Indicated Specific Fuel Consumption Research Articles

Effects of split injection strategy on combustion characteristics and NOx emissions performance in dual-fuel marine engine

In order to address environmental concerns and promote sustainable development, the maritime industry is facing a demand to reduce emissions from ship engines. To address this, a growing trend in the development of diesel natural gas dual-fuel marine engine involves implementing more flexible diesel injection strategies, with the aim of enhancing performance and minimizing harmful emissions. This study utilized a numerical investigation based on the Large Eddy Simulation (LES) method to examine pilot diesel injection strategies in a dual-fuel marine engine operating at a high degree of natural gas substitution rate. Specifically, the analysis focused on the start of injection (SOI) in the single injection strategy and the first start of injection (SOI1) in the split injection strategy for pilot diesel. The findings highlight distinct trade-off relationships between these two injection strategies regarding their impact on indicated specific fuel consumption (ISFC) and NOx emissions. Compared to the optimized single injection strategy (Case A: SOI = -15°CA ATDC), the optimized split injection strategy (Case B: SOI1 = -60°CA ATDC, SOI2 = -10°CA ATDC) increases thermal efficiency by 0.77 % while reducing NOx emissions by 36.3 %. The split injection strategy induces low-temperature reactions of n-heptane in the squish region, resulting in the generation of active free radicals such as CH2O and OH, thereby accelerating the propagation speed of the flame in the squish region. Meanwhile, the split injection strategy diminishes pilot diesel accumulation in the piston bowl region, narrows the distribution range of high-temperature areas surpassing 2400 K, consequently leading to a reduction in NOx emissions.

Multi-objective optimization of the performance for a marine methanol-diesel dual-fuel engine

Marine methanol-diesel compound combustion (DMCC) engines have received extensive attention in the shipping industry. This work aims to further improve the performance and evaluate the carbon reduction potential of the marine DMCC engine. First, the computational fluid dynamic model of the dual-fuel engine was built. Then, an intelligent regression method based on the grey wolf optimizer (GWO) algorithm optimized support vector machine regression (SVR) was proposed. The methanol substitution rate (MSR), excess air ratio (EAR), and diesel injection timing (DIT) were adopted as the decision variables to establish the regression models for NOx, CO, and CO2 emissions and indicated specific fuel consumption (ISFC). Subsequently, a multi-objective grey wolf optimizer (MOGWO) and entropy weight TOPSIS were employed to obtain the optimal case for achieving low NOx and CO emissions and ISFC. Finally, the maximum MSR was explored to achieve greater carbon reduction benefits while balancing the NOx emission and ISFC. The results showed that after GWO optimization, the coefficients of determination of the SVR regression models are all greater than 0.95, with mean square errors consistently below 0.015. It indicates that the regression models have excellent consistency and applicability. The optimal case calculated by MOGWO and entropy-weighted TOPSIS enables co-optimization of the NOx emission and ISFC while maintaining the CO emission below 600 ppm. Compared to the original case, the optimal case achieves reductions of 26.22 % for NOx and 13.39 % for ISFC. The exploration of the maximum MSR reveals that in the Pareto optimal set, the maximum MSR reaches 56.16 %, at which point the NOx and CO2 emissions reduce by 75.85 % and 59.32 % respectively, while the ISFC increases by 21.67 % compared to the original case.

Investigation of injection parameters coupled with fuel reactivity on combustion and emissions in dual direct-injection GCI engine

Fuel injection parameters and fuel reactivity significantly affect engine performance, combustion, and emissions. The dual direct-injection strategy could compensate for the insufficient heat release rate to improve the gasoline compression ignition (GCI) mode with medium injection pressure for high loads. This research aims to couple injection parameters and fuel reactivity to optimize the combustion, emissions, and engine performance of the dual direct-injection GCI mode at high loads. The effect of research octane number (RON) of gasoline, injection timing, and injection pressure of dual injection system on combustion and emissions was investigated. Results show that the optimized dual direct-injection GCI mode can simultaneously achieve high thermal efficiency, low emissions, and low maximum pressure rise rate (MPRR) at high loads with the maximum indicated mean effective pressure (IMEP) of about 16 bar with indicated thermal efficiency (ITE) of 48.5%. Delaying the injection timing of injector-1 reduced the peak pressure (Ppeak), MPRR, and NOx emissions. Ppeak, CO, NOx, and indicated specific fuel consumption (ISFC) decreased compared to the dual-injector simultaneous injection case when the injection timing of injector-2 was retarded to between 5 and 10°CA ATDC. Increasing the injection pressure of injector-2 reduced CO, THC, ISFC, and particulate emissions. Lower RON gasoline obtains higher ITE while higher RON gasoline obtains lower particulate emissions.

