Improving the controllability of partial fuel stratification at low boost levels by applying a double late injection strategy

Yan, Zeng; Gainey, Brian; Hariharan, Deivanayagam; Lawler, Benjamin

doi:10.1177/1468087419896511

Cited by 7 publications

(2 citation statements)

References 40 publications

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“…The overall premixed charge in PFS mitigates the formation of NO x and soot emissions, while the fuel stratification provides some level of control over the combustion phasing and burn rate. 4 However, the low stratification level could still be one of the limiting factors for the high load operation characterized by high noise and a rapid heat release rate, where high boost level, 5 proper thermal treatment, or specific fuel characteristics to promote the j-sensitivity, 6 can still be somewhat challenging.…”

Section: Background Of Gasoline Compression Ignition (Gci)mentioning

confidence: 99%

A numerical evaluation and guideline for thermal barrier coatings on gasoline compression ignition engines

Yan

Levi

Sellnau

et al. 2022

International Journal of Engine Research

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The application of thermal barrier coatings (TBCs) for internal combustion engines has drawn more research attention in recent years due to the improved coating technology and advanced material properties. This paper presents the combination of thermal barrier coatings with an advanced combustion concept: gasoline compression ignition (GCI). This study aims to evaluate the coating performance with GCI combustion on Aramco’s light-duty GCI engine. The thermodynamic engine model has been established and collaborated with CFD results to investigate thermal barrier coatings for GCI with a PPCI-diffusion combustion strategy primarily at a load of 23.5 bar IMEPg. Two real-world coating materials were pre-selected as Gen.1 and Gen.2 candidates. The investigation consists of three main topics: the effect of coating thickness on GCI, the effect of intake boost on the performance of traditional coatings and temperature swing coatings, and the effect of combustion chamber coverage on engine performance. The result shows that the TBC thickness became the key parameter to optimize for TBC with GCI combustion mode, and in the end, 250–500 microns is recommended based on the temperature limit of ceramic material. It was also found that the high level of intake boosting could significantly alleviate the charge heating penalty. The coverage of piston, engine head, and both intake and exhaust valves should be applied to achieve the highest efficiency gains. It was found that the gain ratio from each chamber component can be drastically different at different loads.

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Section: Background Of Gasoline Compression Ignition (Gci)mentioning

confidence: 99%

A numerical evaluation and guideline for thermal barrier coatings on gasoline compression ignition engines

Yan

Levi

Sellnau

et al. 2022

International Journal of Engine Research

Self Cite

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“…The internal combustion engines will continue to be the major power sources, especially for heavy-duty trucks and off-road applications [3,4]. The new requirements of next generation engines are more efficient and cleaner combustion [5][6][7]. The use of updated tools to assist engine design, which can shorten the period of engine design and reduce development costs, is a new trend [8,9].…”

Section: Introductionmentioning

confidence: 99%

The Engine Combustion Phasing Prediction Based on the Support Vector Regression Method

Wang

Yang

Sun³

et al. 2022

Processes

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While traditional one-dimensional and three-dimensional numerical simulation techniques require a lot of tests and time, emerging Machine Learning (ML) methods can use fewer data to obtain more information to assist in engine development. Combustion phasing is an important parameter of the spark-ignition (SI) engine, which determines the emission and power performance of the engine. In the engine calibration process, it is necessary to determine the maximum brake torque timing (MBT) for different operating conditions to obtain the best engine dynamics performance. Additionally, the determination of the combustion phasing enables the Wiebe function to predict the combustion process. Existing studies have unacceptable errors in the prediction of combustion phasing parameters. This study aimed to find a solution to reduce prediction errors, which will help to improve the calibration accuracy of the engine. In this paper, we used Support Vector Regression (SVR) to reconstruct the mapping relationship between engine inputs and responses, with the hyperparametric optimization method Gray Wolf Optimization (GWO) algorithm. We chose the engine speed, load, and spark timing as engine inputs. Combustion phasing parameters were selected as engine responses. After machine learning training, we found that the prediction accuracy of the SVR model was high, and the R2 of CA10−ST, CA50, CA90, and DOC were all close to 1. The RMSE of these indicators were close to 0. Consequently, SVR can be applied to the prediction of combustion phasing in SI gasoline engines and can provide some reference for combustion phasing control.

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Characterization and sources of carbonaceous aerosols in southwest plateau of China: Effects of biomass burning and low oxygen concentration

Shi,

Wu,

Han

et al. 2024

Atmospheric Environment

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Improving the controllability of partial fuel stratification at low boost levels by applying a double late injection strategy

Cited by 7 publications

References 40 publications

A numerical evaluation and guideline for thermal barrier coatings on gasoline compression ignition engines

A numerical evaluation and guideline for thermal barrier coatings on gasoline compression ignition engines

The Engine Combustion Phasing Prediction Based on the Support Vector Regression Method

Characterization and sources of carbonaceous aerosols in southwest plateau of China: Effects of biomass burning and low oxygen concentration

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