Cylinder Pressure Research Articles

Investigation on efficient and clean combustion pre-injection strategy of a diesel/methanol dual direct-injection marine engine under full load

Diesel ignition in-cylinder direct-injection methanol marine engine has shown enormous application potential due to its superior fuel economy and lower carbon emission. However, with high vaporization latent heat in methanol and increasingly strict emission regulations, new injection strategy urgently need to be studied to further improve the engine performance. To explore the feasibility of achieving high-efficiency and low-emission combustion by using pre-injection strategy in a diesel/methanol dual direct-injection marine engine, a numerical investigation is conducted to understand the combustion development, the mechanism of forming unregulated emissions, and the influence of methanol pre-injection timing (SOMIpre) and methanol pre-injection ratio (MPR) on engine performance. The results reveal that too early SOMIpre leads to a wet wall, while too late SOMIpre leads to insufficient mixing, thereby deteriorating combustion stability. The optimal fuel economy characterizing an indicated thermal efficiency (ITE) of 49.58% can be achieved when methanol is pre-injected at 35° crank angle (CA) before the top dead center (BTDC). As SOMIpre advances, the peak in-cylinder pressure (Pmax), peak heat release rate (HRRmax), and indicated mean effective pressure (IMEP) are decreased, along with increased soot, CO, and HC emissions, while the emissions of NOX and CO2 remain essentially unchanged. Additionally, the optimal methanol pre-injection strategy is yielded with an SOMIpre of 35°CA BTDC and an MPR of 15% when adopting a diesel injection timing (SODI) of 20°CA BTDC, increasing ITE by 19.9% and 2.7% and cutting CO2 emissions by 19.4% and 2.9% compared to the prototype (pure-diesel mode) and single-injection strategy. The results of this study provide new direction and data support for the research and development of efficient and clean combustion marine methanol engines.

Numerical investigation on the cold-start/restart process of a linear range extender for faster response

The free-piston linear range extender (LRE) system is an innovative energy conversion system characterized by a simple structure, high reliability, superior conversion efficiency, minimized energy loss, and excellent adaptability to various fuels. This paper establishes a numerical model for the cold start process of the LRE system, and experimental data are utilized to validate the model's accuracy. Subsequently, the influence of cylinder wall temperature on the cold start of the LRE system is investigated. Results reveal that increasing the cylinder wall temperature from 300K to 600K enhances system performance, evidenced by increased peak cylinder pressure (from 8.18 bar to 12.46 bar), peak piston speed (from 1.54 m/s to 1.91 m/s), and operating frequency (from 9.76 Hz to 11.66 Hz), alongside a reduction in ignition time (from 0.462 s to 0.229 s). Additionally, the required motor force for ignition decreases from 219 N to 194 N, showing a linear relationship with cylinder wall temperature. The study indicates that employing the cylinder wall heating method can decrease the motor force needed for ignition, leading to a notable enhancement in the system's cold start capability. This presents a promising strategy for quickly restarting the system following a misfire.

Experimental investigation on in-cylinder working process and thermal efficiency of ammonia/diesel low-carbon engine with pre-injection strategy

