Manifold Absolute Pressure Research Articles

Effect of injection strategy on the hydrogen mixture distribution and combustion of the hydrogen-fueled engine with passive pre-chamber ignition under lean burn condition

Turbulent jet ignition (TJI) effectively achieves lean and stable combustion in hydrogen engines. However, research on injection strategies for TJI hydrogen engines is still lacking. In this study, experimental methods investigated the effects of single and split injection strategies on the combustion and emissions of TJI hydrogen engines under medium loads. The numerical simulation reveals the operational characteristics of fuel distribution, ignition capability, and energy conversion in the pre-chamber at different injection times in a single injection strategy. This work is conducted at 1600 rpm with a manifold absolute pressure of 70 kPa. The experimental results indicate that the delay of the start of injection (SOI) can enhance the performance of the TJI hydrogen engine. However, as SOI approaches TDC, emissions worsen, and combustion stability decreases. When SOI is 90°CA BTDC, the brake mean effective pressure (BMEP) and brake thermal efficiency (BTE) can achieve 3.1 bar and 32.9 %, with the coefficient of variation of the IMEP (COVIMEP) of 1.6 % and lower emissions. For the split injection strategy, delaying the secondary end of injection (SEOI) can increase BMEP and BTE. As SEOI gradually delays the TDC, emissions deteriorate sharply. Under the split injection strategy, COVIMEP is higher, which is unfavorable for hydrogen engine applications.

A comprehensive experimental study to analyze the cyclic variation of a hydrogen-blended ammonia engine with the Miller cycle

The effects of multiple operating parameters (including speed, valve timing, λ, manifold absolute pressure, spark timing, and hydrogen injection timing) on the coefficient of variation of indicated mean effective pressure (CoVIMEP) of a hydrogen-blended ammonia engine have not been adequately evaluated, which motivates this study. Specifically, CoVIMEP is decreased from exceeding 2.4 % to approximately 0.7 % when the speed increases from 1300 rpm to 2000 rpm. Optimizing valve timing keeps CoVIMEP below 0.8 % by improving the airflow exchange process, and the engine tends to realize lower CoVIMEP at close stoichiometric ratio conditions and low pumping loss. Furthermore, adjusting spark timing affects CoVIMEP by varying the ignition process's stability, with a combustion center of gravity around 9°CA ATDC being suggested. The hydrogen direct-injection timing influences the combustion process's instability by varying the mixture concentration gradient, and the late injection strategy allows the engine to achieve a CoVIMEP of less than 0.9 %.

1-D ENGINE MODELING OF 4-CYLINDER TURBOCHARGED GASOLINE ENGINE

This project is conducted to explore one-dimensional (1D) simulation for a 4-cylinder gasoline engine. The simulation and computational development of modeling for the study are conducted by using the commercial Computational Fluid Dynamics (CFD) of AVL BOOST software. The engine model was developed corresponding to a Proton 1.6-litre CamPro 4-cylinder turbocharged gasoline engine including the real engine geometry and parameters. The engine model is based on 1D equation of the gas exchange process, progressive engine combustion process, isentropic compression and expansion, and accounting for the heat transfer as well as the frictional losses. The aim of the study is to predict the steady-state performance of the engine model at full and partload conditions from 1000 to 5000 rpm by using engine cycle simulation. In this study, three parameter tuning works have been performed, which are combustion model tuning, intake manifold temperature tuning and turbocharger’s scaling factor tuning. In addition, the comparison and validation were done for the output performance parameters based on the provided experimental data. Overall, the engine performance behavior have been observed to determine how accurate AVL BOOST software can evaluate engine performance compare to experiment conducted on the real engine. The most accurate validation of the engine performance parameters have been achieved by manifold absolute pressure (MAP) with 3.14% error. However, by comparing with experimental data, major discrepancy is noticeable on several engine performance parameters. From this study, the results showed that the engine model is able to simulate engine’s combustion process and produce reasonable prediction.

