Study on the Effect of Parameter Sensitivity on Engine Optimization Results

Kuo Jiang, Hong Zeng (), Zefan Wu, Jianping Sun, Cai Chen and Bing Han
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Kuo Jiang: Marine Engineering College, Dalian Maritime University, Dalian 116026, China
Hong Zeng: Marine Engineering College, Dalian Maritime University, Dalian 116026, China
Zefan Wu: Marine Engineering College, Dalian Maritime University, Dalian 116026, China
Jianping Sun: Marine Engineering College, Dalian Maritime University, Dalian 116026, China
Cai Chen: Marine Engineering College, Dalian Maritime University, Dalian 116026, China
Bing Han: National Engineering Research Center of Ship & Shipping Control System, Shanghai 200100, China

Energies, 2023, vol. 16, issue 23, 1-16

Abstract: The effects of six control parameters, intake valve opening timing (IVO), exhaust valve opening timing (EVO), compression ratio (CR), engine speed, intake temperature, and intake pressure on engine output power, indicated specific fuel consumption (ISFC), and nitrogen oxides (NOx) emissions, are analyzed through engine simulation. The six parameters were categorized into two groups based on the degree of influence: high influence (EVO, speed and intake pressure) and low influence (CR, IVO and intake temperature). The relationship between these two groups of parameters and power, ISFC and NOx emissions was explored. Optimization was carried out for each of the two groups of parameters, and the optimization of the high impact parameters resulted in a higher diversity and wider distribution of the solution set. On the other hand, the optimization of the low-impact parameters resulted in a more concentrated distribution of the solution set, while better reflecting the trade-off between the optimization objectives. For the optimal solutions for both sets of parameters, the high-impact parameters provided significant optimization performance compared to the standard operating conditions. Although power and ISFC were optimized, the optimal solution for the low-impact parameter performed poorly with a significant increase in NOx emissions. Therefore, the parameters should be evaluated for optimization using high impact parameters to improve engine performance.

Keywords: engine optimization; Box–Behnken design; response surface methodology; sensitivity analysis; MOPSO (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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