissions were lower than that of gasoline engines. The particle size distribution of CNG/gasoline DFSI engines followed a single peak nucleation pattern and most of the particles were in nucleation mode (d ≤ 50 nm) peaking at around 15 nm. This study would be beneficial for the application of CNG in gasoline engines, which was promising to alleviate the strong dependence of engines on petroleum energy and to reduce their greenhouse gas emission.

An Experimental Investigation into the Performance and Emission Characteristics of a Gasoline Direct Injection Engine Fueled with Isopropanol Gasoline Blends

Propanol isomers, which are oxygen-rich fuels, possess superior octane ratings and energy density in comparison to methanol and ethanol. Recently, due to advancements in fermentation techniques, these propanol isomers have garnered increased interest as additives for engines. They are being explored to decrease emissions and reduce the usage of conventional fossil fuels. This study delves into this emerging field. One of the alternatives is the use of alcohol fuels in their pure state or as additives to traditional fuels. Alcohols, due to their higher volumetric energy density, are better fuels for spark ignition engines than hydrogen and biogas. Alcohol-blended fuels or alcohol fuels in their pure state may be used in gasoline engines to reduce exhaust emissions. The current research emphasizes the effect of isopropanol gasoline blends on the performance and emissions characteristics of a gasoline direct injection (GDI) engine. This investigation was conducted with different blends of isopropanol and gasoline (by volume: 10% isopropanol [IP10], 20% isopropanol [IP10], 30% isopropanol [IP30], 40% isopropanol [IP40], and 50% isopropanol [IP50]). The reviewed results showed that with increasing isopropanol in the fuel blends, engine brake power increased while BSFC decreased. In terms of emissions, with the increase in isopropanol in the fuel blends, CO and HC emissions decreased while CO2 and NOx emissions increased.

Combustion and emission characteristics of dimethyl ether/gasoline DFSI engine under different excess air coefficients

Dimethyl ether (DME) was a carbon neutral alternative fuel for engines.The combustion and emission characteristics of a DME/gasoline Dual Fuel Spark Ignition (DFSI) engine with various excess air coefficients (λs) at different DME ratios (ΦDME) were investigated experimentally in this study.The in-cylinder pressures along with their relevant crank angle were used for the combustion characteristics calculation. The light five component exhaust gas analyzer and particle analyzer were employed for the gaseous and particulate matter emission measurement, respectively. Results showed that the DME/gasoline dual fuel combustion strategy can enhance the Brake Mean Effective Pressure (BMEP) by up to 12.6% because the high diffusivity, superior LTR and fast LFS of DME. Although adding DME was beneficial for the reduction of gaseous emissions (HC, CO and NOx) from DME/gasoline DFSI engines, the gaseous emissions were mainly determined by the variation of λ s. Particularly, up to 93.4% of the CO emissions at stoichiometric condition can be reduced after increasing λ to 1.3. The fast evaporation rate and superior LTR of DME helped to suppress PN emissions, but larger DME ratio (ΦDME > 5%) was needed for λ >1.2.

Ignition detection with the breakdown voltage measurement during nanosecond repetitively pulsed discharges

Nanosecond Repetitively Pulsed Discharge (NRPD) is a promising ignition concept for introducing diesel-like process parameters for hard-to-ignite renewable fuels in Spark Ignition (SI) engines. Knowing whether an ignition event initiated by a series of nanosecond electrical discharges was successful or not gives the possibility of using this information for closed-loop ignition control. This paper presents a methodology for detecting successful ignition under NRPD ignition.After a nanosecond discharge, the heat loss from the particles (plasma-gas) between the electrodes and the surrounding gas is different if a robust flame kernel is established. If a flame kernel is present, the heat losses are lower, resulting in a lower local density of the gas between the electrodes. The breakdown voltage value of a nanosecond pulse is proportional to the local density. A control pulse is applied after the main ignition sequence to detect successful ignition. Lower breakdown voltages of the control pulse are present if a robust early flame kernel is present. The control pulse is applied before the pressure rises due to the presence of fast combustion, allowing ignition to be detected during the inflammation phase, thus allowing the possibility to place additional ignition events, if necessary.This technique was experimentally analyzed in a Constant Volume ignition Cell (CVC) and in a Rapid Compression Expansion Machine (RCEM). In the CVC at the ignitability limit, lower breakdown voltages of the control pulse are mostly measured when no pressure rise is measured. In the RCEM, the heat release rate is analyzed with a two-zone thermodynamic model, and the early flame kernel formation is monitored with Schlieren imaging. Some overlap exists in the control pulses' breakdown voltages for the ignition and quenching experiments; nevertheless, the Schlieren videos outline that the overlapping cases have a similar flame kernel formation, and the difference arises thereafter.