Performance and energy balance analysis of the downsized SI engine with using a novel OPCVCR and synchronized twin spark plugs configurations

Recently, the exhaust emissions become one of the main issues in the downsizing spark ignition (SI) engine. It is necessary to develop clean combustion and high efficiency SI engines for further increasing the performance and brake thermal efficiency. In this study, a novel opposite piston type continuous variable compression ratio (OPCVCR) mechanism combined with synchronous twin spark plugs configurations was proposed and applied in the turbocharged downsizing SI engine. The purpose of this study was to propose a novel type of OPCVCR engine and analyze its combustion, performance and energy balance characteristics. The results showed that the peak combustion temperature (PCT) and peak combustion pressure (PCP) of the OPCVCR engine with twin spark plugs were increased when the compression ratio (CR) increased. The knocking combustion intensity of the downsized SI engine was increased when the CR increased, while the knocking combustion intensity can be alleviated effectively by introducing the external EGR. In addition, the energy utilization efficiency was increased with increasing the CR of the OPCVCR engine with twin spark plugs. Besides, the indicated specific fuel consumption (ISFC) of the base downsized SI engine could be decreased by 23.59% and the indicated thermal efficiency (ITE) of the base downsized SI engine could be increased 21.62% by adopting CR 16 and introducing 10% external exhaust gas recirculation (EGR), respectively.

Study on the Effect of Parameter Sensitivity on Engine Optimization Results

The effects of six control parameters, intake valve opening timing (IVO), exhaust valve opening timing (EVO), compression ratio (CR), engine speed, intake temperature, and intake pressure on engine output power, indicated specific fuel consumption (ISFC), and nitrogen oxides (NOx) emissions, are analyzed through engine simulation. The six parameters were categorized into two groups based on the degree of influence: high influence (EVO, speed and intake pressure) and low influence (CR, IVO and intake temperature). The relationship between these two groups of parameters and power, ISFC and NOx emissions was explored. Optimization was carried out for each of the two groups of parameters, and the optimization of the high impact parameters resulted in a higher diversity and wider distribution of the solution set. On the other hand, the optimization of the low-impact parameters resulted in a more concentrated distribution of the solution set, while better reflecting the trade-off between the optimization objectives. For the optimal solutions for both sets of parameters, the high-impact parameters provided significant optimization performance compared to the standard operating conditions. Although power and ISFC were optimized, the optimal solution for the low-impact parameter performed poorly with a significant increase in NOx emissions. Therefore, the parameters should be evaluated for optimization using high impact parameters to improve engine performance.

Numerical investigation for enhancing HCCI combustion characteristics in DI-CI engine fueled with butanol/diesel blends

The fast depletion of fossil fuels and the hazardous emissions associated with the use of fossil fuels in IC engines is driving the research in the area of renewable fuels. Homogeneous charge combustion ignition (HCCI) is a new mode of engine combustion technology, used for reducing the emissions without compromising the engine performance. The combination of HCCI and alcohol/diesel blends has the potential to simultaneously address the twin problems of depletion of fossil fuels and engine emissions. Butanol is an attractive biofuel, which is produced from agriculture wastes such as sugar cane bagasses and corn stalk etc. This paper presents numerical and modeling analysis on the emission and performance characteristics of a direct injection- compression ignition (DI-CI) engine operated with butanol/diesel blends. Numerical analysis was carried out using CONVERGE CFD software. Response surface methodology (RSM) was used in developing the response models for three output parameters, viz., nitrogen oxides (NOx), soot emissions and indicated specific fuel consumption (ISFC), in terms of the four input parameters, viz., compression ratio (CR), start of injection (SOI), fuel injection pressure (FIP) and exhaust gas recirculation (EGR). Numerical experiments were conducted by varying these four input parameters, i.e., CR from 14 to 19, FIP from 200 to 280 bar, EGR from 0% to 30% and SOI from 17° to 29° CA bTDC, and with four butanol/diesel blends (0, 20%, 30% and 40% of butanol-by volume, designated as Bu00, Bu20, Bu30 and Bu40). The optimum combination of the input parameters for the four test fuels were found with the objective of minimizing the three output parameters (i.e., ISFC, soot and NOx) using desirability approach. The homogeneity of the air-fuel mixture was estimated using equivalence ratio distribution index, i.e., Target fuel distribution index (TFDI). From the numerical analysis, it was found that the TFDI improved for the optimized case by 20.5%, 21.5%, 24.4% and 27.2% for Bu00, Bu20, Bu30 and Bu40 respectively as compared to their respective baseline configuration.

