Sensor Controller for Particulate Matter Detection Error Correction
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Solution Overview
Problem
Particulate matter detection sensors often experience errors due to foreign matter attachment, leakage currents, and circuit variations, leading to inaccurate PM detection.
Innovation Solution
A sensor controller with a heater to burn and remove particulate matter, learning means to calculate and store standard values, and correcting means to accurately adjust sensor detection values, reducing detection errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a PM sensor uses a pair of opposed electrodes on an insulating substrate to detect PM amount by measuring resistance, then the sensor structure is simple and easy to manufacture, but detection errors occur due to foreign matter attachment, leakage currents, and circuit variations
Solution Approach 1:
The patent applies preliminary action by performing a learning process to store standard values (first learning value and second learning value) that represent the sensor's characteristics when no PM is attached and when PM is fully burned. These pre-stored standard values are then used to correct detection signals, compensating for errors caused by foreign matter attachment and circuit variations before they affect measurement accuracy.
Solution Approach 2:
The patent utilizes parameter changes by measuring the sensor output at two different temperature states: a first standard value when the sensor is at a lower temperature (no PM attachment) and a second standard value when the sensor is at a higher temperature (PM burned). These parameter changes with temperature allow the system to establish baseline characteristics for error correction.
2Reliability
If foreign matter such as metal pieces is attached to the insulating substrate or leakage current flows through impurities, then the sensor may produce false outputs or outputs larger than expected, but adding complex correction mechanisms increases device complexity
Solution Approach 1:
The patent implements feedback by using the stored first learning value and second learning value to correct the detection signal. The correction amount is calculated based on the difference between the actual detection signal and the expected standard values, and this correction is applied to compensate for errors caused by foreign matter attachment and leakage currents, thereby improving reliability without requiring complex additional hardware.
Solution Approach 2:
The sensor system performs self-diagnosis and self-correction by using its own detection capabilities to identify errors caused by foreign matter or leakage currents. The learning values stored during calibration periods enable the sensor to automatically compensate for its own defects, eliminating the need for external correction mechanisms.
3Productivity
If the sensor detection value is used directly without correction, then the calculation process is simple and fast, but the PM amount detection is inaccurate due to sensor errors
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing the first learning value and second learning value during calibration periods. These pre-stored values are then used to quickly correct detection signals during normal operation, maintaining fast calculation speed while improving measurement accuracy through error compensation.
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
Effectively reduces detection errors in particulate matter sensors by correcting sensor outputs based on learned standard values, ensuring accurate PM detection.
Implementation Method 1
a heater configured to heat the attachment portion so as to burn and remove the particulate matter attached to the attachment portion
Implementation Method 2
burn and remove the particulate matter
Data Source
AI summary
A sensor controller for a particulate matter detection sensor includes a heater configured to heat an attachment portion so as to burn and remove particulate matter attached to the attachment portion, a learning portion for obtaining a sensor detection value immediately after burning and removing the particulate matter due to heating of the heater. The leaning portion calculates a sensor standard value based on the obtained sensor detection value in a state where the particulate matter is removed, and stores the sensor standard value as a learning value. Furthermore, a correcting portion corrects the sensor detection value based on the sensor standard value stored by the learning portion.