Experimental Examination of Recovery by a Thermoelectric Generator of Heat Energy Lost to Engine Coolant in a SI Engine

In this study, the recovery of heat energy lost to the engine coolant (Ec) in a liquid-cooled, gas-fueled (propane), spark ignition (SI) engine using a thermoelectric generator (TEG) is experimentally researched. A two-layer rectangular geometry TEG is designed, consisting of a propane heat exchanger (P_hex) located on the surface of an engine coolant heat exchanger (Ec_hex). 20 items of thermoelectric modules (TEMs), each 30x30 mm in dimensions, are placed between the Ec_hex and P_hex. In the TEG design, engine cooling fluid is used on the hot surface of the TEMs, and propane gas fed to the engine is used on the cold surface. In addition, with the use of the designed TEG, there is no need to use an additional evaporator for propane gas. Experiments are carried out with the designed TEG at 8 engine speeds ranging from 1500 to 5000 rpm. As a result, TEG produces 1.25–3.01 W of DC electrical power in the engine's 1500–5000 rpm range, while TEG efficiency fluctuates between 2.7 and 3.1%. However, the maximum TEG_power is 3.01 W at 5000 rpm, while the maximum TEG_efficiency is 3.1% at 1500 rpm. On the other hand, the electrical power of TEG between 1500 – 5000 rpm of the engine is approximately 1.1–1.26% of the engine charging system power. However, TEG's contribution to the charging system again decreases with the engine speed.

Computational analysis of performances for a hydrogen enriched compressed natural gas engine’ by advanced machine learning algorithms

The support vector machine along with particle swarm optimization and artificial neural network have already been implemented for the regression study of a hydrogen enriched compressed natural gas (HCNG) fueled spark ignition engine. The main issues were that the support vector machine along with particle swarm optimization requires more computational time while the artificial neural network is sensitive to the hidden layers. Therefore, these algorithms are not effectively suitable for online control of the electronic control unit. The theme of this study is to evaluate the multiple mathematical engine’ models with respect to swiftness and accuracy. The experiments have been conducted under a wide range of operating conditions in a heavy-duty SI engine to obtain the data sets. The brake specific fuel consumption, engine torque and NOx emissions have been trained and analyzed by eight different machine learning algorithms along with nineteen sub-models. The effectiveness of these algorithms has been evaluated with respect to the root mean squared error and prediction time. The analysis indicate that the gaussian process regression (GPR) is optimal with respect to the computational efficiency (i.e., RMSE = 0.3823 g/kWh) and time (t < 16.019 sec). Furthermore, it operates without the iteration of the hidden layers. The mean simulation time for the gaussian process regression is 20,192 times lower as compared to the support vector machine along with particle swarm optimization algorithm. Since the gaussian process regression (GPR) is fast, optimal and insensitive to the hidden layers, so it is an ideal tool for online calibration of the electronic control unit.

Effects of fuel composition at varying air-fuel ratio on knock resistance during spark-ignition combustion

Knock resistance of liquid fuels for spark-ignition engines is determined using standardised tests (RON and MON), however, these measurements are not undertaken at the same air–fuel ratio for different fuels. In contrast, modern engines have a highly controlled air–fuel ratio, often operating in a very narrow range around stoichiometric in order to reduce pollutant emissions and achieve high thermal efficiencies. As global efforts to increase the utilisation of renewable fuels of varying composition intensify, understanding of the differing knock sensitivity to the air–fuel ratio at which the engine is operated provides a vital opportunity to further optimise combustion processes.This paper investigates the influence of varying relative air–fuel ratios, the exhaust λ, on the knock resistance of a range of fuels of varying RON values and chemical compositions. Binary component primary reference fuels and practical gasolines of equivalent RON values were tested with a Ricardo E6 variable compression engine operated at conditions similar to those used for RON tests. It was found that the engine compression ratio which could be utilised before a knock threshold was exceeded was the same for fuels of equivalent RON at fuel rich conditions but differed appreciably at stoichiometric conditions (λ = 1). The knock resistance of purely paraffinic reference fuels was observed to be more sensitive to changes in exhaust λ than the aromatic gasoline fuels, especially at λ = 1, where the former fuels required significantly higher engine compression ratios to achieve equivalent levels of knock.

