Abstract The present investigation deals with the influence of Calophyllum Inophyllum methyl esters blend on a CI engine to envisage the performance and emission characteristics with the help of a computing model. Analysis of model using the conventional method is a time consuming and complex phenomenon. Conversely, a soft computing technique called Adaptive Neuro-Fuzzy Inference System (ANFIS) has been used in this work for modelling a system and validating the experimental work. The cylinder pressure, crank angle and heat release data at different load percentages, various blend proportions and different injection pressures have been used as input factors, for getting output characteristics that include Brake Specific Fuel Consumption (BSFC), Brake Thermal Efficiency (BTE), hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx) and smoke emissions. Consequently, the selection of blends and their performance of the IC engine was further validated through use of ANFIS, developed by Matlab R2010a version. ANFIS is capable of validating by obtaining the data set from prior experimental work. A consistent closeness of the validated outputs with measured results has been detected and the error was minimized with an accuracy of more than 90% in all the characteristics was noticed using ANFIS.

中文翻译：

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使用软计算技术验证以金缕梅甲酯为燃料的 CI 发动机的性能和排放

摘要 本研究涉及 Calophyllum Inophyllum 甲酯混合物对 CI 发动机的影响，以借助计算模型来设想性能和排放特性。使用传统方法分析模型是一个耗时且复杂的现象。相反，在这项工作中使用了一种称为自适应神经模糊推理系统 (ANFIS) 的软计算技术来对系统进行建模并验证实验工作。不同负载百分比、各种混合比例和不同喷射压力下的气缸压力、曲柄角和放热数据已用作输入因素，以获得包括制动比燃料消耗 (BSFC)、制动热效率 (BTE)、碳氢化合物 (HC)、一氧化碳 (CO)、氮氧化物 (NOx) 和烟雾排放。因此，通过使用由 Matlab R2010a 版本开发的 ANFIS，进一步验证了内燃机的混合物的选择及其性能。ANFIS 能够通过从先前的实验工作中获取数据集来进行验证。已检测到验证输出与测量结果的一致接近度，并且使用 ANFIS 注意到所有特征的准确度超过 90% 的误差最小化。