Investigation of Emission Characteristics and Lubrication Oil Properties in a Dual Diesel–Hydrogen Internal Combustion Engine

García, Carlos Pardo; Orjuela-Abril, Sofia; Pabón-León, Jhon

doi:10.3390/lubricants10040059

Cited by 6 publications

(4 citation statements)

References 37 publications

(39 reference statements)

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“…The presence of oil in the combustion chamber, i.e., in the cylinder of IC engines, is not desirable because the combustion of oil intensifies the emission of unburned PM. On the other hand, the failure of the reciprocating air compressor due to the inflow of lubricant in the cylinder and downstream into the high air pressure line can cause the failure of the brake system, which is undesirable regarding the safety of traffic and road users [67,68]. As a contribution, the tribological optimization of the cylinder liner surface of the aluminum alloy reciprocating air compressor was realized.…”

Section: Contribution To Research In the Area Of Reducing Pm Emission...mentioning

confidence: 99%

Particulate Matter Emission and Air Pollution Reduction by Applying Variable Systems in Tribologically Optimized Diesel Engines for Vehicles in Road Traffic

Milojević,

Glišović,

Savić

et al. 2024

Atmosphere

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Regardless of the increasingly intensive application of vehicles with electric drives, internal combustion engines are still dominant as power units of mobile systems in various sectors of the economy. In order to reduce the emission of exhaust gases and satisfy legal regulations, as a temporary solution, hybrid drives with optimized internal combustion engines and their associated systems are increasingly being used. Application of the variable compression ratio and diesel fuel injection timing, as well as the tribological optimization of parts, contribute to the reduction in fuel consumption, partly due to the reduction in mechanical losses, which, according to test results, also results in the reduction in emissions. This manuscript presents the results of diesel engine testing on a test bench in laboratory conditions at different operating modes (compression ratio, fuel injection timing, engine speed, and load), which were processed using a zero-dimensional model of the combustion process. The test results should contribute to the optimization of the combustion process from the aspect of minimal particulate matter emission. As a special contribution, the results of tribological tests of materials for strengthening the sliding surface of the aluminum alloy piston and cylinder of the internal combustion engine and air compressors, which were obtained using a tribometer, are presented. In this way, tribological optimization should also contribute to the reduction in particulate matter emissions due to the reduction in fuel consumption, and thus emissions due to the reduction in friction, as well as the recorded reduction in the wear of materials that are in sliding contact. In this way, it contributes to the reduction in harmful gases in the air.

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Section: Contribution To Research In the Area Of Reducing Pm Emission...mentioning

confidence: 99%

Particulate Matter Emission and Air Pollution Reduction by Applying Variable Systems in Tribologically Optimized Diesel Engines for Vehicles in Road Traffic

Milojević,

Glišović,

Savić

et al. 2024

Atmosphere

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“…Another hydrogen-related concern is the oil properties derating due to the reaction of the activated hydrogen with lubricant and additives. In [14] Garcìa et al performed the analysis of the lubricant oil and of the smoke opacity in a compression ignition engine run in dual-fuel conditions with diesel fuel directly injected inside the chamber, and hydrogen fuel supplied via the intake port. Different load conditions and hydrogen flow rate values were tested.…”

Section: Commercial Gasoline Hydrogenmentioning

confidence: 99%

A Numerical Methodology to Test the Lubricant Oil Evaporation and Its Thermal Management-Related Properties Derating in Hydrogen-Fueled Engines

De Renzis,

Mariani,

Bianchi

et al. 2023

SAE Int. J. Engines

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<div>Due to the incoming phase out of fossil fuels from the market in order to reduce the carbon footprint of the automotive sector, hydrogen-fueled engines are candidate mid-term solution. Thanks to its properties, hydrogen promotes flames that poorly suffer from the quenching effects toward the engine walls. Thus, emphasis must be posed on the heat-up of the oil layer that wets the cylinder liner in hydrogen-fueled engines. It is known that motor oils are complex mixtures of a number of mainly heavy hydrocarbons (HCs); however, their composition is not known a priori. Simulation tools that can support the early development steps of those engines must be provided with oil composition and properties at operation-like conditions. The authors propose a statistical inference-based optimization approach for identifying oil surrogate multicomponent mixtures. The algorithm is implemented in Python and relies on the Bayesian optimization technique. As a benchmark, the surrogate for the SAE5W30 commercial multigrade oil has been determined. Then, this multicomponent surrogate and a SAE5W30 pseudo-pure are compared by means of an oil film model, which accounts for oil heat exchange with the cylinder wall and the gases from hydrogen combustion, and its evaporation. The results in terms of oil film temperature, viscosity, and thickness under hydrogen-engine boundaries are evaluated. Analyses reveal that the optimized multicomponent mixture behavior is more realistic and can outperform the pseudo-pure approach when the oil phase change and the oil-in-cylinder presence must be considered.</div>

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“…Engine oil analysis constitutes a crucial aspect of diesel engine and lubricant maintenance. , Alterations in the physical and chemical properties of lubricating oil can be induced by various factors, including the utilization of hydrogen in diesel engines, the application of biodiesel in diesel engines, and the prolonged use-induced degradation of engine oil . Consequently, the identification of contaminants in oil through lubricant analysis allows for the recognition of initial component wear before failure occurs .…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Soft Computing Models for Predicting Viscosity in Diesel Engine Lubricants: An Alternative Approach to Condition Monitoring

Pourramezan,

Rohani,

Abbaspour-Fard

2023

ACS Omega

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The viability of employing soft computing models for predicting the viscosity of engine lubricants is assessed in this paper. The dataset comprises 555 reports on engine oil analysis, involving two oil types (15W40 and 20W50). The methodology involves the development and evaluation of six distinct models (SVM, ANFIS, GPR, MLR, MLP, and RBF) to predict viscosity based on oil analysis results, incorporating metallic and nonmetallic elements and engine working hours. The primary findings indicate that the radial basis function (RBF) model excels in accuracy, consistency, and generalizability compared with other models. Specifically, a root mean square error (RMSE) of 0.20 and an efficiency (EF) of 0.99 were achieved during training and a RMSE of 0.11 and an EF of 1 during testing, utilizing a 35-network topology and an 80/20 data split. The model demonstrated no significant differences between actual and predicted datasets for average and distribution indices (with P-values of 1.00). Additionally, robust generalizability was exhibited across various training sizes (ranging from 50 to 80%), attaining a RMSE between 0.09 and 0.20, a mean absolute percentage error between 0.23 and 0.43, and an EF of 0.99. This study provides valuable insights for optimizing and implementing machine learning models in predicting the viscosity of engine lubricants. Limitations include the dataset size, potentially affecting the generalizability of findings, and the omission of other factors impacting engine performance. Nevertheless, this study establishes groundwork for future research on the application of soft computing tools in engine oil analysis and condition monitoring.

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Investigation of Emission Characteristics and Lubrication Oil Properties in a Dual Diesel–Hydrogen Internal Combustion Engine

Cited by 6 publications

References 37 publications

Particulate Matter Emission and Air Pollution Reduction by Applying Variable Systems in Tribologically Optimized Diesel Engines for Vehicles in Road Traffic

Particulate Matter Emission and Air Pollution Reduction by Applying Variable Systems in Tribologically Optimized Diesel Engines for Vehicles in Road Traffic

A Numerical Methodology to Test the Lubricant Oil Evaporation and Its Thermal Management-Related Properties Derating in Hydrogen-Fueled Engines

Comparative Analysis of Soft Computing Models for Predicting Viscosity in Diesel Engine Lubricants: An Alternative Approach to Condition Monitoring

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