Discussion on the potential of methane-hydrogen dual-fueled Wankel rotary engine

Wankel rotary engine (WRE) is welcomed due to its high power density and compact layout and is criticized due to its low efficiency and poor emission. To develop low-carbon emission and high-efficiency WRE, the present work discusses the potential of hydrogen/methane dual-fueled WRE with varied fuel components. The test was conducted at 1500 r/min, 80 kPa manifold absolute pressure and stoichiometric ratio. The results indicate that compared with pure hydrogen or pure methane WRE, hydrogen/methane dual-fueled WRE can achieve higher thermal efficiency and output power, the maximum values of which are 30.7% and 12.4 kW under test conditions, respectively. Besides, it also has satisfactory NO, CO2 and HC emissions. In particular, there is a linear relationship between NO emission and methane volumetric percentage with a 0.9949 determination coefficient in logarithmic coordinates, which means that the NO emission can be easily predicted. In addition, the cyclic variation is acceptable at maximum-efficiency CH4% and the knock can be almost eliminated in hydrogen-methane dual-fueled WRE when the volume ratio of methane exceeds about 40%. In general, WRE is recommended to be fueled by a mixture of hydrogen and methane with a high methane volumetric percentage.

Experimental study on Miller cycle hydrogen-enriched ammonia engine by rich-burn strategy

In order to achieve climate goals as soon as possible, it is necessary to reshape the energy mix to replace fossil energy with carbon–neutral fuels as soon as possible. Ammonia is a good medium for energy storage, has a large industrial scale and a well-developed infrastructure. To address the problems of NOx emission and low exhaust energy of ammonia-hydrogen engines, this study proposes a rich burn strategy. Firstly, a commercial spark ignition (SI) internal combustion engine (ICE) was modified to achieve a dual fuel supply of ammonia and hydrogen. The engine was run at a steady state of 1500 rpm with the intake manifold absolute pressure (MAP) maintained at 60 kPa, and the ammonia and hydrogen supplies were adjusted to achieve different mixing ratios and excess air ratios. The experimental results showed that the rich burn strategy could significantly reduce the NOx emission and increase the exhaust temperature of the ammonia-hydrogen engine when the excess air coefficient was below 0.8. The rich burn strategy can appropriately increase the engine power output, but it has some influence on the brake thermal efficiency (BTE).

Numerical study of the firing, radicals and intermediates in the combustion process of a H2-assisted combustion DISI methanol engine

The firing, radicals and intermediates in the combustion process of a port-injection hydrogen (H2)-assisted combustion direct-injection spark-ignition (DISI) methanol engine were numerically simulated. The engine with port-injection H2 plus direct-injection methanol was tested at 1800 rpm with intake manifold absolute pressure of 68 kPa. AVL-Fire coupling the detailed methanol chemical kinetics modeling with 21 components and 84 elementary reactions was used to simulate in this study. The model calculation results agreed well with the experiments, and the average error is less than 3% and can guarantee other outcomes. The simulation results show that high added H2 ratio (RH2) has higher turbulent kinetic energy in the region closer to the combustion chamber wall. When RH2 is greater than 6%, the formation time of fire core is obviously shortened and the average flame propagation velocity is significantly increased. Increasing RH2, the generation speed and the peak value of H, O and OH radicals increase, and higher concentration of radicals accelerates the diffusion of combustion from the hot flame zone. OH radical is a key reactant, which always plays a decisive role in the process of methanol oxidation. Effect of added H2 on methanol oxidation reaction is reflected in accelerating the initial stage of combustion and ameliorating the intensity of reaction. The mass fractions of HCHO, HCO and CO, as the main intermediate products, all show a trend of increasing first and then decreasing with the crank angle (CA), and their peak values indicate the phase of the most violent reaction. The peak values of HCHO and HCO are all near the top dead center (TDC), which is consistent with the trend of H and OH radicals generation rate. The relationship between consumption rate of methanol and CA shows that the consumption rate of methanol at RH2 = 9% is the earliest and steepest, and most of methanol has been consumed by reaction before TDC. Added H2 accelerates the fire propagation, H2 dominates the process of radical formation and methanol chain reaction, the flame spread period is shortened rapidly, and the effect of added H2 to promote combustion is obvious.