Ammonia, as a zero carbon and sustainable fuel, combined with traditional diesel fuel can provide a promising solution for reducing the engine environmental impact. However, ammonia/diesel dual-fuel (ADDF) engine has the significant drawback of low combustion efficiency and poor combustion stability at low loads, which seriously hinders its development. Therefore, this study explored the potential of pre-injection strategy in improving the performance of ADDF engine, comprehensively evaluating the effects of four pre-injection parameters (main injection timing (MIT), pre-injection timing (PIT), pre-injection quantity (PIQ), and diesel injection pressure (DIT)) on in-cylinder combustion process, incomplete combustion emissions, and energy efficiency. The results indicate that MIT has the most significant impact on combustion process. Advancing MIT can significantly increase in-cylinder combustion pressure and reduce CO, HC and unburned NH3 emissions. At MIT = -12 °CA ATDC, the highest brake thermal efficiency (BTE) of 32.3 % is obtained, while simultaneously generating high combustion noise. The advance of PIT has adverse effects on combustion stability. When PIT is advanced from −24 °CA ATDC to −36 °CA ATDC, COVIMEP increases from 2.61 % to 4.44 %, unburned NH3 emission increases by 23.5 %, and the BTE of ADDF engine decreases. Adjusting the PIQ and DIP can improve the reactivity distribution of fuel and reduce incomplete combustion emissions. However, the decrease in main injection quantity would increase the cycle fluctuation. At low loads, shortening the pre-main injection interval and increasing PIQ and DIP can enable the engine to achieve higher BTE while reducing pollutant emissions. This study elucidates in detail the influence of four pre-injection parameters on the operation characteristics of ADDF engine. It can offer insights and practical references for expanding the operating range of ammonia fuel engine.

Screening nano additives for favorable NOx/smoke emissions trade-off in a CRDI diesel engine fueled by industry leather waste fat biodiesel blend

The depletion of petroleum reserves and increasing environmental concerns prompted significant research into alternative fuels. This work, biodiesel, is extracted from the byproduct of industrial leather waste fat to generate beneficial energy.The main objective of this study is to enhance common rail direct injection (CRDI) diesel engine outcome characteristics by substituting industrial leather waste fat biodiesel (ILWFB) with the mixing of aluminium nitrate (Al (NO3)3) nanoparticles and graphene oxide nanoplates (GONPS) in the proportion of 50 ppm (parts per million) as catalysts to enhance ignition process. This research found that with the mixing of Al (NO3)3 nanoparticles and GONPS 50 ppm into the ILWFB blend, the in-cylinder pressure increased by 0.463% and 1.5%, and the heat release rate (HRR) improved by 4.19% and 12.04% than diesel and ILWFB blend at maximum load circumstances. Brake thermal efficiency (BTE) increased by 3.1% and 5.27%, and brake specific fuel consumption (BSFC) decreased by 3.57% and 7.14% in D50ILWFB50+Al (NO3)3 50 ppm blend and D50ILWFB50+GONPS 50 ppm blend related to diesel fuel. The carbon monoxide (CO), hydrocarbon (HC), and smoke emissions were reduced by 26.84%, 13.11%, and 5.75% in D50ILWFB50+Al (NO3)3 50 ppm blend and 38.94%, 21.31%, and 9.12% decreased in D50ILWFB50+GONPS 50 ppm blend than diesel fuel. Oxides of nitrogen (NOx) emissions marginally increased by 3.66%, 5.42%, and 8.94% in ILWFB blend, D50ILWFB50+Al (NO3)3, and D50ILWFB50+GONPSrelated to pure diesel at peak load conditions. This work concluded that the nano additives effectively enhanced BTE and decreased BSFC, CO, HC, and smoke emissions in diesel engine applications.

Predictive method of pressure loss in wet clutch caused by seal wear based on stacking ensemble learning

The harsh operating conditions of heavy-duty vehicles accelerates the wear of the sealing ring in the transmission, leading to increased oil leakage and a reduction of the operating pressure in the piston cylinder of wet clutch. This impairs the proper functioning of the transmission in the heavy-duty vehicle. Therefore, it is necessary to predict the pressure loss inside the transmission quickly and effectively after the wear of the sealing ring. The wear of the sealing ring under different operating conditions is calculated through the modified Archard model. The relationship between the oil leakage and pressure loss after the wear of the sealing ring is analyzed using Fluent software. The analysis involves the effects of different wear levels of the sealing ring. The simulation results are validated through a high-speed oil cylinder performance test rig. Based on the validated simulation data and test data, a prediction model for pressure loss is established by using stacking ensemble learning with MLR (multiple linear regression), DTR (decision tree regression), and SVR (support vector regression) as the base learners and RF (random forest) as the meta-learner. The risk of model overfitting is reduced through k-fold cross-validation. The research results indicate that the fused stacking ensemble learning algorithm fully utilizes the advantages of each base learner and can effectively predict the pressure loss after the wear of the sealing ring, and achieve a higher accuracy. The establishment of this model provides theoretical support for real-time prediction of pressure loss after the wear of the sealing ring in actual heavy-duty vehicles.

