Exhaust Gas Temperature Sensor Abnormality Detection
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Solution Overview
Problem
Conventional methods for detecting abnormalities in exhaust gas temperature sensors fail to identify issues within the normal operating range, as they rely on threshold-based detection, which can miss abnormalities where the sensor output remains constant despite temperature changes.
Innovation Solution
A control unit estimates exhaust gas temperature based on engine operating conditions and compares the change characteristics of the estimated temperature with the detected temperature to determine sensor abnormalities, enabling detection across the entire temperature range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If threshold-based detection is used to identify sensor abnormalities, then detection simplicity is improved, but detection precision deteriorates because abnormalities within the normal range cannot be detected
Solution Approach 1:
The patent transitions from static threshold-based detection to dynamic correlation-based detection. Instead of comparing sensor output against fixed thresholds, the system continuously monitors the correlation between estimated temperature (from engine operating conditions) and detected temperature. When the correlation deviates from expected patterns, abnormality is detected. This dynamic approach enables detection of abnormalities throughout the entire temperature range while maintaining operational simplicity through automated correlation analysis.
2Device complexity
If threshold-based abnormality detection is employed, then device complexity is reduced, but reliability deteriorates as abnormalities in the normal range are missed
Solution Approach 1:
The patent implements a feedback mechanism where the control unit continuously compares the detected temperature from the sensor with the estimated temperature derived from engine operating conditions (load, speed, intake air amount). This feedback loop calculates correlation between the two temperature values and detects abnormalities when correlation deviates from normal patterns. This feedback-based approach enhances reliability by detecting abnormalities throughout the entire temperature range while keeping the detection system relatively simple through automated correlation calculation.
3Ease of manufacture
If conventional threshold detection methods are used, then detection cost is minimized, but measurement precision deteriorates because abnormalities within normal range cannot be identified
Solution Approach 1:
The patent employs a self-service approach where the control unit utilizes existing engine operating condition data (load, speed, intake air amount) to estimate exhaust gas temperature and compare it with sensor readings. No additional hardware or complex detection systems are required - the system uses readily available information to perform correlation analysis and detect abnormalities. This self-service method maintains low detection cost while significantly improving measurement precision by identifying abnormalities throughout the entire temperature range.
Data Source
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AI summary
On the basis of a correlation between exhaust gas temperature detected by an exhaust gas temperature sensor and exhaust gas temperature estimated according to an engine operating condition, it is detected whether or not abnormality occurs in the exhaust gas temperature sensor. Namely, when a change characteristic of the detected exhaust gas temperature follows a change characteristic of the estimated exhaust gas temperature, it is determined that the exhaust gas temperature sensor is normal. On the other hand, when the change characteristic of the detected exhaust gas temperature does not follow that of the estimated exhaust gas temperature, it is determined that the exhaust gas temperature sensor is abnormal.