微种群遗传算法在HCCI燃烧模型动力学参数标定中的应用

HCCI Engine Combustion Model Calibration Using Micro-Genetic Algorithm

介绍了一种新兴的高效全局寻优方法——微种群遗传算法,并采用该方法,同时结合CHEMKIN化学动力学软件中的SENKIN模块以及发动机零维单区模型,对新发展的正庚烷化学反应动力学简化模型(40种组分,62个反应)中的7个动力学参数进行了标定．模拟结果表明,标定后的简化动力学模型在当量比0．1～1．3,温度300～3000 K的范围,对着火时刻的预测与详细模型(544种组分,2 446个反应)吻合较好．

The micro-genetic algorithm, as a highly effective optimization method, is applied to calibrating a newly developed reduced chemical kinetic model （40 species and 62 reactions） for the homogeneous charge compression ignition （HCCI） combustion of n-heptane in order to improve its autoignition predictions under different engine operating conditions. The seven kinetic parameters of the calibrated modal are determined using a combination of the micro-genetic algorithm and the SENKIN program of CHEMKIN chemical kinetics software package. Simulation results indicated that the autoignition predictions of the calibrated model agree better with those of the detailed chemical kinetic model （544 species and 2 446 reactions） than the original model over the range of equivalence ratios from 0.1 to 1.3 and temperature from 300 to 3 000 K.