Model Based Control Method for Diesel Engine Combustion
With the increase of information processing speed, more and more engine optimization work can be processed automatically. The quick-response closed-loop control method is becoming an urgent demand for the combustion control of modern internal combustion engines. In this paper, artificial neural netw...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-11-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/13/22/6046 |
| _version_ | 1827701900003246080 |
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| author | Hu Wang Xin Zhong Tianyu Ma Zunqing Zheng Mingfa Yao |
| author_facet | Hu Wang Xin Zhong Tianyu Ma Zunqing Zheng Mingfa Yao |
| author_sort | Hu Wang |
| collection | DOAJ |
| description | With the increase of information processing speed, more and more engine optimization work can be processed automatically. The quick-response closed-loop control method is becoming an urgent demand for the combustion control of modern internal combustion engines. In this paper, artificial neural network (ANN) and polynomial functions are used to predict the emission and engine performance based on seven parameters extracted from the in-cylinder pressure trace information of over 3000 cases. Based on the prediction model, the optimal combustion parameters are found with two different intelligent algorithms, including genetical algorithm and fish swarm algorithm. The results show that combination of quadratic function with genetical algorithm is able to obtain the appropriate combustion control parameters. Both engine emissions and thermal efficiency can be virtually predicted in a much faster way, such that enables a promising way to achieve fast and reliable closed-loop combustion control. |
| first_indexed | 2024-03-10T14:43:49Z |
| format | Article |
| id | doaj.art-60d686189d3445b6aa7197d697af4201 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T14:43:49Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-60d686189d3445b6aa7197d697af42012023-11-20T21:31:04ZengMDPI AGEnergies1996-10732020-11-011322604610.3390/en13226046Model Based Control Method for Diesel Engine CombustionHu Wang0Xin Zhong1Tianyu Ma2Zunqing Zheng3Mingfa Yao4State Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaWith the increase of information processing speed, more and more engine optimization work can be processed automatically. The quick-response closed-loop control method is becoming an urgent demand for the combustion control of modern internal combustion engines. In this paper, artificial neural network (ANN) and polynomial functions are used to predict the emission and engine performance based on seven parameters extracted from the in-cylinder pressure trace information of over 3000 cases. Based on the prediction model, the optimal combustion parameters are found with two different intelligent algorithms, including genetical algorithm and fish swarm algorithm. The results show that combination of quadratic function with genetical algorithm is able to obtain the appropriate combustion control parameters. Both engine emissions and thermal efficiency can be virtually predicted in a much faster way, such that enables a promising way to achieve fast and reliable closed-loop combustion control.https://www.mdpi.com/1996-1073/13/22/6046closed-loop controldiesel combustionvirtual emission predictionartificial neural networkdiesel engine |
| spellingShingle | Hu Wang Xin Zhong Tianyu Ma Zunqing Zheng Mingfa Yao Model Based Control Method for Diesel Engine Combustion Energies closed-loop control diesel combustion virtual emission prediction artificial neural network diesel engine |
| title | Model Based Control Method for Diesel Engine Combustion |
| title_full | Model Based Control Method for Diesel Engine Combustion |
| title_fullStr | Model Based Control Method for Diesel Engine Combustion |
| title_full_unstemmed | Model Based Control Method for Diesel Engine Combustion |
| title_short | Model Based Control Method for Diesel Engine Combustion |
| title_sort | model based control method for diesel engine combustion |
| topic | closed-loop control diesel combustion virtual emission prediction artificial neural network diesel engine |
| url | https://www.mdpi.com/1996-1073/13/22/6046 |
| work_keys_str_mv | AT huwang modelbasedcontrolmethodfordieselenginecombustion AT xinzhong modelbasedcontrolmethodfordieselenginecombustion AT tianyuma modelbasedcontrolmethodfordieselenginecombustion AT zunqingzheng modelbasedcontrolmethodfordieselenginecombustion AT mingfayao modelbasedcontrolmethodfordieselenginecombustion |