Optimization of Injection Parameters for Diesel Engine during Transient Process Based on Response Surface Method and Genetic Algorithm

LOU Diming; ZHAO Chengzhi; YU Huayang; TAN Piqiang; HU Zhiyuan

doi:10.3969/j.issn.1001-2222.2017.02.008

Vehicle Engine ›› 2017, Vol. 0 ›› Issue (2) : 45-50. DOI: 10.3969/j.issn.1001-2222.2017.02.008

Optimization of Injection Parameters for Diesel Engine during Transient Process Based on Response Surface Method and Genetic Algorithm

LOU Diming1, ZHAO Chengzhi1, YU Huayang2, TAN Piqiang1, HU Zhiyuan1

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Abstract

Based on the bench test data, an approximate highprecision model of fuel injection parameters and performance during transient process for a diesel engine applied in engineering field was established by using response surface method. Then genetic algorithm was used to optimize injection parameters offline. Finally, the best optimized values of brake specific fuel consumption(BSFC), NO_xand PM emission by single objective methods were 180.23 g/(kW·h), 8.92 g/(kW·h) and 0.011 8 g/(kW·h), which decreased by 4.5%, 34.0% and 37.3% respectively. Pareto solution of double objective optimization showed that BSFC and PM emission were easier to optimize simultaneously comparing with BSFC and NO_x emission.Triple objective optimization results of BSFC, NO_xand PM emission based on the fitness function of weight factor were 184.70 g/(kW·h),12.62 g/(kW·h) and 0.012 2 g/(kW·h), which decreased by 2.1%, 6.6% and 35.3% respectively. With improved optimization model, the correspondent BSFC and PM emission of Pareto solutions for performance optimization were close to limit values of single objective optimization, but NO_x emissionwas still high.

Key words

diesel engine / transient / injection parameter / response surface method；genetic algorithm；optimization.

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LOU Diming, ZHAO Chengzhi, YU Huayang, TAN Piqiang, HU Zhiyuan. Optimization of Injection Parameters for Diesel Engine during Transient Process Based on Response Surface Method and Genetic Algorithm[J]. Vehicle Engine. 2017, 0(2): 45-50 https://doi.org/10.3969/j.issn.1001-2222.2017.02.008