摘要
进行了进气管直接喷射式氢发动机中过量空气系数对其性能影响的研究,分析了过量空气系数对输出功率、氢燃料消耗率和NOx排放量的影响,试验表明过量空气系数对氢发动机性能有较大影响。基于神经网络在逼近动态系统输入和输出之间非线性关系的优势,运用BP神经网络对过量空气系数与输出功率和氢燃料消耗率的关系建模,仿真和试验结果的对比研究表明:模型能准确地得出各工况所需的最佳过量空气系数,可为优化控制氢发动机性能提供理论支持。
The effect of the excess air ratio on output performances, such as power, hydrogen consumption and NOx emission, of hydrogen engine of intake pipe injection was analysed and investigated. Experiment results show that the excess air ratio has large effect on performances of the hydrogen engine. Based on neural network＇s superiority in approximation to nonlinear relations between input and output of dynamic systems, the model of excess air ratio with power and hydrogen consumption was set up by BP neural network. The contrasting results of simulation and experiment show that the model can abstractly calculate the optimum excess air ratio of every situation in satisfactory calculating result, then that puts on a firm foundation to optimal controlling the hydrogen engine.
出处
《内燃机工程》
EI
CAS
CSCD
北大核心
2006年第3期39-42,共4页
Chinese Internal Combustion Engine Engineering
基金
美国GM中国科学研究基金(国家自然科学基金)(50322262)
河南省科技攻关计划项目(0424440049
0524260028)
清华大学汽车安全与节能国家重点试验室开放基金(KF2006-01)
郑州市科技计划项目(0528CYG21113)