Experimental study on the effect of hydrogen substitution rate on combustion and emission characteristics of ammonia internal combustion engine under different excess air ratio

Reducing carbon emissions in the transport sector requires technology upgrades to engines and the use of carbon–neutral fuels. Ammonia is a zero-carbon renewable fuel that complements hydrogen. This study is based on a Miller cycle spark ignition engine using ammonia-hydrogen fuel. The effects of the mixture ratio of ammonia and hydrogen under stoichiometric ratio and lean burn condition on the performance of the Miller cycle engine are focused. First, a commercial Miller-cycle ICE was modified to allow a dual fuel supply of ammonia and hydrogen. The engine was run steadily at 1500 rpm with the manifold absolute pressure (MAP) maintained at 60 kPa, and the ammonia and hydrogen supplies were adjusted to achieve different mixing ratios and excess air ratios. The test results showed that an increased ammonia percentage under stoichiometric ratio conditions significantly improved the Braking mean effective pressure (BMEP) and Braking thermal efficiency (BTE) of the ICE. Under lean burn conditions, the changes of BMEP and BTE are small with the increase of the ammonia ratio. The exhaust temperature of the ammonia-hydrogen engine is relatively low, so it is necessary to consider matching a small inertia turbocharger. Ammonia ratios above 80 % by volume resulted in erratic engine operation and even misfires. Ammonia-hydrogen fuel blends lead to higher Nitrogen oxide (NOx) emissions.

Effect of HHO addition on combustion and emission in SI engine with butanol direct injection and gasoline port injection

As a renewable biofuel fuel with similar properties to gasoline, butanol can not only reduce the consumption of fossil energy, but also effectively improve the performance of engine. However, when the mixture ratio of butanol is large, the combustion of the mixture will deteriorate due to the high latent heat of butanol vaporization. In order to solve this problem, the HHO supply system was innovatively built on the basis of butanol/gasoline compound injection system. The HHO produced by the HHO supply system is sucked into the cylinder by the way of negative pressure in the cylinder. This system also forms a new intake system with the original intake system. In this research, the engine speed is 1500 rpm, manifold absolute pressure (MAP) is 42 kPa, and λ is 1. Five butanol direct injection ratio (BDIr), five HHO flux and six direct injection timing (DIT) are studied to observe the combination effects of butanol and HHO. The results show that under all test conditions, with the increase of HHO flux, indicated mean effective pressure (IMEP), peak in-cylinder pressure (Pmax) and NO increase, CA 0–10, CA 10–90, CO and HC decrease. When HHO flux increases from 0 to 16 L/min, IMEP increases by 4.84% and CO emission decreases by 22.52%. It is worth noting that this improvement is more obvious when BDIr >40%. HHO can effectively offset the negative impact of large proportion of butanol vaporization latent heat and improve the engine's tolerance to BDIr. Moreover, the engine performance gap between different DIT is also shortened with the addition of HHO, which reduces the engine's sensitivity to DIT. In addition, it can also be found that butanol can improve the surge of NO emission caused by HHO. When BDIr ≥60%, the NO emission after the introduction of HHO can be maintained at the original level or even lower. In general, biofuel butanol and clean fuel HHO can work together well and “16 L/min HHO +40% BDIr +60% GPIr +300 ° CA BTDC DIT” is the optimal combination of the BDI + GPI + HHO engine.

Estimating the charge burning velocity within a hydrogen-enriched gasoline engine

This paper proposed a feasible method for estimating the turbulent burning velocity of gasoline/hydrogen blends in a spark-ignited (SI) engine based on the cumulative heat release fraction, engine speed and engine geometry. The experiment was conducted on a naturally-aspirated port-injection gasoline engine equipped with a hydrogen injection system. The engine was run at 1400 rpm with different loads and hydrogen volume fractions in the intake gas. The test results showed that the addition of hydrogen benefited increasing the burning velocity and advancing the relevant crank angle for the peak burning velocity, due to the high burning and diffusion velocities of hydrogen. At 1400 rpm, a manifolds absolute pressure of 61.5 kPa and stoichiometric conditions, the peak burning velocity was raised from 11.6 to 12.3 and 14.6 m/s, and the relevant crank angle for the peak burning velocity was advanced from 21.0 to 14.0 and 8.6 oCA when the hydrogen volume fraction in the intake increased from 0% to 3% and 6%, respectively. Moreover, the effect of hydrogen addition on enhancing the burning velocity of a gasoline engine was more pronounced at low loads than that at high loads.