EXHAUST GAS ANALYSIS OF DIESEL - CADOBA FARINOSA FORSKK BIO-ETHANOL BLENDED FUEL SAMPLES RUNNING ON COMPRESSION IGNITION ENGINE

The world is facing declining liquid fuel reserves at a time when energy demand is exploding. As the supply decreases and costs rise, everyone will be forced to adopt the alternative energy resources. In order to achieve a secure and stable energy supply that does not cause environmental damage, renewable energy sources must be explored and promising technologies should be developed. This study investigates the effects of exhaust gases of diesel-Cadoba farinosa forskk bio-ethanol blended fuel samples run on a compression ignition engine. The test fuels were prepared; BDE2 (97% Diesel and 2% bio-ethanol volumetric proportion), BDE4, BDE6, BDE8 and BDE10 with 1% biodiesel (palm oil methyl esters) was maintained throughout to prevent phase separation of the ethanol and diesel respectively. The engine performance and exhaust gas analysis were also conducted to investigate the effect of bio-ethanol as diesel fuel extender, with a TD110-115 single-cylinder, four-stroke and air-cooled, compression ignition engine test rig, under different loading conditions, and incorporated with an SV-5Q automobile exhaust gas analyzer was used to monitor and measure the concentration of gaseous emissions, such as; exhaust gas temperature (EGT), carbon dioxide (CO 2), carbon monoxide (CO), and unburned hydrocarbon (HC) from the engine tail pipe. Results of the test revealed an appreciable increase in exhaust gas temperature of 16.66% due to the rise in cylinder pressure and temperature respectively. An appreciable decrease in HC, CO and CO 2 15.7%, 37.5% and 15% respectively emissions was recorded for all blended fuel samples with the exception of diesel. While, the least CO and CO 2 emission levels were observed for BDE10 fuel samples. On the account of its satisfactory engine performance behavior, fuel conservation advantages, and inherent greenhouse gas mitigation potentials, the candidacy of Cadoba Farinosa Forskk bio-ethanol and diesel blends, offers the promise of a prospective fuel for compression ignition engines.

Optimizing soybean biofuel blends for sustainable urban medium-duty commercial vehicles in India: an AI-driven approach

This article presents the outcomes of a research study focused on optimizing the performance of soybean biofuel blends derived from soybean seeds specifically for urban medium-duty commercial vehicles. The study took into consideration elements such as production capacity, economics and assumed engine characteristics. For the purpose of predicting performance, combustion and emission characteristics, an artificial intelligence approach that has been trained using experimental data is used. At full load, the brake thermal efficiency (BTE) dropped as engine speed increased for biofuel and diesel fuel mixes, but brake-specific fuel consumption (BSFC) increased. The BSFC increased by 11.9% when diesel compared to using biofuel with diesel blends. The mixes cut both maximum cylinder pressure and NOx\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{NO}}}_{{\ ext{x}}}$$\\end{document} emissions. The biofuel-diesel fuel proved more successful, with maximum reduction of 9.8% and 22.2 at rpm, respectively. The biofuel and diesel blend significantly improved carbon dioxide (CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{CO}}}_{2}$$\\end{document}) and smoke emissions. The biofuel blends offer significant advantages by decreeing exhaust pollutants and enhancing engine performance.Graphical

Development and evaluation of a process-oriented 3D finite element model for earth pressure balance shield tunneling

