Sensor Signal Processing Device for Pre-ignition Detection
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Solution Overview
Problem
Existing sensor signal processing devices struggle to accurately detect pre-ignition in engine combustion, especially when it occurs near knock generation timing, due to high processing load and inability to differentiate between pre-ignition and knock detection intervals.
Innovation Solution
A sensor signal processing device with an AD conversion part, pre-ignition check interval setting, crank angular interval setting, time measuring, peak value detection, and crank angle calculation parts, which converts analog signals into digital, sets specific check intervals, measures time, detects peak values, and calculates crank angles for accurate pre-ignition detection within reduced processing load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sampling frequency of about 100 kHz is used to accurately detect pre-ignition vibration frequency in the range of 5 kHz to 25 kHz, then measurement precision is improved, but processing load increases and processing time must be completed within 10 microseconds
Solution Approach 1:
The pre-ignition check interval is divided into multiple crank angular intervals (e.g., four intervals of 10 degrees each). The peak value detection part detects peak values in each subdivided interval separately, allowing the system to process data in manageable segments rather than overwhelming the processor with all data at once, thus reducing the processing load while maintaining detection accuracy.
Solution Approach 2:
The system performs preliminary peak value detection in each crank angular interval before final pre-ignition determination. By identifying and storing peak values in advance within each subdivided interval, the system prepares data for subsequent analysis, reducing the real-time processing burden during critical detection phases.
2Productivity
If pre-ignition check interval and knock detection interval are differentiated to reduce processing load, then productivity is improved, but pre-ignition detection reliability deteriorates when pre-ignition occurs near knock generation timing
Solution Approach 1:
Different threshold values are applied to different crank angular intervals. The threshold for pre-ignition detection is set differently for each subdivided interval within the pre-ignition check interval. This allows the system to maintain high detection reliability in regions where pre-ignition is more likely to occur while still achieving reduced processing load through interval differentiation.
Solution Approach 2:
The system dynamically adjusts detection parameters based on the specific crank angular interval being analyzed. By making the detection process adaptive to the local characteristics of each interval rather than using a single static threshold for the entire interval, the system maintains reliability across varying combustion conditions while improving overall processing efficiency.
3Measurement precision
If the microcomputer checks whether AD-converted sensor value exceeds threshold value to detect abnormal vibration, then measurement precision is improved, but processing time increases due to continuous monitoring requirements
Solution Approach 1:
The system extracts only the peak values from the AD-converted sensor data in each crank angular interval, rather than continuously analyzing all data points. By focusing computational resources on identifying and evaluating only the peak values (which represent the most significant vibration events), the system maintains detection precision while significantly reducing the time required for processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables reliable detection of pre-ignition even during knock detection intervals by reducing processing load and accurately calculating crank angles at peak value detection, ensuring precise identification of pre-ignition without increasing memory capacity or complicating signal processing.
Implementation Method 1
an AD conversion part for converting an analog sensor signal outputted from a sensor into a digital signal
Data Source
AI summary
A microcomputer is formed of a CPU and a detection circuit and inputs sensor signals of a vibration sensor and a rotation sensor. The detection circuit includes an AD converter circuit for AD conversion of the sensor signal of the vibration sensor at a predetermined sampling interval, a peak hold circuit for detecting a peak value of the sensor signal, a RAM for storing the peak value, a counter for detecting a crank angle at a peak value detection time, and an angle calculation part. The microcomputer divides a pre-ignition check interval into plural interval units and checks the pre-ignition based on the peak value detected in each unit interval. The pre-ignition and the knock are checked by using different threshold values in an interval, in which the pre-ignition check interval overlaps a knock check interval.