Multiple fault detection and isolation using artificial neural networks in sensors of an internal combustion engine

Technology advances rapidly in vehicles with internal combustion engines; therefore, detecting vehicles’ faults becomes more complex, primarily due to the increased usage of sensors and actuators to improve engine performance. Specialized instruments for detecting vehicle faults can sometimes show errors in multiple sensors when there is only one issue in the system, and they are not responsible for isolating faults. Then, it must add superior algorithms for fault detection and isolation (FDI) in the Internal Combustion Engine to these diagnostic instruments. For this reason, this research focuses on designing an individual and multiple fault detection and isolation system based on artificial neural networks for an internal combustion engine. The proposed scheme detects individual and multiple faults in the throttle position sensors (TPS), mass air-flow (MAF), and manifold absolute pressure (MAP). The FDI system uses five artificial neural networks (ANN). Each ANN estimates the value of two sensors using the engine speed and the air–fuel ratio (AFR) signal to generate analytical redundancy. When a sensor fault occurs, the FDI system substitutes the faulty signal with a healthy signal estimate provided by an ANN. Suppose a second fault arises in another sensor. The FDI system can replace the faulty signal with the ANN’s estimated signal, allowing the internal combustion engine to run even with multiple faults.

Dynamic individual-cylinder analysis of a Gasoline Direct Injection engine emissions for cold crank-start at elevated cranking speed conditions of a Hybrid Electric Vehicle

The cold crank-start phase significantly contributes to the engine-out total emissions during the US Federal Test Procedure (FTP). A Gasoline Direct Injection (GDI) engine dynamics and emissions are investigated during the first three engine cycles of the cold crank-start in Hybrid Electric Vehicle (HEV) elevated cranking speed at 20 °C. To this end, the impact of the operating strategy on the individual-cylinder engine-out emissions is analyzed quantitatively. For this purpose, a new dynamic method was developed to translate the engine-out emissions concentration measured at the exhaust manifold outlet to mass per cycle per cylinder. The HEV elevated cranking speed provides valve timing control, throttling, and increased fuel injection pressure from the first firings. This study concentrates on analyzing the cranking speed, spark timing, valve timing, and fuel injection strategy and parameters effect on engine-out emissions. Design of Experiment (DOE) method is used to create a two-step multi-level fractional-factorial test plan with a minimum number of test points to evaluate the significant parameters affecting engine-out emissions during cold crank-start. Out of the first step DOE analysis, the optimal cranking speed, spark timing, and valve timing, which results in the lowest unburnt HydroCarbon (HC) and NOx emissions, are distinguished. Then, fixing the first step parameters at their optimal values, the second step is accomplished with the fuel injection parameters sweep. The split injection parameters, including the Start of the first Injection (SOI), End of the second injection (EOI), and split ratio (SR), in addition to the first cycle additive fuel factor, are investigated. Results show that the high cranking speed with stabilized low Manifold Absolute Pressure (MAP), highly-retarded spark timing, high valve overlap, late intake first injection, 30 CAD bTDC firing EOI, and low first cycle fuel factor reduces the HC emissions 94%.

A Comparative Study of Design of Active Fault-Tolerant Control System for Air–Fuel Ratio Control of Internal Combustion Engine Using Particle Swarm Optimization, Genetic Algorithm, and Nonlinear Regression-Based Observer Model

In this article, three distinct strategies for designing an Active Fault-Tolerant Control System (AFTCS) for Air-Fuel Ratio (AFR) control of an Internal Combustion (IC) engine in a process plant to avoid engine shutdown, are presented. The proposed AFTCS employs a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a Nonlinear Regression (NLR)-based observer model in the Fault Detection and Isolation (FDI) unit for analytical redundancy. A comparison between these three proposed techniques is carried out to determine the least expensive and most accurate approach. The results show that the nonlinear regression produces highly accurate results by consuming very low computational power, and its response time is also very low as compared to GA and PSO. The results obtained show that NLR requires 99.6% and 93.1% less computational time for throttle and MAP estimation, respectively, by reducing the estimation error to as low as 0.01. The simulation of the proposed system is carried out in the MATLAB/Simulink environment. The results prove the superior fault tolerance performance for sensor faults of the AFR control system, especially for the Manifold Absolute Pressure (MAP) sensor in terms of less oscillatory response as compared to that reported in existing literature.

