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

Ming Zhang, Vikas Sharma, Zezhong Wang , Yu Jia, Abul K Hossain, Yuchun Xu

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Number of pages9
JournalInternational Journal of Automotive Manufacturing and Materials.
Issue number2
Publication statusPublished - 30 May 2023


  • Industry 4.0
  • big-data analysis
  • condition monitoring
  • performance assessment
  • internal combustion (IC) engine
  • biofuels


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