Online Big-Data Monitoring and Assessment Framework for Internal Combustion Engine with Various Biofuels

Abstract

Article Online Big-Data Monitoring and Assessment Framework for Internal Combustion Engine with Various Biofuels Ming Zhang 1,*, Vikas Sharma 2, Zezhong Wang 1, Yu Jia 1, Abul Kalam Hossain 1, and Yuchun Xu 1 1 College of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK 2 School of Architecture, Technology and Engineering, University of Brighton, Brighton BN2 4GJ, UK * Correspondence: m.zhang21@aston.ac.uk     Received: 14 December 2022 Accepted: 26 April 2023 Published: 30 May 2023   Abstract: As the primary power source for automobiles, the internal combustion (IC) engines have been widely used and served millions of people worldwide. With increasingly stringent environmental regulations, biofuels have been obtained more attentions and are being used as alternative fuel to power IC engines. However, there are currently no standard solutions or well-established monitoring and assessment methods that can effectively evaluate the IC engine’s performance with biofuels. The expectation for biofuels is to keep the engine’s lifetime as long as the conventional fuels, or even longer. Otherwise, their usage would be unnecessary because they would reduce the lifecycle of the engine and also cause more waste and pollution. To address this challenge, we initially designed two biofuels: waste cooking oil biofuel (WCOB) and lamb fat biofuel (LFB). Then we proposed an online big-data monitoring and assessment framework for IC engines operating with various types of fuel. We conducted comprehensive experiments and comparisons based on the proposed framework. The results indicate that LFB performs best under all the performance indicators.