Optimization of a Spark Ignition Engine Knock and Performance Using the Epsilon-Constrained Differential Evolution Algorithm and Multi-Objective Differential Evolution Algorithm
Since the advent of the internal combustion engine, knock has been a vital issue limiting the thermal efficiency of spark ignition engines under heavy load conditions. The occurrence of knock is also directly influenced by several operating parameters simultaneously. In order to investigate the effe...
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| Vydáno v: | ACS omega Ročník 7; číslo 36; s. 31638 - 31650 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
American Chemical Society
13.09.2022
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| ISSN: | 2470-1343, 2470-1343 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Since the advent of the internal combustion engine, knock has been a vital issue limiting the thermal efficiency of spark ignition engines under heavy load conditions. The occurrence of knock is also directly influenced by several operating parameters simultaneously. In order to investigate the effects of multiple variables on economic performance and power performance under knock limits, this study adopts single-objective optimization and multi-objective optimization methods to optimize the engine operating parameters, including exhaust gas recirculation rate, exhaust valve timing, spark timing, and intake valve timing. The optimization aims to obtain maximum volumetric efficiency, brake mean effective pressure, and minimum brake specific fuel consumption on the knock limit. First, based on the bench test data at the operation point 2800 rpm and 11.42 bar, a one-dimensional simulation engine model is established in GT-power software and verified. Second, four engine operating parameters are input into the GT-power model as controlled parameters. The epsilon-constrained differential evolution algorithm and the multi-objective differential evolution algorithm are employed to optimize the above four parameters to minimize the knock index and the damage to engine performance due to knock suppression, respectively. Finally, the results show that the two optimization algorithms optimize four parameters. The results of the epsilon-constrained differential evolution algorithm indicate that the decreasing extent of the knock index is 73.3%. In addition, the decreasing extent of brake mean effective pressure is 10.2%. What is more, the increased brake specific fuel consumption is only 0.07%. The multi-objective differential evolution algorithm gives a set of nondominated Pareto optimal solution sets. The optimal solution has a 64.4% decrease in the knock index, a 5.78% decrease in brake mean effective pressure, and a 1.45% decrease in brake specific fuel consumption. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 2470-1343 2470-1343 |
| DOI: | 10.1021/acsomega.1c06678 |