Thrust system performs the task of driving the shield machine forward and adjusting its posture, ensuring that the shield advances along a designed tunnel alignment. However, there is still no unanimously agreed approach for incorporating the thrust system in shield tunneling simulation. For this purpose, an attempt is made to embed the parallel mechanism properties of thrust system in simulation, i.e., modeling the thrust system as a 4-spherical-prismatic-spherical (4-SPS) branched chain. Meanwhile, a mesh-to-mesh solution mapping technique is introduced to ensure mesh compatibility across the cutterhead-soil interface without losing the stress history information generated during soil excavation. Thereby, a process-oriented 3D finite element model is developed for earth pressure balance (EPB) shield tunneling. The proposed model is quantitatively evaluated by reproducing a comprehensive field dataset collected from Changsha Metro Line 6 project. It is demonstrated that the proposed model can accurately reproduce the measured data for total thrust, grouped cylinder pressure, and total torque with mean relative errors of 5.8 %, 9.6 %, and 7.8 %, respectively. Moreover, the model can well reproduce the highly varied spatial distribution of the grouped cylinder pressure, highlighting its potential in capturing the mechanics for the posture variation of EPB shield.

A theoretical framework for the analysis of an opposed piston linear engine design

Traditional crank-based engines face limitations due to mechanical, thermal, and combustion inefficiencies. In contrast, the opposed piston design of a linear engine generator mitigates frictional losses by eliminating rotational motion and crankshaft linkages. Instead, electrical power is generated through the oscillation of a translator within a linear stator. However, the lack of geometric constraints in the free piston design leads to uncertainties regarding dead center positions, resulting in challenges such as misfire, stall, over-fueling, and rapid load changes.This study aims to fill this gap by reviewing existing modeling literature and advancing the fundamental understanding of opposed piston linear engines (OPLE) with springs through the development of an idealized, nondimensional model. A combination of analytical and numerical models was developed to better understand the behavior of the OPLE. The model introduces a streamlined symmetric analytical solution, succeeded by a broader general analytical resolution, with careful attention to the significant influence of thermodynamic effects at each phase, offering insights into the engine's dynamic performance. Limitations inherent to the analytical solutions are addressed by a numerical scheme utilizing the Runge-Kutta technique. This approach guarantees swift and dependable computational outcomes, which captures cyclic variation. The alternator model amalgamates both linear and sinusoidal work profiles, adjusting the magnetic work output in response to fluctuations in the compression ratio relative to the Top Dead Center (TDC) clearance distance. This adjustment dictates the generator load for each translator.The proposed model integrates the dynamics of a damped spring-mass system with thermodynamic expressions representing in-cylinder processes. Simplifications are made assuming perfect springs, ideal gases, instantaneous heat transfer, and an average friction force dependent on stroke length for work output. Selected cases are analyzed to elucidate the system's fundamental behavior, both within and outside the context of the Otto cycle, showcasing natural and forced stability over multiple operation cycles. Notably, enhancing the baseline cylinder pressure, or input heat relative to spring stiffness can elevate the work-to-heat ratio values. The attained work-to-heat ratio within compression ratio window of 16 is approximately 28 %. While this percentage may fluctuate in the context of general FPLE designs, the model developed for OPLE in this work plays a crucial role in maintaining the engine within this narrowly defined efficiency range, without compromising the potential performance demonstrated in this study. Differences in compression ratios provided intriguing insights into the dynamics of the translator and the in-cylinder thermodynamics of the interconnected system. Lower TDC clearance resulted in high translator displacement, velocity, and enhanced thermal efficiency.

Effect of Ammonia Addition on Combustion and Emission Characteristics of Diesel Engine Under Various Operating Conditions