Monitoring of hydrogen-fueled engine backfires using dual manifold absolute pressure sensors

The application of hydrogen in internal combustion engines (ICE) has attracted widespread attention. However, due to the low ignition energy, high flame propagation speed, and wide combustible range of hydrogen, it is easy to cause abnormal combustion phenomena such as backfire in the port fuel injected (PFI) hydrogen-fueled engine. When a backfire occurs, the combustible mixture burns in the intake, resulting in a decrease in the volumetric efficiency of the engine, which may cause it to misfire or shut down in severe cases. Fast and accurate detection of backfire events is essential to take targeted control measures. In this research, a backfire detection system based on dual intake manifold absolute pressure (MAP) sensors were designed, with two MAP sensors installed on the intake manifolds of the first and fourth cylinders, and four gas injectors were installed on the intake manifold to convert the gasoline ICE into a hydrogen-fueled ICE. During the experiment, the engine speed was stabilized at 1000 rpm, the throttle valve was fully opened, and the intake pressure was maintained at 100 kPa.The test results show that the system can accurately determine the location and intensity of backfire occurrence. This method provides a basis for precise control of backfiring. • Set up two MAP sensors to monitor the backfiring of the hydrogen ICE. • MAP sensors allow accurate monitoring of backfiring. • Need to optimize valve strategy and injection strategy for hydrogen ICE.

Comparison and evaluation of advanced machine learning methods for performance and emissions prediction of a gasoline Wankel rotary engine

In order to improve the performance, reduce the emissions and enhance the calibration efficiency of a gasoline Wankel rotary engine (WRE), three advanced machine learning (ML) methods, including artificial neural network (ANN), support vector machine (SVM), and Gaussian process regression (GPR), were applied to develop the prediction model of the torque, fuel flow, nitrogen oxide, carbon monoxide, and hydrocarbon. The effect of feature numbers was examined using the recommended parameters of the ANN, SVM, and GPR models. It was concluded that using speed, manifold absolute pressure, and air fuel ratio as input parameters to build the prediction model performed best. The generalization ability of the three ML models was compared on the interpolative and extrapolative data sets using the extended recommendation parameters. The results showed that the GPR model performed the best generalization ability in scarce data sets and was simpler to train compared with ANN and SVM. The response surfaces constructed using the GPR model were very smooth and accurate, in which the coefficient of determination for all the predicted parameters was more than 0.99. It is strongly proposed that the GPR approach is a universal approach which will be an essential direction for WRE system control and surrogate model modeling.

Study of NOx emission for hydrogen enriched compressed natural along with exhaust gas recirculation in spark ignition engine by Zeldovich’ mechanism, support vector machine and regression correlation

The hydrogen fuel is an ideal fuel to achieve the zero-carbon emission for heavy-duty vehicles. The experiments have been conducted under a wide range of operating conditions at different ignition timings (0 to 60°CA bTDC), hydrogen fractions (0–40%) in CNG fuel, EGR ratios (0–35.8%), manifold absolute pressures (65–178 kPa), engine speed (700–2000 rpm) at stoichiometric condition. The calibrated quasi-dimensional combustion model has been applied for simulation of in-cylinder pressure and temperature of HCNG engine. These combustion parameters have been utilized in Zeldovich’ mechanism for the prediction of NOx emission. The mean absolute percentage error is 69.1573% and R2 = 0.8353 that is quite high. The support vector machine and regression correlation have been applied for NOx modelling of HCNG engine.The four sets have been formulated at different independent variables: controllable parameters (engine speed, load, ignition timing, EGR ratio and hydrogen fraction in CNG fuel), combustion parameters (maximum pressure, indicated mean effective pressure, coefficient of variation and combustion duration), working medium parameters (inlet temperature, exhaust temperature, manifold absolute pressure and temperature of the coolant) and mixed parameters. The different sets of brake specific NOx emission have been trained by support vector machine algorithm at different independent variables, combinations (5C2, 5C3, 5C4, 5C5), tuning parameters (penalty factor kernel, function width & intensive band loss function) and sample sizes (decrement & increment of sample sizes). The minimum MAPE for SVM is 4.7490% & R2 = 0.9981. The mathematical modelling has been carried out with utilization of suitable independent parameters, combination and sample size. The mean absolute percentage error for regression correlation is 18.2461% and R2 = 0.9619.

