Cylinder Pressure Research Articles

Influence of ZnO and TiO2 nanoparticles on the performance, combustion and emission characteristics of diesel engine fueled with okra seed bio-diesel

Energy sector is demanding alternate fuel for conventional fuel to solve the problems like environmental pollution, Climate change and the exhaustion of fossil resources. Hence, the search of new fuel is paramount importance. This study aimed to identify a new fuel source from okra plants. Okra oil was extracted from okra seed and Okra biodiesel was prepared by transesterfication process. Okra bio-diesel was added with ZnO and TiO2 particles and its effects on diesel engine performance were examined. Performance study showed that B20 fuel exhibited the lowest BSFC of 0.34 kg/kWh and higher BTE of 33% among the biodiesel blends. Further, a lowest BSFC of 0.31 kg/kWh and BTE of 34% were observed for B20/50 ppm ZnO fuel. Combustion study showed that B20/50 ppm ZnO fuel exhibited the In-cylinder pressure and HRR of 71 bar and 54 kJ/°CA respectively. This is 5.9% and 8% increasing in In-cylinder pressure and HRR respectively, compared to B20 fuel. Emission study reported that the B20/50 ppm ZnO fuel showed the CO, HC and smoke release of 0.22 vol%, 40 ppm and 25 HSU respectively. This is 8.3%, 20% and 10.7% decrease in CO, HC, smoke release respectively, than B20 fuel.

Comprehensive wheel cylinder pressure estimation based on systematic hydraulic control unit model

Wheel cylinder pressure (WCP) is a crucial state for vehicles, directly influencing safety, comfort, and fuel economy. Serving as the foundation for sensor-less control and sensor redundancy, WCP estimation is a promising work for brake-by-wire systems (BBW). Nevertheless, WCP estimation is a challenging problem due to the nonlinear characteristics and intricate coupling within the hydraulic control unit (HCU). To enhance the performance of BBW, this paper proposes a comprehensive WCP estimation scheme based on the systematic HCU model. Component models including direct current (DC) motor pump and normally open valve (NOV) are established first. Considering the pulsation of the plunger pump, a modified nonlinear observer (MNO) is used to observe the angular speed of the DC motor. Inspired by the critical state, the linear pressure-drop relationship of NOV is analyzed and the NOV is simplified as a relief valve model expressed by algebraic equations. Dividing the HCU into the pump front part, pump rear part, and cylinder part, the systematic HCU model is then established, based on which, the comprehensive cause-based WCP estimation scheme is proposed. Next, simulations utilizing Amesim validate the angular speed estimator, while bench experiments prove the NOV model. Finally, vehicle tests under active and passive pressure regulating conditions are conducted. The results indicate the proposed scheme exhibits satisfactory performance while preserving computational efficiency.

Reduced chemical kinetics mechanism for modelling of n-Heptane/syngas combustion with NOx formation in a micro-pilot ignited dual fuel engine

A reduced chemical kinetics model was developed to simulate the combined combustion of n-Heptane with syngas, as well as the standalone syngas combustion and NOx formation in a pilot-ignited dual fuel engine. This simplified model comprises 75 different species and 276 reactions. Its accuracy was confirmed by comparing it with experimental data from existing literature and numerical results from established models. The comparison encompassed key factors such as ignition delay, the speed of combustion in a laminar flame, and the concentration profiles of NOx. The reduced model closely aligned with both experimental and simulated outcomes, particularly under conditions relevant to engine combustion.This reduced mechanism was then employed in a comprehensive computational fluid dynamics computations to predict syngas combustion in a dual-fuel engine that employs the injection of reduced amount of liquid n-Heptane fuel with subsequent micro-pilot ignition. The model accurately captured the necessary conditions for n-Heptane injection and the co-oxidation of syngas with n-Heptane. Moreover, it exhibited strong agreement with experimental measurements of the heat release rate (ROHR) and cylinder pressures. The study's results highlight that the reduced mechanism can precisely simulate combustion of syngas-based fuels in engine cylinder containing up to 57% hydrogen (H2) content. As a result, this simplified model is highly suitable for simulating engine conditions involving fuels derived from syngas.