Optimization of fuel injection timing and ignition timing of hydrogen fueled SI engine based on DOE-MPGA

For the port injection hydrogen-fueled spark ignition (SI) engine modified from the Jialing JH600 gasoline engine, the hydrogen injection timing and ignition timing of the hydrogen SI engine are comprehensively optimized on the AVL-FIRE software based on the combination of design of experiment (DOE) and multiple population genetic algorithm (MPGA). Firstly, the effects of hydrogen injection timing and ignition timing on the performance of the hydrogen engine are investigated through the full factors design of experiment scheme, and then the optimum intervals of them are determined respectively. Secondly, the uniform design of experiments scheme is arranged, and the regression functions of indicated power, indicated thermal efficiency and emissions of the hydrogen engine under different working conditions are fitted. Then, the comprehensive optimization model is constructed. Finally, the optimum hydrogen injection timing and ignition timing of the hydrogen engine under different working conditions are solved based on MPGA. The results show that, compared with the standard genetic algorithm (SGA), the MPGA has faster convergence speed and higher convergence accuracy. In addition, as the load increases from low to high, the optimum hydrogen injection timing is advanced and the rate of variation increases from 0.6% to 1.1%, the optimum ignition timing is delayed and the rate of variation decreases from 29.1% to 17.8%.

Investigation of combustion and emission characteristics of an SI engine operated with compressed biomethane gas, and alcohols.

Alternative fuels in spark-ignition engines significantly reduce engine exhaust emissions and improve fuel efficiency. This research investigates the performance of a multicylinder SI engine using 10%, 20% (ethanol, methanol, methyl acetate), and 100% compressed biomethane gas (CBG) as alternative fuels. Engine performance parameters (BTE, ITE, ME, BP), BSFC, ISFC, FF, combustionphenomenon (cylinder pressure, crank angle, cylinder volume, mass fraction burned, net heat release, mean gas temperature, cumulative heat release, rate of pressure rise), and emission characteristics (HC, CO, CO2, NOx) are measured. CBG achieved a maximum BTE of 23.33% compared to all other fuels.Minimum fuel consumption rate of 1.72kg/h at maximum rpm achieved BSFC value of 0.44kg/kWh and ISFC value of 0.261kg/kWh. The highest cylinder pressure of 6.79bar was achieved in the G90M10 with a cylinder volume of 48.58cc. NHR of 3.08 j/deg was found in the G80M20 at a crank angle of 376°, and the maximum MGT was 390.20°C in the G80E20. The highest CHR values of 0.12kJ at crank angles of 432°, 420°, 422°, and 427° were achieved in the G100, CBG, G80E20, and G90E10. G90M10 reached a maximum value of 0.14bar/degree of rate of pressure rise at a crank angle of 374°. Average minimum emission gas was found in CBG at a minimum and maximum RPM, indicating that CBG gives the best emission result with engine performance compared to all alternative fuels.

Enhancement of Low Operating Load Limit and Engine Characteristics by Hydrogen Addition in a Biogas-Fueled Spark-Ignition Engine

Abstract Biogas is a renewable gaseous fuel and has the potential to replace fossil fuels for spark-ignition engines; however, a higher volumetric proportion of CO2 in biogas degrades the engine characteristics significantly. Biogas upgradation techniques are limited by higher fuel costs, and strenuous modifications would be required for improving engine physical parameters. In this study, experimental investigations were performed with hydrogen-enriched biogas to enhance low operating load limit and engine characteristics, and to the best of authors' knowledge, studies related to operating range and low load enhancement by hydrogen addition in biogas fueled engines are not reported in literature. Gaseous-fuels blending setup was developed to fabricate the gaseous fuel mixtures in desired proportions and moderate amounts of hydrogen (5, 10, 20, and 30% by vol.) were blended with biogas. The experiments were conducted on a single-cylinder SI engine operated at the compression ratio of 10:1 and 1500 rpm for stationary applications. It was found that the coefficient of variation (COV) of indicated mean effective pressure decreased from 10% in case of biogas to 8.69, 6, 3.05, and 1.66%, respectively, for 5, 10, 20, and 30% hydrogen cases at 6 N·m loading condition. Low operating load limit enhanced from 6 N·m in case of biogas to 5.3, 2.2, 1.5, and 0.8 N·m, respectively, for 5, 10, 20, and 30% of hydrogen share in the fuel mixture and brake thermal efficiency also improved with hydrogen enrichment. Carbon-based emissions decreased with hydrogen addition, whereas oxides of nitrogen increased but it was well below the baseline case with pure methane. Overall results indicated that hydrogen enrichment enhances the low load limit and engine characteristics of biogas-fueled SI engines for stationary power generation applications in rural areas.