An Experimental Study on Combustion and Cycle-by-Cycle Variations of an N-Butanol Engine with Hydrogen Direct Injection under Lean Burn Conditions.

This study experimentally investigated the effects of hydrogen direct injection on combustion and the cycle-by-cycle variations in a spark ignition n-butanol engine under lean burn conditions. For this purpose, a spark ignition engine installed with a hydrogen and n-butanol dual fuel injection system was specially developed. Experiments were conducted at four excess air ratios, four hydrogen fractions(φ(𝐻2)) and pure n-butanol. Engine speed and intake manifold absolute pressure (MAP) were kept at 1500 r/min and 43 kPa, respectively. The results indicate that the θ0–10 and θ10–90 decreased gradually with the increase in hydrogen fraction. Additionally, the indicated mean effective pressure (IMEP), the peak cylinder pressure (Pmax) and the maximum rate of pressure rise ((dP/dφ)max) increased gradually, while their cycle-by-cycle variations decreased with the increase in hydrogen fraction. In addition, the correlation between the (dP/dφ)max and its corresponding crank angle became weak with the increase in the excess air coefficient (λ), which tends to be strongly correlated with the increase in hydrogen fraction. The coefficient of variation of the Pmax and the IMEP increased with the increase in λ, while they decreased obviously after blending in the hydrogen under lean burn conditions. Furthermore, when λ was 1.0, a 5% hydrogen fraction improved the cycle-by-cycle variations most significantly. While a larger hydrogen fraction is needed to achieve the excellent combustion characteristics under lean burn conditions, hydrogen direct injection can promote combustion process and is beneficial for enhancing stable combustion and reducing the cycle-by-cycle variations.

Effect of ammonia addition on combustion and emission characteristics of hydrogen-fueled engine under lean-burn condition

Hydrogen (H 2 ) is a carbon-free fuel with many excellent combustion characteristics, but abnormal combustion is one of the main obstacles to the promotion and application of hydrogen-fueled engines. This experimental study aims to investigate the suppression of the heat release rate (HRR) of a hydrogen-fueled engine through the addition of ammonia (NH 3 ). The engine was run at 1300 rpm, with manifold absolute pressure (MAP) of 61 kPa and NH 3 addition ratio of 0% and 2.2%, under lean-burn conditions. The results showed that the addition of small amounts of ammonia reduced the combustion rate of the fuel mixture, prolonged the flame development period (CA0-10) and propagation durations (CA10-90) of the engine, and reduced the peak in-cylinder pressure and peak HRR under lean-burn conditions. The addition of ammonia increased the peak indicated mean effective pressure (IMEP) and the peak indicated thermal efficiency (ITE) of the engine. The addition of ammonia resulted in increased nitrogen oxides (NOx) emissions. • The effect of ignition timing of an H 2 /NH 3 dual-injection engine was studied. • Reduces the peak heat release rate after ammonia was added. • CA0-10 and CA10-90 were extended after ammonia was added. • The peak IMEP and ITE were increased after ammonia was added.