Improving the combustion and emission performance of a diesel engine with TiO2 nanoparticle blended Mahua biodiesel at different injection pressures

Alternative fuels have sparked a lot of interest as oil deposits have decreased and environmental concerns have grown. Biodiesel is an alternative fuel that is being researched as a possible replacement for fossil fuels. A 4-stroke diesel engine's performance, combustion, and emission parameters were investigated in this work by changing the fuel injection pressure (180, 200, 220 and 240 bar) were studied using biodiesel obtained from Mahua oil at 20 % v/v blended with neat diesel (20% Mahua Biodiesel + 80 % Diesel) B20, then TiO2 nanoparticles added four concentrations are 25 ppm, 50 ppm, 75 ppm and 100 ppm. Performance characteristics such as BTE and BSFC of fuel samples were improved with TiO2 nanoparticles at higher injection pressure. Combustion characteristics were improved at lower injection pressure, B20T50 indicated near In-Cylinder pressure to diesel at 180 bar and B20T50 showed 5.3 % higher HRR compared to B20. TiO2 nanoparticles in the fuel blend gave positive results by decreasing emissions, CO and HC emissions were lower at small injection pressure. CO2 emissions were increased by 2.5 % and 4.4 % with B20T100 compared to diesel and B20. Maximum reduction of smoke opacity and NOx were observed at 240 bar FIP.

The effects of design parameters on the dynamic performance, in-cylinder pressure and electrical power generation of a free piston linear engine

Operation of a free piston linear engine is modeled based on the combination of three mathematical models, including a piston dynamic model, a linear alternator model and a thermodynamic model. The simulated in-cylinder pressure, piston velocity, and electric power output are compared with the corresponding experimental results to validate the models mentioned above. The influences of the design parameters, including cylinder dimension ( Le), number of coil turns ( N), and air gap ( g) between the translator and stator, on the dynamic performance, in-cylinder pressure and electric power generation of the free piston linear engine are studied. The study results show that the reduction of Le has a benefit for improving the piston dynamic performance and output electric power, however it also reduced the cylinder pressure. The increase of number of coil turns N results in the reduction of the peak piston velocity, displacement, acceleration, and pressure in the cylinder, however, it increases the output electric power of the free piston linear engine. The peak piston velocity, displacement, acceleration, and pressure in the cylinder are considerably decreased when g is reduced. However, the reduction of g has a benefit to improve the output electric power of the free piston linear engine. The energy conversion efficiency can be maximized when g and Le are reduced, and N is increased.

Investigating the impact of n-heptane (C7H16) and nanoparticles (TiO2) on diesel-microalgae biodiesel blend in CI diesel engines.

Recent global challenges encompass profound environmental pollution and the depletion of finite fuel resources. In this study, the biodiesel used in the mixture was derived from Azolla pinnata microalgae oil through a trans-esterification reaction chosen for its high oil concentration. During the initial phase of the experiment, varying volumes of biodiesel (5%, 10%, and 15%) and n-heptane (5%, 10%, and 15%) were introduced to diesel to form a ternary fuel blend. The experimental outcome shows that an n-heptane and biodiesel mixture of 10% by volume would produce the best results. Next, experiments were carried out by incorporating 10, 40, and 80ppm titanium oxide (TiO2) nanoparticles (NPs) in a recommended ternary fuel blend. The experimental investigation showed that D80A10H10TNP40 (diesel 80% + biodiesel 10% + n-heptane 10% + TiO2 40ppm) caused a 7.21% increase in brake thermal efficiency (BTE) with a decrease in brake specific fuel consumption (BSFC) and brake specific energy consumption (BSEC) by 9.58% and 10%, respectively, compared to (diesel 80% + biodiesel 20%) D80A20. D80A10H10TNP40 exhibits lower emissions, with a significant reduction of 11.29% and 20.96% in carbon monoxide (CO) and unburnt hydrocarbons (UBHC), respectively. Nitrogen oxide (NOX) and smoke emissions were reduced by 3.3% and 11.13%, respectively, compared to D80A10H10. Furthermore, D80A10H10TNP40 demonstrated enhanced combustion properties, comprising a significant rise of 4.39% in-cylinder pressure (CP), 35.29% in heat release rate (HRR), and 25.05% in the rate of pressure rise (RPR). The findings of this investigation indicate that D80A10H10TNP40 exhibits enhanced efficiency, emission, and combustion properties compared to the D80A20 fuel.

