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煤层气发动机稳态排放预测模型的辨识建模研究
Study on Identification Based Model for Predicting Exhaust Emission of the Coal-bed Gas Engine under Steady State Operation Condition
【摘要】 基于排放测量数据,采用量化共扼梯度法(SCG)建立了煤层气发动机的BP神经网络排放预测模型,检验结果证实了模型的准确性。为全面了解煤层气发动机的排放特性和制定合理的排放控制策略,借助于该模型,通过模拟研究对发动机的排放性能进行了预测,并分析了预测结果。
【Abstract】 A BP neural network model for predicting exhaust emission of the coal-bed gas engine under steady-state operation condition was established based on exhaust emission experiment data using Scaled Conjugate Gradient(SCG) method.The results show that the simulation data and the measured data was in good agreement and the model was accurate enough.In order to know the emission performance of the coal-bed gas engine and get proper control strategy,the model was used to predict emission performance of the coal-bed gas engine by means of simulation study based on this model.And some prediction results are presented.
【Key words】 Coal-bed Gas Engine; Exhaust Emission; Prediction Model; Scaled Conjugate Gradient Method;
- 【文献出处】 内燃机与动力装置 ,Internal Combustion Engine & Powerplant , 编辑部邮箱 ,2006年03期
- 【分类号】TK464
- 【被引频次】1
- 【下载频次】79