Comparing different approaches for estimating tailpipe emissions in passenger cars

Vehicles with Internal Combustion Engines (ICE) still represent the most prevalent form of road transport in Europe, being an important source of both greenhouse gases and air pollutants. In response to these concerns, Portable Emission Measurement Systems (PEMS) have been widely used by researchers to measure tailpipe emissions and to detect cheating of emissions regulations by manufacturers. This paper introduces four different approaches to estimate carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for these vehicles. These approaches were based on: i) speed intervals (≤50 km.h-1, 50-90 km.h-1, ≥ 90 km.h-1); ii) internally observable variables (IOVs); iii) vehicle specific power (VSP); and iv) driving volatility indicators. The development of IOVs models was made by testing the most significant parameters on CO2 and NOx emission rates, which included the engine speed (RPM), manifold absolute pressure (MAP), and intake air temperate (IAT). VSP-modal approach centred on binning emission rates in 14 models that reflects deceleration, idling, cruise, and acceleration states. Driver volatility was characterized by means of vehicular jerk (i.e., first derivate of acceleration) using nine combinations of vehicular jerk types. To obtain real world emissions, data were collected from one petrol and one diesel passenger cars using an integrated PEMS. IOVs and jerk models based on the product of MAP and RPM presented similar CO2 emission compared to measured values for both vehicles, but they resulted in higher overestimation of NOx than a VSP-modal approach. The proposed methodology can be extended to other individual ICE or alternative fuel vehicles for which it may be expensive to get emissions, engine, and dynamic data.

Effect of ammonia addition on combustion and emissions performance of a hydrogen engine at part load and stoichiometric conditions

The development of alternative fuels is important in the fight against climate change. Both hydrogen and ammonia are renewable energy sources and are carbon-free combustible fuels. In a recent experimental study, the performance and emission characteristics of a spark-ignition engine burning a premixed hydrogen/ammonia/air mixture were evaluated. The manifold absolute pressure was adjusted to 61 kPa and the engine speed was stabilized at 1300 rpm. The difference between a mixture with a 2.2% volume fraction of ammonia and a pure hydrogen fuel was analyzed in comparison. Specifically, the addition of ammonia increased the ignition delay and flame development periods and reduced the rate of in-cylinder pressure rise. In conjunction with the ignition timing strategy, the addition of ammonia did not affect the engine performance. Nitrogen oxides emissions are increased due to the addition of ammonia. The experimental results suggest that ammonia can be used as a combustion inhibitor, which provides a new reference for the development of hydrogen-fuelled engines.

Study on combustion and emissions of a hydrous ethanol/gasoline dual fuel engine with combined injection

Hydrous ethanol has lower cost and energy consumption during the production process than anhydrous ethanol. Many researchers used hydrous ethanol instead of anhydrous ethanol to manufacture hydrous ethanol-gasoline. The water ratio in hydrous ethanol (ω) determines the energy consumption in the production process of ethanol. However, no one researched the effects of different ω on combustion and emissions of hydrous ethanol-gasoline. So, we prepared five kinds of ethanol with different ω (0, 5%, 10%, 15%, 20% vol.) to research the effects of ω on combustion and emissions. This study adopted combined injection with hydrous ethanol direct injection plus gasoline port injection (HEDI + GPI). The engine speed was 1500 rpm, and λ was 1, the intake manifold absolute pressure was 48 kPa, the direct injection ratio was 20%, five spark timings varied from 5 °CA BTDC to 25 °CA BTDC. The results showed hydrous ethanol prolonged flame development and propagation duration, decreased Tmax and Pmax, delayed APmax. Water increased COVimep, but using hydrous ethanol at the reasonable spark timing would not significantly affect the stability. Meanwhile, when the spark timing was MBT, compared with GE (gasoline/anhydrous ethanol dual fuel) fuel, as ω in GEW (gasoline/hydrous ethanol dual fuel) fuels increased, torque and brake thermal efficiency improved by 1.69%, 1.13%, −0.01%, −0.77%; HC increased by 2.13%, 9.02%, 23.89%, 37.15%; CO decreased by 41.95%, 28.56%, 5.59%, 2.46%; NOx decreased by 10.10%, −0.75%, −0.17%, 4.18%; total PN emissions decreased by 24.07%, 69.57%, 36.34%, 32.45%. Meanwhile, more water caused the size of particles to drop, made particles smaller.