ABSTRACT Ammonia is a carbon-free alternative fuel and a hydrogen carrier. Ammonia diesel dual fuel (ADDF) combustion mode is one of the promising ways to reduce carbon emissions in CI engines. However, present researches are mainly based on combustion and emissions for naturally aspirated diesel engine under specific operating condition. This paper aims to illustrate the impacts of replacing diesel with ammonia in a turbocharged diesel engine under various operating conditions. Hence, the effects of various ammonia substitution rate (ASR) on combustion and emission characteristics are numerically investigate by using GT-Power software for nine groups of different operating conditions with low, medium and high speeds and loads. Results show maximum 70% of input energy can be provided by ammonia for nine groups of different operating conditions, and the brake mean effective pressure (BMEP) and the indicated thermal efficiency (ITE) increases with the increase of ASR. Secondly, increasing ASR decreases the peak cylinder pressure (PCP) under different operating conditions, but increases the maximum pressure rise rate (MPRR) at certain operating conditions. Among them, under medium-speed and high-load conditions, the MPRR reaches the highest value, about 0.587 MPa/(°CA), but does not exceed 0.6 MPa/(°CA). Thirdly, increasing ASR changes the combustion mode from diffusion combustion in pure diesel operation to premixed combustion in dual fuel mode. Finally, adding ammonia reduces the NOx, CO and HC emissions, and the decrease is 15.2%–43.2%, 76.2%–82.3%, 70%–79.6%, respectively.

Experimental investigation of performance, emission, and combustion characteristics of a variable compression ratio engine using waste cooking vegetable oils blended with diesel

The availability of crude oil and petroleum products has become scarce and costly over the years leading to a stiff rise in engine fuel. Due to the depletion of conventional fuels; alternative fuels are gaining importance in recent times and Waste Cooking Vegetable Oils (WCVOs) are the viable option for the same. The present study highlights the performance, emission, and combustion characteristics of the Variable Compression Ratio (VCR) engine using three varieties of WCVOs (Ground Nut (GDN), Palm (PM), and Sunflower (SF)). Their inferior fuel features (density, viscosity, calorific value, etc.) are enhanced by blending 30 % of these oils with 70 % Diesel. The experiments are then conducted in the VCR engine using these blended oils under varying loading conditions (0–8 N) and at a constant speed of 1500 (RPM) with a compression ratio (18:1). It is seen that a single blend of Palm oil (PM) increases the engine Brake Thermal Efficiency (BTE) by 5 % in comparison to Diesel and other blended fuels (GDN, SF) owing to its lower calorific value and greater viscosity. The engine Brake Specific Fuel Consumption (BSFC) decreases with the increase in load and the lower loads reduce the BSFC for WCVOs by 9–15 % compared to Diesel. Engine emissions like Carbon Monoxide (CO), Nitrogen Oxide (NOx), and Hydrocarbons (HC) are also reduced significantly (by 12–15 %) using these blended oils compared to Diesel. The surge in both the Peak Cylinder Pressure (PCP) and Heat Release Rate (HRR) is also observed using these blended fuels, especially for Sunflower. Hence, these WCVOs are an appropriate option to advance the VCR engine performance and decrease its emissions.

Fracture Analysis and Repair of Last Stage Blade Reinforcement Boss for Low Pressure Cylinder Rotor of 330 MW Unit

The lace convex table of the final stage blade of a 330 MW turbine fractured. The reason was analyzed by fracture analysis, chemical composition analysis and metallographic analysis. It showed that the overload was the main reason for the fracture. Deformation of guide ring caused by fracture of guide ring bolt was the main reason of the overload. The analysis of the guide ring bolt showed that the brittleness of the guide ring bolt was the main reason for its fracture. It was suggested to strengthen the supervision of the manufacturing process of the guide ring bolt. The lace convex table was repaired by surfacing welding. A reasonable welding process was developed and the repair was successful.
 Abstract, Final stage blade, Lace convex table, Surfacing welding, Welding repair

Novel virtual sensors development based on machine learning combined with convolutional neural-network image processing-translation for feedback control systems of internal combustion engines

