Optimization and study of performance parameters in an engine fueled with hydrogen
Optimization and study of performance parameters in an engine fueled with hydrogen
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DOI：
10.1016/j.ijhydene.2019.10.250
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发表时间：
2020
影响因子：
7.2
通讯作者：
J. Zareei;A. Rohani
中科院分区：
文献类型：
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作者：
J. Zareei;A. Rohani
发动机性能参数，包括燃料转换效率(FCE)、功率、扭矩和比油耗(SFC)，可以受到点火正时(IGT)、喷射正时(IT)和氢体积分数(H2%)等变量的影响。本文对不同体积比的H2/CNG混合燃料在不同转速下的点火和喷射正时进行了研究。为了验证模型的有效性，使用AVL FIRE软件对发动机的工况进行了模拟，并与试验结果进行了比较。经统计学比较，两者差异无统计学意义。同时，根据所研究的变量，利用支持向量机对发动机的行为进行了学习。支持向量机模型对FCE、功率、扭矩、SFC和CO的预测误差小于4%。采用遗传算法(GA)寻找最优的IGT、IT和H2%值，使发动机性能达到最优。因此，结果表明，发动机的最佳工况取决于发动机的转速。结果还表明，自变量(IT、IGT和H2%)使发动机性能最大化，同时使SFC和CO排放最小。因此，在本研究中，不同发动机转速下氢气的最佳使用量为20%至30%。
Engine performance parameters, including fuel conversion efficiency (FCE), power, torque and specific fuel consumption (SFC), can be affected by variables such as ignition timing (IGT), injection timing (IT) and hydrogen volume fraction (H2%). In this paper an engine fueled with different H2/CNG blend rations from 0 to 50% volume under ignition and injection timing at different speeds were investigated. For model validation, the engine operating conditions were simulated using the AVL fire software and compared with experimental results. The statistical comparison showed that there was no significant difference between them. Also, a support vector machine (SVM) was used to study the engine's behavior according to the variables studied. The SVM model predicted the FCE, power, torque, SFC and CO with error of less than 4%. The Genetic Algorithm (GA) was used to find optimal IGT, IT and H2% values to achieve optimum engine performance. Therefore, the results showed that the optimum engine operating conditions depend on the engine speed. Also, the results showed that independent variables (IT, IGT and H2%) maximize the engine performance and minimize SFC and CO emission. So that the optimum use of hydrogen in this research at different engine speeds was between 20% and 30%.