Effect of early intake valve closing, exhaust gas recirculation and split injection on combustion and emissions characteristics of a HDDI diesel engine operating in PCCI combustion mode

Premixed Charge Compression Ignition (PCCI) combustion is an alternative to conventional diffusion-controlled combustion for Mono-nitrogen oxides (NOx) and soot emissions reduction in DI diesel engines. However, bringing the center of combustion (CoC) near top dead center (TDC) to reduce brake specific fuel consumption is challenging. In this study, for two Early Intake Valve Closing (EIVC) profiles of split injection strategy, combustion characteristics and emissions of a heavy-duty direct injection (HDDI) diesel engine are evaluated by CFD simulations. Combustion efficiency, Indicated Specific Fuel Consumption (ISFC), NOx, soot, and carbon monoxide (CO) emissions are evaluated for 40 ˚CA and 80˚CA EIVC timings with respect to the base diesel combustion with 0, 30, 50, and 70% Exhaust Gas Recirculation (EGR) rates at 3 bar Brake Mean Effective Pressure (BMEP).CFD simulations reveal that EIVC strategy can displace the CoC towards TDC up to 5–10 ˚CA depending on the EGR rate. Moreover, up to 30% NOx reduction can be achieved in EIVC cases. In 70% EGR case, lower ISFC and near zero NOx emissions can be obtained compared to conventional diesel combustion due to CoC being closer to TDC. However, the EIVC strategy with EGR increases CO emissions due to incomplete combustion of a lower air/fuel ratio mixture.

Ammonia-hydrogen engine with reactivity-controlled turbulent jet ignition (RCTJI)

Ammonia (NH3) is a promising fuel for engine carbon neutrality. However, the terrible combustion characteristics substantially restrain the application of NH3 in internal combustion engines (ICE). Hydrogen addition and pre-chamber turbulent jet ignition (TJI) show outstanding abilities to solve the difficult ignition and low flame velocity for ammonia combustion. At present work, a concept of reactivity-controlled TJI (RCTJI) with hydrogen fuel is proposed, and the combustion characteristics of the ammonia-hydrogen engine are investigated. The present study proposes two operating modes of the RCTJI ammonia-hydrogen engine. The controllable pre-chamber reactivity is achieved by varying the hydrogen concentration and/or adjusting the quantity of the pre-chamber mixture. Then, the effects of the pre-chamber properties regarding the pre-chamber nozzle diameter, per-chamber operating mode, and pre-chamber mixture reactivity on the engine performance are analyzed. The results show that adjusting the mixture reactivity in the pre-chamber can effectivity control the ignition ability and engine performance. The better performance of the RCTJI ammonia-hydrogen engine is obtained under the conditions of per-chamber with a 4 mm hole size and hydrogen fuel, and it can further be optimized by operating the pre-chamber in Mode 2 with an extra scavenging process. An operation strategy of the pre-chamber for the RCTJI ammonia-hydrogen engine is proposed: the RCTJI pre-chamber is suggested to operate under Mode 2 and achieve the first scavenging process by stoichiometric hydrogen/air mixture, and the injection quantity of scavenging gas in the pre-chamber should be controlled in the range of 1.0 Mt–2.5 Mt. At the boosting conditions, the power performance and fuel economy of the RCTJI ammonia-hydrogen engine are optimized effectively. The indicated mean effective pressure (IMEP) increases from 6.3 bar to 10.0 bar at λ = 1.0 as the intake pressure increases from 1.0 bar to 1.4 bar. The optimum fuel consumption rate is obtained at the lean condition of λ = 1.4, achieving a 13.3% reduction of the indicated specific fuel consumption (ISFC).