Machine learning approaches for identification of heat release shapes in a low temperature combustion engine for control applications

This paper presents the application of machine learning classification algorithms to identify and classify different heat release rate (HRR) shapes to control the combustion for an optimal multi-mode low-temperature combustion (LTC) engine operation. Low-temperature combustion engine produces low nitrogen oxides (NOx) and soot emissions and offers high thermal efficiency. But high in-cylinder pressure rise rates limit the operating range of the LTC engine. Therefore, it is imperative to control combustion in the LTC engine for safe operation. To this end, the HRR traces for over six hundred engine operating conditions are classified using supervised (i.e., Decision Tree, K-Nearest Neighbors (KNN), and Support Vector Machines (SVM)) and unsupervised (i.e., Kmeans clustering) machine learning approaches to segregate different combustion regimes based on HRR shape. Kmeans clustering was not successful in classifying the HRR shapes. Among different supervised machine learning techniques, SVM has proved to be the best method, having an overall classifier prediction accuracy of 92.4% for identifying the distinct shapes using normalized HRR data. In addition, three classifiers have been trained based on the combustion parameters and control inputs. These classifiers are then used as scheduling variables to develop predictive models. A model predictive control (MPC) framework is developed to control multi-mode LTC engine on cycle-to-cycle basis. The MPC framework achieved the simultaneous reference tracking of combustion phasing (CA50) and indicated mean effective pressure (IMEP) while constraining maximum pressure rise rate (MPRR) below 8 bar/CAD.

Enhancement of Efficiency and Mitigation of Pollutan Emissions in a Compression Ignition Engine by the Utilization of Rice Bran Oil as Green Fuel

The current investigation involved the implementation of a research experiment aimed at assessing the operational and emission attributes of a compression ignition direct injection engine comprising a single cylinder. The engine was fuelled with rice bran oil (RBO), and its performance was analysed under different engine loads. The performance metrics that were analysed included the brake specific fuel consumption BSFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), and cylinder pressure. The exhaust emission parameters that were investigated include carbon monoxide (CO), carbon dioxide (CO2), hydrocarbons (HC), and oxide of nitrogen (NOX). The study compares the results obtained from an experimental investigation involving different variants of rice bran oil (RBO50, RBO75, RBO100) with those obtained from a diesel engine (RBO00). The lowest BSFC obtained for RBO100 is around 0.29 kg/kWh at maximum load conditions (75 %), while the highest obtained for RBO00 is 0.33 kg/kWh. For all operations of diesel and RBO blends, it was discovered experimentally that the BSFC increases until 25 % of engine load and then starts to decline as the engine load is raised. At normal engine load circumstances, RBO75 has the highest thermal efficiency, while RBO00 has the lowest. The high EGT reading of RBO50 blends was due to the high calorific value (CV) of the fuel blends, which produced more heat per unit mass than RBO75 and RBO100. RBO75 achieved the highest cylinder pressure under both half and full load scenarios. RBO00 (pure diesel) achieved the lowest cylinder pressure under both half and full load scenarios. RBO outscored diesel in terms of efficiency of engine. The exhaust emission characteristics that were assessed included NOX, CO2, HC, and CO. The experimental outcomes of the study using rice bran oil-based fuels, specifically RBO50, RBO75, and RBO100, are being contrasted with those of diesel fuel (RBO00). The findings indicate that emissions of CO, CO2, HC, and NOX are lower when using RBO75 and RBO100 compared to diesel fuel. Furthermore, an analysis was conducted to determine the HC emissions of both RBO75 and RBO100 fuels at two distinct engine speeds, specifically 3500 rpm and 2000 rpm. The HC emission level for RBO75 was observed to be at its peak of 211 ppm when the engine speed reached 3500 rpm. The RBO50 fuel exhibits lower levels of CO emissions, measuring at 1.2% (3500 rpm) and 0.32% (2000 rpm). Similarly, CO2 emissions are also reduced with RBO50, measuring at 8.3% (3500 rpm) and 6.9% (2000 rpm). These exhaust emission reductions are observed when comparing RBO50 to diesel (RBO00) and other fuel mixtures, under a 75% load condition. Elevated levels of NOX emissions were detected in diesel fuel (RBO00) at concentrations of 499 ppm (3500 rpm) and 599 ppm (2000 rpm). In comparison to other fuels such as RBO50, RBO75, and RBO100, these higher NOX emissions were noted. In summary, the emission properties of RBO were shown to be superior to those of diesel fuel. The optimal blend for emissions reduction, including CO2, CO, NOX, and HC, was determined to be RBO50.

