Fuzzy logic model for prediction of cold filter plugging point of biodiesel from various feedstock

The present study investigates the potential of Fuzzy Logic model to predict the cold filter plugging point (CFPP) of biodiesel fuel from its fatty acid (FA) composition. CFPP defines the operability for diesel fuel which is strongly influenced by the FA of feedstock. Prediction of CFPP based on the FA of feedstock can reduce the experimental effort to produce a biodiesel suitable for a regional climate. To generate fuzzy prediction model, data sets containing FA composition and CFPP temperatures of 60 biodiesel samples traced from literature. To check the accuracy of the model developed, waste/refined frying oil (WFO/RFO) and waste/refined canola oil (RCO/WCO) were converted to biodiesel fuel by transesterification then, their CFPP temperatures were determined following the EN and ASTM standards. The CFPP temperatures estimated by the multi input single output (MISO) fuzzy model were in close agreement with the experimental values. The validation results confirm the applicability of the fuzzy model developed here with its high degree of accuracy and minimum time demand can be rapid alternative to the costly and time consuming actual experiments and trails.