滕勤,杨瑜,左承基,谈建.煤层气发动机混合气充量系数模型的辨识[J].农业机械学报,2007,38(3):47-51.
.[J].Transactions of the Chinese Society for Agricultural Machinery,2007,38(3):47-51.
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煤层气发动机混合气充量系数模型的辨识   [下载全文]
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DOI:10.3969/j.issn.1000-1298.[year].[issue].[sequence]
中文关键词:  煤层气发动机  充量系数  辨识建模  神经网络
基金项目:
滕勤  杨瑜  左承基  谈建
合肥工业大学
中文摘要:将充量系数作为预混合点燃式煤层气发动机转速和进气歧管压力的函数,根据实验数据,应用系统辨识方法,建立了基于多项式、BP神经网络和自适应神经网络模糊推理系统(ANFIS)的混合气充量系数模型,比较了各种模型的建模效果。为了验证模型的有效性,将所建充量系数模型分别嵌入煤层气发动机平均值模型,对平均值模型的估计值和实验数据进行了比较。检验结果表明,充量系数的非参数模型比多项式模型具有更高的预测精度,适合作为系统仿真的子模型。
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Abstract:The volumetric efficiency of gaseous mixture (VEGM) is regarded as a function of speed and intake manifold absolute pressure of a pre-mixed spark ignition coal-bed gas engine. Three models of VEGM were developed based on polynomial, BP neural network and the adaptive neural fuzzy inference system (ANFIS), respectively, by using the system identification method and the experimental data. The modeling efficiencies of various models was compared. In order to validate the models, the volumetric efficiency models were embedded into the mean value model of the coal-bed gas engine respectively. The estimated output of the mean value model was compared with the experiments data. The results show that non-parametric models of the volumetric efficiency are more accurate than the parametric model for prediction and more suitable for system simulation as a sub-model.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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