Acoustic Engine Misfire Detection via Cycle Length Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Internal combustion engines face inefficiencies due to misfires, which are difficult to detect and can lead to lower fuel efficiency and wear on catalytic converters, especially in vehicles outside the scope of on-board diagnostics (OBD) II regulations.
Innovation Solution
Methods and systems for analyzing cyclo-mechanical engines involve detecting engine signals, comparing cycle lengths, and analyzing frequency spectra to identify variations and misfires by correlating signal samples, using sensors and processors to determine cycle length and engine speed variations, and refining estimates to pinpoint misfiring cylinders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional OBD II diagnostic methods are used, then misfires can be detected in regulated vehicles, but vehicles outside OBD II regulations cannot be diagnosed
Solution Approach 1:
The patent replaces traditional electronic/OBD II diagnostic systems with an acoustic-based detection system. A microphone or acoustic sensor captures engine sounds, and signal processing algorithms analyze these acoustic signals to detect misfires. This substitution of acoustic measurement for electronic diagnostic protocols enables universal vehicle compatibility while maintaining reliable misfire detection capability.
2Adaptability or versatility
If acoustic signal processing is used to detect misfires, then universal vehicle compatibility is achieved, but detection precision for partial combustion misfires remains challenging
Solution Approach 1:
The patent introduces multiple intermediary processing steps between the raw acoustic signal and misfire detection. These include bandpass filtering to isolate engine frequency ranges, Fast Fourier Transform (FFT) to convert time-domain signals to frequency-domain analysis, and correlation techniques to compare expected versus actual combustion patterns. These intermediaries enhance the precision of detecting partial combustion misfires while maintaining universal vehicle compatibility.
3Measurement precision
If detailed signal analysis is performed to improve misfire detection, then detection accuracy improves, but computational complexity and analysis time increase
Solution Approach 1:
The patent segments the complex signal processing task into distinct modular stages: (1) acoustic signal acquisition and pre-filtering, (2) FFT frequency domain transformation, (3) correlation analysis with reference patterns, (4) misfire classification based on correlation coefficients. This segmentation reduces computational complexity by processing signals in manageable stages rather than attempting comprehensive analysis simultaneously, while maintaining high detection accuracy through systematic progression through each analytical layer.
Data Source
AI summary
Methods of analyzing a cyclo-mechanical engine include detecting an engine signal associated with a plurality of cycles of the cyclo-mechanical engine, comparing a first sample of the engine signal with a second sample of the engine signal to determine a cycle length of the cyclo-mechanical engine, and analyzing the engine signal to detect a variation in the cycle length of the cyclo-mechanical engine over time based on the determined cycle length. Related systems and computer program products are also disclosed.