Performance of a compression ignition engine fuelled with diesel-palm biodiesel-gasoline mixtures: CFD and multi parameter optimisation studies

In this research, 3D CFD simulations are conducted for a compression ignition engine fuelled with D100 (diesel), D80|BD20 (80%diesel|20%biodiesel), D75|BD20|G5 (75%diesel|20%biodiesel|5%gasoline), D70|BD20|G10 and D65|BD20|G15 mixtures. The effects of blending ratio, exhaust gas recirculation (EGR) and start of injection (SOI) on the combustion, emissions, engine output and fuel efficiency are analysed. In brief, D65|BD20|G15 produced the least nitrogen oxides (NOx) and soot emissions of 6.5E-2 and 5.46E-3 g/kWh, respectively, which were lower than the Euro VI limit. The least carbon monoxide (CO) and unburnt hydrocarbons (UHCs) emissions were achieved for D75|BD20|G5 for 1.62 and 5.8 g/kWh, respectively. D75|BD20|G15 improved the indicated mean effective pressure (IMEP), combustion efficiency and indicated specific fuel consumption (ISFC) up to 13.9%, 12.7% and 13.9% compared to D80|BD20, respectively. Also, applying 20% EGR led to 50% reduction in NOx and soot for D65|BD20|G15, while UHCs and CO were increased up to 27% and 54%, respectively and ISFC and combustion efficiency slightly declined. Additionally, advancing SOI timing to −24 Crank Angle (°CA) decreased the CO and UHCs emissions of D65|BD20|G15 up to 20% and 15% compared to −20°CA, respectively. A multi-parameter optimisation is also performed to ascertain the best operating condition, under which the emissions are mostly supressed and engine performance and fuel efficiency are enhanced.

Borderline knock adaptation based on online updated surrogate models

Spark ignition engines are often desired to be operated close to its knock borderline limit, when MBT (maximum brake torque) cannot be achieved, to optimize engine efficiency. Traditionally, engine knock is closed-loop controlled using a dual-rate PID scheme with the help of feedforward control based on off-line calibrated borderline knock limit along with associated corrections. Note that the feedforward control is often not accurate and very conservative. This paper proposed a data-driven knock baseline control architecture consisting of two-key components: (a) offline training knock borderline Surrogate models under the worst and lightest knock conditions and (b) online updating the composite Surrogate model for adaptation. A Bayesian-based multi-objectives optimization algorithm is used to obtain optimal knock control parameters with significantly improved calibration efficiency, where the offline trained models are obtained using spark and intake valve timings as control parameters, and indicated specific fuel consumption (ISFC) and knock intensity (KI) as two competing performance measures to be minimized. Based on our early results, two Kriging surrogate models with two corresponding Pareto fronts (most and least advanced timing) can be obtained, and the purpose of this paper is to generate a composite real-time Kriging model for compensating engine aging and operational environmental changes such as fuel type, temperature, humidity, etc. In order to reduce the number of control parameters used in online updating, principal component analysis is conducted to find dominated control parameter, and in this case, the spark timing is the most sensitive factor of Pareto front. During the online updating process, a likelihood ratio controller with short- and long-term buffers was proposed to update the surrogate model in real-time and to adapt to fast and slow environmental and engine variations so that the optimal borderline knock limit can be found based on the intersection of mean and variance of Pareto front from the real-time updated composite Kriging model; and accordingly, the optimal control parameters can be located in the design space using surrogate model. Both simulation and test results indicate that the proposed online updating scheme is able to update the machine-learned stochastic surrogate models and adjust the feedforward borderline knock control parameters adapted to engine aging and operational environment.

Experimental investigation on the performance of pure ammonia engine based on reactivity controlled turbulent jet ignition

Ammonia-based internal combustion engines (ICEs) produce carbon-free emissions. However, the application of ammonia in ICEs results in difficult ignition, combustion instability, and reduced engine performance. In this study, the pre-chamber turbulent jet ignition (TJI) technology was applied to overcome these issues. Two TJI modes based on a self-designed scavenging pre-chamber were proposed in the engine experiments. These modes were air-assisted injection mode (TJI mode 1) and air-assisted injection mode with an air-scavenging process (TJI mode 2). The results demonstrated that the TJI system optimized the combustion stability and improved the burning rate of the ammonia engine. TJI combustion mode had a superior indicated mean effective pressure (IMEP), coefficient of IMEP variation (CoVIMEP), and indicated specific fuel consumption (ISFC) compared with the SI mode, particularly the TJI mode 2 with scavenging process. The NOx and NH3 emissions were high for the ammonia engine regardless of the ignition mode. However, the emissions decreased after adopting the TJI combustion mode. This study provides valuable insights into the application of the TJI ammonia engine to achieve zero-carbon emissions.

