NOx Sensor Monitoring Using Phase-Based Reference Profiles
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Solution Overview
Problem
Existing methods struggle to accurately detect malfunctions in vehicle sensors, particularly NOx sensors, which are critical for aftertreatment systems, due to issues like drifting and deteriorated step responses, leading to inaccurate emission monitoring and potential environmental damage.
Innovation Solution
A method involving data storage, normalization, and comparison of sensor representations with reference representations using discrete intervals and classification schemes to identify normal or abnormal sensor operation, allowing for robust classification and prediction of sensor malfunctions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensor monitoring methods are used, then the system complexity remains low, but the measurement precision and reliability of sensor malfunction detection deteriorate due to drifting and deteriorated step responses
Solution Approach 1:
The patent segments the sensor monitoring process into distinct operational phases (cold start, hot soot, hot NOx) and creates separate reference representations for each phase. This segmentation allows for more precise malfunction detection in each specific operational context without requiring a single complex universal monitoring system.
Solution Approach 2:
The patent performs preliminary actions by storing multiple reference sensor representations under different operating conditions before actual monitoring begins. These pre-stored references are then compared against actual sensor readings during operation, enabling accurate malfunction detection without requiring complex real-time analysis algorithms.
2Reliability
If a single reference value is used for sensor monitoring, then the ease of operation is maintained, but the reliability of malfunction detection worsens due to varying operating conditions
Solution Approach 1:
The patent applies local quality by creating specific reference representations tailored to different local operating conditions (cold start, hot soot, hot NOx phases). Each reference representation is optimized for its specific operational context, improving detection reliability without requiring a single complex universal reference that would compromise ease of operation.
Solution Approach 2:
The patent changes the parameter of reference data by storing multiple reference representations with different characteristics corresponding to different operating phases. The system selectively applies the appropriate reference representation based on current operating conditions, thereby maintaining reliability across varying conditions while keeping the monitoring method relatively simple through automated phase-based selection.
3Measurement precision
If sensor data is collected continuously without phase differentiation, then the productivity of monitoring is high, but the measurement precision deteriorates due to mixing different operational states
Solution Approach 1:
The patent segments continuous sensor data collection into distinct operational phases (cold start, hot soot, hot NOx). By separating data from different operational states, the system achieves higher measurement precision for each phase-specific analysis without the negative effects of mixing disparate operational conditions, while maintaining productivity through efficient phase-based processing.
Data Source
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AI summary
A method for monitoring the operation of a sensor is provided. The method comprises the step of representing the operation of the sensor by: i) storing a plurality of data values, each data value corresponding to the sensor output signal, wherein said step is performed during a time period such that said data values are distributed over a range of possible data values, ii) defining a plurality of discrete intervals within said range of possible data values; and iii) calculating the frequency of the data values within each interval thus forming a sensor representation. The method further comprises the steps of receiving at least one reference sensor representation; and comparing said sensor representation with said at least one reference sensor representation.