Physical sensors are commonly used to record performance data of internal combustion engines (ICEs) for online feedback control and calibration, but they are prone to diagnostic and increased development costs. Lookup tables are commonly used in conventional calibration and feedback control; however, the table parameters increase with the advancement of ICE technologies under transient operations. Consequently, the calibration and control systems are time-consuming. This work proposes novel virtual sensors to address these issues by predicting the combustion, performance, and emission of ICEs using neural networks and image processing/translation. The novel sensors are targeted for onboard feedback control systems under transient driving. Firstly, a virtual diesel engine (VDE) was developed and calibrated against experimental data taken from a production 2.2 L turbocharged diesel engine. The VDE was calibrated under WLTC, JC08, and NEDC transient operations and was used to generate teaching data. Next, the virtual sensors are developed using five machine learning (ML) regressors. The result shows that the coefficient of determination R2 from all ML regressors exceeded 0.94, and the XG-Boost outperforms other ML techniques with R2 > 0.977. XG-Boost parameter estimations were 8 times faster than that on a desktop simulation. Then, an image classification model using a deep convolutional neural network (D-CNN) is constructed, and the dependency of performance parameters and exhaust emissions with the rate of heat release (R.H.R) and in-cylinder pressure profile is confirmed. The performance parameters and emissions dependency was compared individually with R.H.R. and the in-cylinder pressure profile. As a result, a strong correlation between the performance and R.H.R. was observed. Finally, a generative adversarial network (GAN) model was constructed to translate the in-cylinder pressure profile to R.H.R. profile. A novel method to develop virtual sensors for advanced feedback control of any type of ICEs is proposed for the first time.

Data-Based In-Cylinder Pressure Model with Cyclic Variations for Combustion Control: An RCCI Engine Application

Cylinder-pressure-based control is a key enabler for advanced pre-mixed combustion concepts. In addition to guaranteeing robust and safe operation, it allows for cylinder pressure and heat release shaping. This requires fast control-oriented combustion models. Over the years, mean-value models have been proposed that can predict combustion metrics (e.g., gross indicated mean effective pressure (IMEPg), or the crank angle where 50% of the total heat is released (CA50)) or models that predict the full in-cylinder pressure. However, these models are not able to capture cycle-to-cycle variations. The inclusion of the cycle-to-cycle variations is important in the control design for combustion concepts, like reactivity-controlled compression ignition, that can suffer from large cycle-to-cycle variations. In this study, the in-cylinder pressure and cycle-to-cycle variations are modelled using a data-based approach. The in-cylinder conditions and fuel settings are the inputs to the model. The model combines principal component decomposition and Gaussian process regression. A detailed study is performed on the effects of the different hyperparameters and kernel choices. The approach is applicable to any combustion concept, but is most valuable for advance combustion concepts with large cycle-to-cycle variation. The potential of the proposed approach is successfully demonstrated for a reactivity-controlled compression ignition engine running on diesel and E85. The average prediction error of the mean in-cylinder pressure over a complete combustion cycle is 0.051 bar and of the corresponding mean cycle-to-cycle variation is 0.24 bar2. This principal-component-decomposition-based approach is an important step towards in-cylinder pressure shaping. The use of Gaussian process regression provides important information on cycle-to-cycle variation and provides next-cycle control information on safety and performance criteria.

Optimization and impact of modified operating parameters of a diesel engine emissions characteristic utilizing waste fat biodiesel/di-tert-butyl peroxide blend