The multi-parameter optimization of injections on double-layer diesel engines based on genetic algorithm

In this paper, a coupling model of the NSGA-II genetic algorithm and KIVA-3 V program is developed to perform a multi-objective intelligent optimization study of the injection parameters in a diesel engine with double-layer diverging combustion (DLDC) chamber. Four optimization parameters, involving the first injection timing, the first fuel split ratio, the injection timing interval, and the exhaust gas recirculation (EGR) ratio, are optimized after comparing the pollutant emissions and fuel consumption characteristics. The computation results reveal that both soot and fuel consumption function as the optimization objectives, proving a trade-off relationship with the NOx emission. The analysis of the response surface demonstrates that the application of the multiple-injection strategies is beneficial for enhancing the performance of diesel engines. A large first fuel split ratio and a low EGR rate can minimize both ISFC (indicated specific fuel consumption) and soot emission concurrently. A high EGR rate can significantly reduce NOx emission. In addition, the distribution of the final Pareto font shows that 66.7 % percent of the first fuel split ratio is above 0.56, and only two solutions (8.3 %) have values below 0.35. Furthermore, three representative points of the first fuel split ratio are selected for combustion analysis, which are 0.05, 0.35, and 0.88. As the first fuel split ratio rises, the high-temperature areas in the cylinder are gradually enlarged, and the NOx emission is increased while the soot emission and ISFC are further reduced.

Multi-objective optimization of a hydrogen-fueled Wankel rotary engine based on machine learning and genetic algorithm

Hydrogen is a promising way to achieve high efficiency and low emissions for Wankel rotary engines. In this paper, the intake and exhaust phases and excess air ratios (λ) were optimized using machine learning (ML) and genetic algorithm (GA). Firstly, a one-dimensional model was built and verified under various λ. Secondly, the variables were determined using sensitivity analysis method, and the sample for training models was generated using the Latin hypercube sampling. Finally, a prediction model for performance and emissions was built using ML and combined with GA for multi-objective optimization. The results show that the timing of intake port full closing (IPFC) and exhaust port start opening (EPSO) exhibits the most significant influence on performance and emissions, while the other phases are less influential. Both indicated mean effective pressure (IMEP) and indicated specific nitrogen oxides (ISNOx) increase as the IPFC timing is advanced, while indicated specific fuel consumption (ISFC) decreases as EPSO timing is delayed. Compared with the original engine, the optimized IMEP is improved by 0.18%, ISFC is reduced by 2.39%, and ISNOx is reduced by up to 65.43%. It is an efficient way to use ML combined with GA to improve performance and reduce emissions simultaneously.

Effect of Intake Charge Temperature on Oxy-Fuel Combustion in an HCCI Diesel Engine Under Different Carbon Dioxide Dilutions

Abstract Carbon dioxide is one of the leading contributors to global warming. Oxy-fuel combustion (OFC) integrated with carbon capture and storage (CCS) technology is an efficient way to reduce carbon dioxide emissions. In OFC, pure oxygen (O2) is used instead of air to react with hydrocarbon fuel. Consequently, the products of combustion mainly include carbon dioxide (CO2) and water vapor (H2O) under lean conditions. Meanwhile, due to the absence of N2 in the intake charge, nitrogen-related emissions such as NOx are greatly removed from the exhaust gases. In the present study, the effect of intake charge temperature on OFC has been investigated in a diesel engine under the homogeneous charge compression ignition (HCCI) mode. In order to control combustion temperature and avoid overheating problems caused by oxygen in OFC, a portion of the exhaust CO2 was added to the O2. For this purpose, different CO2 dilutions ranging from 79-85% have been employed. It has been found that OFC can significantly reduce CO and particulate matter (PM) emissions while eliminating NOx emissions. With a higher intake charge temperature, combustion occurs earlier with shorter main stages, reducing the indicated mean effective pressure (IMEP) and increasing the indicated specific fuel consumption (ISFC), whereas, with a lower intake charge temperature, combustion stability deteriorates leading to incomplete OFC. By raising the intake charge temperature from 140 °C to 220 °C and applying 21% O2 and 79% CO2 v/v, the indicated thermal efficiency (ITE) is reduced from 34.6% to 29.2% while ISFC is increased from 0.24 to 0.285 Kg/kWh.

