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This study introduces a new method to diagnose internal combustion engine issues using the fuel injection system as a sensor. It accurately detects faults like connector degradation and needle movement, improving engine diagnostics.

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Area of Science:

  • Automotive Engineering
  • Mechanical Engineering
  • Sensor Technology

Background:

  • Internal combustion engines require precise fuel injection for optimal performance.
  • Traditional diagnostic methods for fuel injectors can be complex and invasive.
  • Monitoring injector performance is crucial for engine efficiency and emissions control.

Purpose of the Study:

  • To develop a novel, non-invasive diagnostic method for internal combustion engines.
  • To utilize the fuel injection system as an integrated sensor for real-time monitoring.
  • To accurately detect and diagnose common injector faults.

Main Methods:

  • Analyzing electrical parameters (current amplitude, coil charging time) of the fuel injector.
  • Correlating electrical variations with injector needle displacement, fuel pressure, and series resistance.
  • Simulating faults such as connector degradation (oxidation/wear) by altering series resistance.
  • Developing an automated diagnostic system based on current waveform analysis.

Main Results:

  • Reduced injector needle opening (100% to 20%) led to a 35% peak current reduction and 0.2 ms delay.
  • Increased fuel pressure (0.3 to 2.5 bar) caused a 35% peak current rise and 0.4 ms delay.
  • Increased series resistance (0.2 Ω to 2.0 Ω) reduced current amplitude by ~50% and distorted waveforms.
  • The automated system achieved over 90% accuracy in fault detection.

Conclusions:

  • Electrical characteristics of fuel injectors are reliable indicators of internal engine conditions.
  • The proposed method effectively diagnoses injector needle movement, fuel pressure variations, and connector degradation.
  • An automated diagnostic system using this method offers a highly accurate and efficient solution for engine fault detection.