The influence of plastic pyrolysis oil on fuel lubricity and diesel engine performance.

This study investigates the viability of using plastic oils derived from High-density polyethylene (HDPE), Polypropylene (PP), and Polystyrene (PS) as alternative fuels for diesel engines. The research focuses on comparing the physical and chemical properties, fuel lubricity, engine performance, combustion characteristics, and exhaust emissions of these plastic oils. Analysis revealed that PS exhibits different fuel properties compared to diesel, with a carbon range distribution similar to gasoline, while HDPE and PP properties closely resemble diesel fuel. To prevent potential engine damage, PS was excluded from engine tests. PP displayed the best fuel lubricity, attributed to its higher kinematic viscosity and sulphur content, reducing direct friction. Diesel followed, with PS and HDPE in decreasing order of lubricity. Diesel's lubricity was influenced by the 7% palmitic methyl ester content in the fuel. In engine tests, HDPE demonstrated BTE similar to diesel, while PP exhibited lower BTE due to combustion retardation, leading to increased energy losses and higher BSFC. The combustion characteristics, in-cylinder pressure, and heat release rate of HDPE closely resembled diesel, while PP showed significantly delayed combustion due to low oxygen content and higher kinematic viscosity. Notably, NOX emissions from PP were lower than diesel and HDPE at all engine loads due to heat losses, resulting in a low in-cylinder temperature unsuitable for NOX emission. HDPE produced higher NOX emissions than diesel at low and middle loads due to its higher H/C ratio, promoting high thermal NOX formation. HC emissions from both HDPE and PP were higher than diesel due to increased fuel supply, hindering chemical bond breakdown. Similarly, CO emissions increased for HDPE and PP due to insufficient time for complete combustion, with HDPE producing more CO due to its heavy composites and lower cetane index. Smoke emissions from both HDPE and PP surpassed diesel, attributed to lower oxygen and higher sulphur content, leading to increased sulphurate particulate matter formation, and lower fuel density referring to the high amount of fuel supplied to the engine.