This study comprehensively investigated the transesterification process of converting waste pork fat oil into biodiesel as a fuel for the common rail direct injection (CRDI) diesel engine. In addition, Di-tert-butyl peroxide (DTBP) is used as an ignition enhancer to minimize exhaust gas emissions. The test fuels are diesel and diesel-waste pork fat biodiesel (WPFB)-DTBP blend (B20DTBP10 by volume), were used to analyze the engine outcome parameters with modified engines operating conditions like various compression ratios (CRs 16, 17.5, and 19) and injection pressures (IPs 400, 500 and 600 bar) at maximum load. The experiment results revealed that higher CRs and IPs, the heat release rate (HRR) and cylinder pressure increased. The brake thermal efficiency (BTE) is enhanced by increasing CRs and IPs but lowered than neat diesel. Smoke opacity decreased while increasing CRs and IPs. At CR 19 and IP 600 bar, smoke opacity decreased by 18.29%, related to baseline diesel. Increasing CRs and IPs lowered HC and CO emissions, but increasing IPs increased both emissions. HC and CO emissions were lowered in CR 19 and IP 500 bar by 21.73% and 28.49% more than neat diesel. The lower CRs and IPs, the oxides of nitrogen (NOx) emissions decreased, but further increasing CRs and IPs, the NOx emissions increased. Compared to baseline diesel, NOx emissions decreased in CR 16 and IP 400 bar by 15.49%. It was discovered that with increasing CRs and IPs, the emissions decreased with a minor rise in NOx emissions. Furthermore, the experimental results matched the predictions of an artificial neural network (ANN) model. The research concluded that the blend B20DTBP10 with modified engine operating conditions CRs and IPs suits diesel engine operation.

In-cylinder pressure and vibration analysis on port fuel injected gasoline engine

Research on knocking combustion is vitally essential since it impacts engine performance regarding noise and emissions, fuel consumption, power density, and durability. Because of end-gas auto-ignition, current SI engines may experience conventional knock, which restricts increasing the compression ratio to increase thermal efficiency. Therefore, this paper examined the in-cylinder pressure and vibration of a port fuel-injected gasoline engine under knocking and non-knocking conditions. The heat release rate was calculated from pressure traces where the crank angle resolutions were not constant, and the conversion from the time domain to the frequency domain of knock sensor signals by using the Fourier Transform was performed. The result reveals that more heat is released during knocking combustion than during non-knocking combustion. When there is a knock, the temperature variation increases. This would facilitate the use of heat transfer studies to detect knock occurrences. Moreover, knocking is caused by an ignition timing that is too advanced, 22°BTC, compared to the non-knocking spark case, 14°BTC. In the frequency domain, the amplitude of the knocking combustion is higher than the amplitude of the non-knocking combustion, indicating the engine’s noise and vibration.

Estimation of Piston Surface Temperature During Engine Transient Operation for Emissions Reduction

Abstract Piston surface temperature is an important factor in the reduction of harmful emissions in modern gasoline direct injection (GDI) engines. In transient operation, the piston surface temperature can change rapidly, increasing the risk of fuel puddling. The prediction of the piston surface temperature can provide the means to significantly improve multiple-pulse fuel injection control strategies through the avoidance of fuel puddling. It could also be used to intelligently control the piston cooling jet (PCJ), which is common in modern engines. Considerable research has been undertaken to identify generalized engine heat transfer correlations and to predict piston and cylinder wall surface temperatures during operation. Most of these correlations require in-cylinder combustion pressure as an input, as well as the identification of numerous model parameters. These requirements render such an approach impractical. In this study, the authors have developed a thermodynamic model of piston surface temperature based on the global energy balance (GEB) methodology, which includes the effect of PCJ activation. The advantages are a simple structure and no requirement for in-cylinder pressure data, and only limited experimental tests are needed for model parameter identification. Moreover, the proposed model works well during engine transient operation, with maximum average error of 6.68% during rapid transients. A detailed identification procedure is given. This and the model performance have been demonstrated using experimental piston crown surface temperature data from a prototype 1-liter 3-cylinder turbocharged GDI engine, operated in both engine steady-state and transient conditions with an oil jet used for piston cooling turned both on and off.

