A Comprehensive Analysis on Biodiesel Blend Model
This article addresses the issue regarding the exploitation of conventional fuel diesel. To overcome this issue, the Tamanu oil-diesel oil blend is introduced, where a new neural model is proposed, which is trained by renowned firefly algorithm, termed as FF-NM. In addition, different compression ratios such as 15, 16, 17, 17.5 and blend ratios like 5:95, 6:94, 7:93, 8:92, and 9:91and 10:90 is exploited. The emission analysis and the combustion characteristics of the TO-diesel oil blend are evaluated as well as the MSE analysis is carried out for the proposed FF-NM method. For all the predicted parameters, the MSE of the proposed method is low for varying blend as well as the compression ratios. Moreover, the emission characteristics of the HC, CO2, NOx, CO, as well as O2 at different CR concerning the actual, and FF-NM is computed with the chosen blend ratios. From analysis, it is recognized that the estimation errors are less for the FF-NM approach. Hence, the simulation outcomes demonstrate the better performance of the proposed FF-NM approach under various compression ratios of 15, 16, 17 and 17.5, respectively.