Technical Feasibility of Dimethyl Ether-Fueled Mechanical Fuel Injection System-Equipped Multicylinder Compression Ignition Engine

Abstract This experimental study evaluated the combustion and performance characteristics of a 100% dimethyl ether (DME)-fueled multicylinder compression ignition engine equipped with a customized mechanical fuel injection system. The engine operating envelope covered different engine loads and speeds. The effect of DME's physicochemical properties, such as density, compressibility, and latent heat of vaporization, on the engine combustion and performance characteristics was analyzed under varying engine loads and speeds. The DME-fueled engine exhibited an average of >8% higher brake thermal efficiency than the baseline diesel-fueled engine. DME's lower brake-specific energy consumption indicated that the DME-fueled engine efficiently converted fuel's chemical energy into mechanical energy compared to the baseline diesel-fueled engine. The in-cylinder pressure of DME was higher than that of the mineral diesel engine at low loads and lower at higher engine loads. DME engine exhibited extensive and reliable operating range and consistent performance. The mixing-controlled phase dominated the DME combustion. DME's higher compressibility led to a few distinct effects with respect to baseline diesel: (1) lower fuel line pressure in high-pressure fuel lines, (2) higher residual pressure oscillations due to higher compression energy stored in the high-pressure fuel lines, and (3) retarded actual injection timing. The variations in the engine speed showed a similar effect on DME's combustion and performance characteristics as baseline diesel. The DME-fueled engine's lower in-cylinder pressure, lower rate of initial pressure rise, and lower exhaust gas temperature indicate a lower heat rejection engine, delivering higher thermal efficiency.

Study on the Combustion and Emission Characteristic of a Heavy‐Duty Natural Gas/Ammonia RCCI Engine with Diesel Ignition

As a carrier of hydrogen, ammonia has great potential in reducing pollution and carbon. This paper investigates the impact of diesel compression ignition on the combustion and emission performance of a natural gas/ammonia mixture RCCI engine through numerical simulation. The energy fraction of ammonia is set from 0% to 100% in the study to evaluate the feasibility of ammonia application in heavy‐duty natural gas/diesel RCCI engines. A natural gas/n‐heptane/ammonia reaction mechanism that includes 89 species and 611 reactions was innovatively established, which can accurately simulate the ignition process. The results indicate that under all engine load conditions, as the ammonia energy fraction increases, the cylinder pressure and thermal efficiency of the engine decrease, and the power performance gradually weakens. Under high load conditions, when ammonia is added to premixed natural gas, as the ammonia energy fraction increases, the characteristic frequency near the resonance mode gradually disappears, which is beneficial for reducing the knock trend and ringing intensity of engines. However, due to the increase in incomplete combustion increase, the ammonia energy fraction should not be too large at high loads.

Optical investigation of low temperature combustion and soot emission characteristics of biodiesel/n-pentanol engine

Biodiesel/n-pentanol blend fuels have been regarded as the attractive alternatives for the utilization of diesel engines. However, the fundamental studies of low temperature combustion and soot formation characteristics of biodiesel/n-pentanol blend fuels in diesel engines are still scarce. The low temperature combustion and soot emission characteristics of pure waste cooking oil (WCO) biodiesel (B100) and 70% WCO biodiesel/30% n-pentanol blend (B70P30) were experimentally studied in an optical engine in the present study. Results reveal that B70P30 has longer ignition delays than B100 at low exhaust gas recirculation (EGR) rate, but the ignition delays of B70P30 become similar or even shorter when the EGR rate is over 12%. Adding n-pentanol into biodiesel increases the in-cylinder combustion pressure peak and maximum pressure rise rate. In addition, the delay in the appearance of ignition kernels and two-color images are observed for B70P30 fuel. In the initial stage of fuel combustion, B70P30 has less ignition kernels and lower soot KL factor distribution area. In the middle and late stages of combustion, flame area of B70P30 is small and flame brightness is weaker. Also, at the end of combustion, the two-color images of B70P30 show that the soot KL factor distribution around the periphery of the chamber is decreasing at a higher rate compare to B100.