Effect of multi ferrites nanoparticles added Terminalia bellirica biodiesel on diesel engine: Combustion, performance, and emission studies

The objective of current investigation is to assess the diesel engine performance, combustion, and emissions fuelled with bismuth ferrite codoped with zinc and manganese (BZnFMO) nanoparticles dispersed Terminalia bellirica biodiesel. BZnFMO nanoparticles were uniformly dispersed in B20 together with the surfactant and the dispersant at a concentration of 50 ppm and 75 ppm, respectively, and the stability of the nanoparticles in B20 was evaluated by UV photo spectroscopy. In addition, the experimental analysis of all nano-fuel samples was tested on diesel engines with different injection timing (i.e. 21°bTDC, 23°bTDC and 25°bTDC). The addition of nanoparticles in B20 led to an improvement in performance and combustion properties while simultaneously reducing emissions. The dispersion of BZnFMO nanoparticles in B20 led to a significant improvement in cylinder pressure (CP), cumulative heat release rate (CHRR), rate of pressure rise (RoPR) and brake thermal efficiency (BTE), while reducing brake specific fuel consumption (BSFC), carbon monoxide (CO), unburnt hydrocarbons (UHC), nitrogen oxides (NOx) and diesel engine smoke opacity. The increase in injection timing also led to an improvement in performance and combustion characteristics, as well as a reduction in emissions, with the exception of NOx. At 25°bTDC, a CP of 71.14 bar, a CHRR of 3.27 J/°CA and a RoPR of 5.3 bar/°CA were found, while BTE and BSFC were 35.03 % and 0.391 kg/kWh, respectively for B20 + 75 ppm BZnFMO + 75 ppm TWEEN 80. The values for CO, UHC, NOx, smoke opacity and nitrogen oxides were 0.01 %, 22 ppm, 826 ppm and 35.85 % respectively.

Study on backfire characteristics of port fuel injection single-cylinder hydrogen internal combustion engine

Hydrogen energy is one of the most promising sources of carbon neutrality from well to wheel. Among various applications of hydrogen energy, hydrogen internal combustion engines serve as the critical technical pathway. Nevertheless, several challenges persist, primarily related to abnormal combustion resulting from excessive flame propagation velocity. Of these challenges, backfire emerges as the most recurrent and pressing issue to be resolved in the port fuel-injected hydrogen internal combustion engine (PFI-H2ICE). In order to delve into the characteristics and mechanisms of backfire, this study concentrates on a critical internal parameter, namely the start of injection (SOI), and comprehensively assesses the backfire occurrences under varying lambda and engine speed conditions. Experimental findings reveal that SOI encompasses one of the pivotal factors influencing backfire. Backfire predominantly arises within two ranges of SOI conditions: the region before −430 degCA ATDC (Zone I) and the stretch between −360 degCA ATDC and − 280 degCA ATDC (Zone II). In the process of employing EGR to depress the effects of backfire on subsequent tests, it was incidentally found that the Universal Exhaust Gas Oxygen Sensor (UEGO) installed on the intake manifold for executing EGR rate calculations acted as a hotspot (with temperatures exceeding 100 °C). This not only intensified the backfire strength and the scope in Zone I but also caused the most severe backfire events to occur after −270 degCA ATDC (in Zone III). Despite this, the EGR strategy still demonstrated a significant backfire suppression effect, only exhibiting almost no influence on backfire caused by hotspots within the intake manifold. With an escalation in engine speed, the intensity of backfire diminishes, and the range of backfire occurrence decreases accordingly. By exercising control over SOI within the operating range from -430degCA to -360degCA ATDC (Zone A), the risk of backfire can be dramatically reduced, thereby achieving nearly backfire-free operation. Detailed analysis of cylinder pressure indicates that backfire may also give rise to other abnormal combustions, such as misfire, pre-ignition, and knock, in subsequent cycles. Moreover, this effect amplifies in tandem with an increase in mixture concentration. A certain degree of mutual promotion among diverse abnormal combustions is also observed. This study furnishes the most direct and practical foundation for internal and external strategies in the realm of backfire control.

Computational Fluid Dynamics (CFD) Validation and Investigation the Effect of Piston Bowl Geometries Performance on Port Fuel Injection-Homogeneous Charge Compression Ignition (PFI-HCCI) Engines

Computational Fluid Dynamics (CFD) Validation and Investigation the Effect of Piston Bowl Geometries Performance on Port Fuel Injection-Homogeneous Charge Compression Ignition (PFI-HCCI) Engines