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The main objective of this research is to collect a database on pollutant emissions in internal combustion engines to develop a diagnostic model based on fuzzy logic. Operating parameters of MPFI engines are collected using a gas analyzer, which measures concentrations of CO, HC, CO₂, and O₂. Tests are conducted on vehicles with various ignition point settings, lambda factors, and mileage levels. A fuzzy system is then developed to analyze the collected data and create a diagnostic tool for maintenance and repair. The results show diagnostic errors of 0.46% in Mixture Dosage, 45.1% in Ignition Point, and 27.99% in Mileage. These findings provide a basis for optimizing diagnostics and improving engine performance.

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Development of a Fuzzy System for Emission Diagnosis in MPFI Engine Systems

  • 会议论文

  • 发表日期：

    2025年

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  • Nataly Azucena Ochoa Durazno,
  • Andrea Karina Bermeo Naula,
  • Néstor Diego Rivera-Campoverde

摘要

The main objective of this research is to collect a database on pollutant emissions in internal combustion engines to develop a diagnostic model based on fuzzy logic. Operating parameters of MPFI engines are collected using a gas analyzer, which measures concentrations of CO, HC, CO₂, and O₂. Tests are conducted on vehicles with various ignition point settings, lambda factors, and mileage levels. A fuzzy system is then developed to analyze the collected data and create a diagnostic tool for maintenance and repair. The results show diagnostic errors of 0.46% in Mixture Dosage, 45.1% in Ignition Point, and 27.99% in Mileage. These findings provide a basis for optimizing diagnostics and improving engine performance.