Machine learning predictions on the output parameters of CRDI engines fueled with ternary blend

This study aims to employ a machine learning algorithm (MLA) to predict CRDI engine emissions and performance using alternative feedstock. This study started with a diesel-SCOME- Methyl Acetate ternary mix. The engine was tested with fuel injection time (FIT) of 23?, 21?, and 19? bTDC with exhaust gas recirculation (EGR) levels of 10%, 15%, and 20% at estimated power productivity. Retard injection time and increasing EGR rates reduced in-cylinder peak pressure. Operating conditions with the maximum BTE were 21? bTDC and 10% EGR. Adjusting injection time and EGR reduced nitrogen oxide relative to the baseline. Smoke opacity was 1% lower at 21? bTDC and 10% exhaust gas recirculation than in conventional diesel operation. Retard injection time and exhaust gas recirculation increased HC and CO emissions. However, MLAs predict CI engine operation and discharge properties. The long short-term memory (LSTM) Model predicts engine output characteristics with a squared correlation (R2) of 0.92 to 0.961. At the same time, mean relative error (MRE) values ranged from 1.74 to 4.68%. These results show that the LSTM models provide superior predictive capabilities in this investigation, particularly when considering numerous variables to analyse engine responses.

Early flame development characterization of ultra-lean hydrogen–air flames in an optical spark-ignition engine

Hydrogen-fueled internal combustion engines (H2ICEs) represent a promising technology for decarbonizing the transport sector. In pursuit of this goal, research is needed on lean hydrogen–air combustion under engine conditions aiming to mitigate NOx emissions. However, there is a limited amount of experimental data focusing on flame development at high pressure and temperature, especially in ultra-lean mixtures, which are recently considered to play an important role for future H2ICEs. This study investigates the behavior of very-lean to ultra-lean hydrogen–air flames (0.20 <ϕ< 0.55) in an optical spark-ignition engine, focusing on the early flame development phase. Fuel–air equivalence ratio and engine speed (900 <N< 1500 rpm) effects on hydrogen combustion are addressed with pressure-based heat release analysis and chemiluminescence flame imaging techniques. The findings revealed an intrinsic association between these two approaches. Hydrogen flames development measured before 2% of Mass Fraction Burned (MFB) strongly correlates with pressure-based quantities up to 50% MFB, underscoring the critical role of understanding the early flame phase for predicting total combustion duration and in-cylinder pressure traces. A model for hydrogen turbulent flames in the initial combustion stages is formulated based on the Zimont equation and the experimental data. An equation for 0D/1D combustion duration prediction up to 10% MFB is proposed, demonstrating its validity from the wrinkled flame to the well-stirred reactor premixed combustion regimes. Additionally, flame chemiluminescence images for each zone within the Peters–Borghi diagram are presented, offering valuable insights into the diverse characteristics of these flames.

Optical diagnostics and chemical kinetic analysis on partially premixed combustion characteristics fueled with methanol and various cetane improvers

The need for decarbonization has inspired the utilization of methanol in transportation industry. Via both experimental and modeling frameworks, this study, for the first time, reveals the ignition, heat release and flame development characteristics of methanol mixed with different cetane improvers, i.e., 2-ethylhexyl nitrate (EHN) and di-tertiary‑butyl peroxide (DTBP), under practical, advanced engine conditions. Particularly, a detailed chemical kinetic model is newly developed for methanol/EHN/DTBP mixtures, incorporating the most updated sub-chemistries for relevant fuel components and critical intermediates, to assist in further analysis on the effects of EHN and DTBP on ignition and emission formation under engine thermodynamic environments derived from recorded in-cylinder pressure histories. Results show that stable combustion of methanol/EHN mixtures can be realized under low direct injection (DI) pressure, high in-cylinder thermodynamic condition, featuring the lowest coefficient of variation of indicated mean effective pressure (COVIMEP) of 1.46 %. Throughout the combustion process, the yellow and white flame dominates. At the same DI timing, methanol/EHN mixtures present shorter ignition delay, faster heat release rate (HRR) and more advanced combustion phasing compared with methanol/DTBP mixtures. At similar combustion phasing, the peak flame/OH* natural luminosity intensity of methanol/EHN mixtures is higher. KL factor, which is utilized to evaluate soot concentration, also shows similar trend, indicating higher sooting tendency of methanol/EHN mixtures. Flux analysis further highlights higher production of soot precursor (i.e., C2H2) with EHN than DTBP, primarily via the pathway of C2H4→ C2H3→C2H2. The active atmosphere created by the decomposition of EHN or DTBP has significant effects on decreasing methanol ignition delay in the early stage of their exothermic process, while the active atmosphere of EHN remains impactful whereas that of DTBP diminishes at later stages. The thermal atmosphere shows greater effects on methanol ignition at later stages of the exothermic process of EHN or DTBP decomposition than the early stages.