Multi-objective optimization of the performance and emission characteristics for a dual-fuel engine with hydrogen addition

In this work, multi-objective optimization of a dual-fuel engine with hydrogen addition was performed with a hybrid approach of RSM-NSGA II-TOPSIS. The optimization objective variables include NOx, CH4 emissions and indicated specific fuel consumption (ISFC); decision variables include H2 addition ratio, diesel injection timing (DIT), spray angle (SA) and swirl ratio (SR). Firstly, a computational fluid dynamics (CFD) model of a dual-fuel engine cylinder was established, and a chemical reaction mechanism containing 53 species and 325 reactions was developed by the CHEMKIN program. Then, a regression model of the objective variables was obtained by the response surface method and multi-objective optimization was performed by NSGA II genetic algorithm. Finally, the optimal solution was selected from the Pareto front by the TOPSIS decision method. The distribution of the Pareto front showed that a higher hydrogen addition ratio, DIT at 10-20° CA BTDC, SA at 90-110° and SR at 0.6–0.8 or 1.2 provided a better trade-off between the three objectives. The optimal solution can reduce NOx, CH4 emissions and ISFC by 8.21%, 61.64% and 4.59%, respectively, compared to the original solution. Optimization of.decision variables effectively mitigate the trade-off between NOx, CH4 emissions and ISFC for a dual-fuel engine with hydrogen addition at low loads.

Experimental study of gasoline engine with EGR dilution based on reactivity controlled turbulent jet ignition (RCTJI)

The exhaust gas recirculation (EGR) method can suppress knock and improve the thermal efficiency of engines, but it also deteriorates the combustion stability and engine power. Turbulent jet ignition (TJI) is a reliable ignition way for improving ignition stability and burning rate. However, the EGR in the pre-chamber will worsen the reactivity of the fuel-air mixture in the pre-chamber and subsequently lower the intensity of the TJI. To this end, the reactivity controlled turbulent jet ignition (RCTJI) based on a newly air-assisted pre-chamber turbulent jet ignition with a scavenging function has been proposed to improve the reactivity in the pre-chamber for the first time. The combustion characteristics, pressure oscillation, and combustion stability of a single-cylinder spark-ignition engine under four ignition modes of spark ignition (SI), passive TJI, active TJI, and scavenged TJI have been investigated. The results show that three TJI modes can obviously shorten the combustion duration due to the fast jet flame. Compared to the SI mode, the spark timing of TJI is not sensitive to the change in EGR rate. In particular, the scavenged TJI could effectively promote the chemical reactivity in the pre-chamber, and subsequently improves the intensity of the turbulent jet flame and shortens the ignition delay and combustion duration. As a result, using the scavenged TJI can effectively reduce cycle variation and achieve the lowest indicated specific fuel consumption (ISFC) at high EGR rates. However, with the increase in EGR rate, the SI combustion gradually becomes unstable. In contrast, the scavenged TJI can effectively extend the EGR tolerance. In addition, the present work further has confirmed the three main combustion stages of jet ignition in terms of the heat release rate.

The combustion and emission characteristics of a common-rail diesel engine fueled with diesel and higher alcohols blends with a high blend ratio

Experiments were conducted to investigate the effects of different alcohol additives on the combustion and emission characteristics of a diesel engine. Diesel was blended with four higher alcohols (propanol, butanol, pentanol, and hexanol) with a blend ratio of 40% by volume. To evaluate the engine performance at different engine loads, four loads ranging from 0.35 to 0.65 MPa IMEP (Indicated mean effective pressure) were conducted. Diesel/higher alcohol blends showed longer ignition delays and shorter combustion durations in comparison to diesel. Diesel had lower indicated specific fuel consumption (ISFC) values compared to diesel/alcohol blends. At the engine load of 0.35 MPa IMEP, Pr40 (40% propanol + 60% diesel) and Pe40 (40% pentanol + 60% diesel) had higher indicated thermal efficiency (ITE) than that of diesel. When the engine load increased to 0.45 MPa IMEP, Pe40 still had a larger ITE than diesel. Pe40 showed the highest ITE among the diesel/alcohol blends at different engine loads. The emission results showed that diesel/higher alcohol blends had higher NOx (oxides of nitrogen) and lower soot emissions than that of diesel under all test conditions. Overall, Pe40 and H40 (40% hexanol + 60% diesel) were good alternative fuel blends for diesel engines at high loads with only a slight trade off in combustion efficiency and NOx emissions.