Assessment of the Operation of an SI Engine Fueled with Ammonia

Recently, the research interest regarding ammonia applications in energy systems has been increasing. Ammonia is an important hydrogen carrier that can also be obtained starting from renewable energy sources. Furthermore, ammonia can be used as a carbon-free fuel in combustion systems. In particular, the behavior of internal combustion engines (ICEs), fueled by ammonia, needs to be further investigated. The main disadvantage of this kind of fuel is its low laminar flame speed when it is oxidized with air. On the other hand, considering a spark-ignition (SI) engine, the absence of knock phenomena could allow a performance improvement. In this work, a 1D numerical approach was used in order to assess the performance and the operating limits of a downsized PFI SI engine fueled with pure ammonia. Furthermore, the reliability of the 1D model was verified by means of a 3D approach. Both throttled and unthrottled engine operation was investigated. In particular, different boost levels were analyzed under WOT (wide-open throttle) conditions. The potential of the 1D approach was also exploited to evaluate the effect of different geometrical compression ratio on the ammonia engine behavior. The results show that the low laminar flame speed of ammonia–air mixtures leads to increased combustion durations and optimal spark timings more advanced than the typical ones of SI engines. On the other hand, knock phenomena are always avoided. Due to the engine operating limits, the maximum rotational speed guaranteeing proper engine operation is 3000 rpm, except for at the highest boost level. At this regime, the load regulation can be critical in terms of unburned fuel emissions. Considering increased compression ratios and no boost conditions, even the 4000 rpm operating point guarantees proper engine operation.

Investigation on injection strategy affecting the mixture formation and combustion of a heavy-duty spark-ignition methanol engine

Methanol is thought as a carbon neutral fuel and one of the most promising alternative fuels for spark-ignition (SI) engine. On the basic combustion theory of SI engines, mixture formation plays an important role in the SI engine performance. However, there is a lack of investigation on the mixture formation process of heavy-duty (HD) port fuel injection (PFI) SI methanol engines. Therefore, experiments and simulations were conducted on a HD PFI SI engine fueled with pure methanol. The effects of the injection timing (αinj) on the mixture formation process, combustion and emission characteristics were investigated. Methanol engine performance can be predicted by the mixture homogeneity which is deeply affected by injection timing. When αinj was 240°CA, 360°CA and 480°CA, there were three typical mixture formation modes, namely “spray”, “premix and spray” and “premix” mode, respectively. The mixture homogeneity increased first and then decreased while the in-cylinder temperature at the spark timing increased monotonically as αinj varied from 240°CA to 480°CA at the interval of 120°CA. The “premix and spray” mode was the optimal mixture formation strategy from the perspective of promoting mixture homogeneity and decreasing the in-cylinder mixture temperature. When αinj was from 120°CA to 300°CA, the leaner mixture around the spark plug and lower mixture prolonged or retarded CA0-10, CA10-90 and CA50. The above combustion characteristics contributed to a lower engine brake thermal efficiency (BTE) at αinj of 120°CA to 300°CA. As αinj varied from 0°CA to 720°CA, HC emissions increased first and then decreased while CO emissions did the opposite. Both HC and CO emissions at αinj of 360°CA were at low levels. The more HC emission was caused by the more regions with the richer mixture in the crevice formed by the piston and liner. The CO emission was determined by the volume of regions with the richer mixture in the combustion chamber and in-cylinder mixture temperature. The “premix and spray” mode should be adopted to improve the BTE and reduce both HC and CO emissions.

Prediction of gasoline research octane number using multiple feature machine learning models

Liquid hydrocarbons are typically used as fuels in the internal combustion engines due to their high volumetric energy density and ease of handling, storage, and transportation. Gasoline is the most extensively used fuel for the light-duty automobiles and passenger cars. Research octane number (RON), among other auto ignition related properties, is a primary indicator of the grade of the light-duty automobile fuels. Because measuring the RON is expensive and time-consuming, an alternative cost-effective grading method for engines is desired, for example, methods that in corporate machine learning. However, the physicochemical properties of the constituents of gasoline have a notable nonlinear relationship with the RON of the fuel. The accurate blending and production of commercial spark ignition engine fuels is limited by the lack of precise predictive models for RON. In this study, we developed a high-throughput method that accounts for the properties of gasoline and uses the Random Forest (RF) algorithm to predict the RON of gasoline. The maximum error of the RF model in RON prediction was 0.46, which was close to the range of experimental uncertainty. The experimental results indicated that the properties of gasoline can be used to predict its RON, and the complex relationships among the constituents can be analyzed using tools such as the RF algorithm.