LES of pilot n-heptane ignition and its interaction with the lean premixed methane–air mixture in a dual-fuel combustion engine

Large eddy simulations of pilot fuel ignited, lean premixed, natural gas engines are performed to study the pilot-ignition process and its subsequent interaction with the premixed charge. The injection pressure (Pinj) and injection duration (Δinj) are varied (i.e. 800 bar/760μs, 800 bar/500μs, and 400bar/760μs) to study the impact of the injection process on the subsequent combustion evolution. Open-cycle simulations considering the full engine geometry are used to predict the in-cylinder flows, while combustion is modeled using a finite-rate chemistry model. In-cylinder methane (CH4) is shown to delay the low-temperature ignition of the pilot fuel, regardless of the pilot injection setting, which subsequently prolongs the overall pilot fuel ignition delay. Moreover, all simulated cases show the occurrence of back-supported combustion (BSC), where the burning of CH4-air mixture is “back-supported” by pilot fuel radicals. Despite both the 800 bar/500μs and 400 bar/760μs cases having the same injected pilot fuel mass, the peak in-cylinder pressure and burning rate of the premixed CH4-air mixture in the former case are higher. Higher Pinj and shorter Δinj lead to better mixing between the pilot fuel and the premixed CH4-air charge. Subsequently, this forms a larger volume of regions with elevated equivalence ratio due to the presence of pilot fuel (ϕ>ϕCH4) which, consequently promotes the formation of BSC. The impact of in-cylinder flow fields on the dual-fuel combustion process is investigated by performing two closed-cycle 800 bar/500μs cases with one assuming solid-body rotation and another without solid-body rotation (i.e. zero velocity field). In-cylinder flow field is shown to have a visible impact on the transition stage between the pilot ignition stage and the premixed flame propagation stage, but have an insignificant effect on the pilot fuel ignition process. In the transition stage, slower flame propagation is observed in the zero-velocity case. The results show that this is not only due to the turbulence effect on premixed flame but also due to differences in the volume and distribution of pilot fuels that impacts BSC.

Enhancing internal combustion engine fault detection through co-simulation with piezoelectric pressure measuring chains

This study undertakes a proof-of-concept investigation,employing a combination of physics-based and empirical models toanalyze an in-cylinder pressure piezo-electric measurement chain. Theprimary objective is to systematically characterize and comprehenddeviations arising from the components within the measuring chain. Themethod implemented elucidates the real-time capabilities of the measuringchain model, thereby refining raw measurement data to discern deviations(errors) in the measuring chain components. This endeavor is gearedtowards facilitating effective condition monitoring and enhancing systemreliability. We detail our approach, which integrates co-simulationtechniques with piezo-electric pressure measuring chains, to detect andmitigate faults within internal combustion engines. Through this approach,we develop a comprehensive understanding of the underlying dynamics ofthe measuring chain, allowing for automated parameter estimation usinggenetic algorithms. Our key findings reveal significant improvements infault detection accuracy, with a notable reduction in in-cylinder pressureerrors. This study not only contributes to advancing fault detectionmethodologies but also holds promise for optimizing engine performanceand reliability in various applications.

