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An Investigation Of Optimum Control Of A Spark Ignition Engine Fueled By Ng And Hydrogen Mixtures

机译:Ng和氢混合气为燃料的火花点火发动机的最优控制研究

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In this study statistical analysis methods were used for optimizing a spark ignition engine fueled by NG and hydrogen mixtures. Firstly designs of experiment and range analysis of the results have been carried out in order to improve the efficiency of experiments and reduce the workload. And then, a flexible model of this kind of engine that is catered to multidimensional optimization has been built. After that, the genetic algorithm is used to optimize the model. Finally the optimum control parameters of this operated point are determined to be hydrogen fraction 30-40%, excess air ratio 1.45-1.6 and ignition timing 20-22° BTDC at 1200 r/min, 0.4 MPa. The comparison of the optimized results and the original CNG performance showed that CH_4, CO, NO_x, and BSFC decrease by 70%, 83.57%, 93%, and 5%, respectively. This proved that the combination of artificial neural network and genetic algorithm is an effective way to optimize the hydrogen blend natural gas engine.
机译:在这项研究中,使用统计分析方法来优化由天然气和氢气混合物供能的火花点火发动机。为了提高实验效率和减少工作量,首先进行了实验设计和结果范围分析。然后,建立了适合多维优化的这种引擎的灵活模型。之后,使用遗传算法对模型进行优化。最后,确定该工作点的最佳控制参数为氢气分数30-40%,过量空气比率1.45-1.6和点火正时20-22°BTDC,转速为1200 r / min,0.4 MPa。优化结果与原始CNG性能的比较表明,CH_4,CO,NO_x和BSFC分别降低了70%,83.57%,93%和5%。证明了将人工神经网络与遗传算法相结合是优化混合氢天然气发动机的有效途径。

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