Development cycle time reduction using design of experiments and machine learning-based optimization framework

In this study, we have developed an in-house design of experiments (DoE) and machine learning (ML) based optimization framework for the engine calibration process. The new framework was compared to the traditional “one factor at a time” (OFAT) calibration process. The calibration process was carried out in a single-cylinder research engine for 7 bar indicated mean effective pressure (IMEP) at 1500 rpm. The engine control parameters such as the rail pressure, exhaust gas recirculation (EGR), start, and duration of injections for main and pilot injections were optimized to minimize indicated specific fuel consumption (ISFC) and smoke under constraint limitations of indicated specific oxides of Nitrogen (ISNOx), maximum in-cylinder pressure (Pmax), peak pressure rise rate (PPRR) and IMEP. The engine control parameters were optimized for the same load and speed conditions individually by two approaches for comparison. Machine learning models were built on the data obtained from both approaches. The ML models were used as a surrogate for experiments to screen the entire design space to optimize the objective function. Then, the optimized control parameters were validated through experiments. The machine learning-based optimization approach facilitated unraveling the global optimum faster. The DoE-ML-based process was able to identify a combination of control parameters which yielded a 14.7 g/kWh improvement in ISFC with other target parameters within the acceptable limits. Further, the DoE-ML-based optimization framework reduced the total number of experimental runs by about 40% compared to the OFAT-ML-based calibration process.

Numerical Assessment on the Influence of Engine Calibration Parameters on Innovative Piston Bowls Designed for Light-Duty Diesel Engines

The optimization of the piston bowl design has been shown to have a great potential for air–fuel mixing improvement, leading to significant fuel consumption and pollutant emissions reductions for diesel engines. With this aim, a conventional re-entrant bowl for a 1.6 L light-duty diesel engine was compared with two innovative piston designs: a stepped-lip bowl and a radial-bumps bowl. The potential benefits of these innovative bowls were assessed through 3D-CFD simulations, featuring a calibrated spray model and detailed chemistry. To analyse the impact of these innovative designs, two different engine operating conditions were scrutinized, corresponding to the rated power and a partial load, respectively. Under the rated power engine operating condition, a start of injection sensitivity was then carried out to assess the optimal spray–wall interaction. Results highlighted that, thanks to optimal injection phasing, faster mixing-controlled combustion could be reached with both the innovative designs. Moreover, the requirements in terms of swirl were also investigated, and a higher swirl ratio was found to be necessary to improve the mixing process, especially for the radial-bumps design. Finally, at part-load operating conditions, different exhaust gas recirculation (EGR) rates were analysed for two injection pressure levels. The stepped-lip and radial-bumps bowls highlighted reduced indicated specific fuel consumption (ISFC) and soot emissions values over different rail pressure levels, guaranteeing NOx control thanks to the higher EGR tolerance compared with the re-entrant bowl. The results suggested the great potential of the investigated innovative bowls for improving efficiency and reducing emissions, thus paving the way for further possible optimization through the combination of these designs.

Enhancement of mixture homogeneity for DI-CI engine to achieve Homogeneous Charge Compression Ignition (HCCI) combustion characteristics: a numerical approach

ABSTRACT Homogeneous Charge Compression Ignition (HCCI) engine is a new mode of engine combustion concept used for decreasing emissions like NOx and soot and to meet stringent emission norms. A numerical and modeling analysis of the performance and emission characteristics of a DI-CI engine is presented in this paper. The numerical analysis was carried out using CONVERGE CFD software. In this paper, four different engine parameters were considered, i.e., Compression Ratio (CR) (14.5 to 19.5), Exhaust Gas Recirculation (EGR) (0 to 30%), Fuel Injection Pressure (FIP) (200 to 280 bar), and Start of Injection (SOI) (17 to 29° CA bTDC). Response Surface Methodology (RSM) was used for developing the design matrix in the given parameter ranges. Results were analyzed in terms of NOx, soot emissions, and Indicated Specific Fuel Consumption (ISFC) with an objective of lowering ISFC, soot, and NOx. The statistical analysis showed that CR of 18.9, SOI of 25.89° CA bTDC, EGR of 24.9%, and FIP of 262.45 bar predicted as an optimum combination of operation parameters set. From the ANOVA analysis, it is observed that CR and SOI are the most influencing parameters on the output response parameters. The mixture homogeneity (i.e., Target Fuel Distribution Index (TFDI)) of air-fuel was improved by 19.2% for optimum configuration as compared to baseline configuration.