Experimental investigation of low temperature combustion in a diesel engine depending on injection advance and injection pressure

In this study, the performance parameters and emissions of a pre-mixed charge compression ignition were investigated under different injection pressures and injection advances. After the peak engine power was reached, reasonable decreases occurred in brake mean effective pressure at certain injection advances with the increase of injection advance, and dramatic decreases observed when interval was so exceeded. In addition mean indicated pressure and peak in-cylinder pressure were investigated. Considering the emissions, dramatic increases were observed in CO and total hydrocarbon, depending on the increase in the low temperature combustion regime. The NOx started a rapid downward trend after a certain injection advance value in the experimental region, but this effect did not occur at the de?sired level for specific NOx. It was observed that the NO2 to NOx ratio increased as the pre-mixed charge compression ignition became dominant and NO2 production increased among the total NOx. In the operating region where the low temperature combustion regime was dominant, the targeted reduction in NOx and particulate matter emissions was observed, but the desired reduction in specific emissions did not occur. In the low temperature combustion region, the combustion process was prolonged, initially reasonable changes occurred at performance parameters, but unacceptable results were observed at high injection pressures with excessive injection advances.

Numerical evaluation of ignition timing influences on performance of a stratified-charge H2/methanol dual-injection automobile engine under lean-burn condition

Influences of ignition timing (IT) on combustion, carbon monoxide (CO) and nitric oxide (NO) regulated emissions and formaldehyde (HCHO) and unburned methanol (CH3OH) unregulated emissions in a hydrogen (H2)/methanol dual-injection automobile engine under lean-burn condition were studied numerically. The results demonstrate that at lean-burn (excess air ratio = 2.0) condition, the peak cylinder pressure (PCP), peak heat release rate (PHRR) and peak cylinder temperature (PCT) all decrease with delayed IT, and their corresponding crank angles are also late; ignition delay (ID) and combustion duration (CD) decrease with delayed IT; CO, HCHO and CH3OH emissions increase with delayed IT, while NO emission decreases with delayed IT. At a fixed IT, PCP, PHRR and PCT for with adding 5 % H2 (RH2 = 5 %) are higher than those for without adding H2 (RH2 = 0 %), and their corresponding crank angles for RH2 = 5 % are earlier than those for RH2 = 0 %; ID and CD for RH2 = 5 % are lower than those for RH2 = 0 %. CO, HCHO and unburned CH3OH emissions for RH2 = 5 % are also much lower than those for RH2 = 0 %, while NO emission for RH2 = 5 % is also higher than that for RH2 = 0 %. The influence order of adding H2 to reduce emissions of engine is: CO > HCHO > unburned CH3OH.

Simulation and Optimization of Bus Interior Noise Based on Hybrid Method for Engine Vibration Load Identification

Buses are crucial for urban public transportation systems as they help reduce traffic congestion and promote environmental sustainability. The noise inside buses significantly affects the comfort and physical health of both drivers and passengers. Although numerous studies have focused on the interior noise of buses, few have explicitly addressed the methods of reducing bus noise through comprehensive bus simulation and testing. Challenges of the full bus simulation include obtaining accurate engine vibration loads and building the finite element model of the full bus. This study presents a comprehensive approach for analyzing and optimization bus interior noise caused by engine vibration excitation. A novel hybrid method is proposed to identify bus engine vibration load, combining experimental testing of engine cylinder pressure with multibody dynamics simulation. Structure–acoustic coupled simulations were conducted to predict bus interior noise based on a detailed finite element model of the full bus. The study demonstrates a strong correlation between simulation and experimental results, validating the accuracy and effectiveness of the proposed method. The primary causes of the interior booming noise were identified by simulation analysis and experimental diagnosis. Optimization analysis led to a notable noise reduction by adjusting the support stiffness of the drive shaft, body structure, and integrating rear leaf spring dampers. These processes contribute to the analysis and improvement of bus interior noise, ultimately enhancing bus ride comfort and promoting sustainable urban public transportation.