NOx Sensor Diagnostic Algorithms for Diesel Exhaust Systems

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

On-vehicle NOx sensors in diesel engine exhaust streams often fail to respond accurately or quickly to changes in NOx concentrations, leading to incorrect urea dosage and excessive emissions or ammonia slip, necessitating a reliable diagnostic method for prompt fault detection.

Innovation Solution

A computer-managed diagnostic system using algorithms to analyze NOx sensor output, determining offset conditions and response times by stopping fuel flow to establish baseline NOx levels and using timers and statistical analysis to identify faulty sensors, alerting operators to potential issues.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If NOx sensors are used to monitor exhaust gas NOx concentrations for controlling urea injection, then exhaust treatment effectiveness is improved, but sensor response accuracy and speed deteriorate over time leading to faulty readings

Engineering Contradiction:

Improveexhaust treatment effectivenessVSAvoidsensor response accuracy

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The system performs preliminary diagnostic tests by stopping fuel flow to create baseline conditions, then deliberately inducing transient NOx concentration changes to assess sensor response characteristics before actual fault occurs. This proactive approach identifies sensor degradation early, allowing preventive maintenance before treatment effectiveness is compromised.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors sensor output and compares it against expected response characteristics derived from baseline measurements and statistical analysis of normal operation. When deviations exceed predetermined thresholds, the system generates diagnostic codes indicating sensor performance degradation, enabling timely intervention to maintain treatment effectiveness.

Inventive Principle:

Principle #23Feedback

2Measurement precision

If fuel flow is stopped to establish baseline NOx levels for diagnostic testing, then sensor offset detection accuracy is improved, but vehicle operation time is reduced

Engineering Contradiction:

Improvesensor offset detection accuracyVSAvoidvehicle operation time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system implements periodic diagnostic testing at predetermined intervals or when trigger conditions are met, rather than continuous testing. This allows baseline measurements to be obtained at optimal times while minimizing disruption to vehicle operation. The diagnostic sequence is executed as a time-limited routine that resumes normal operation afterward.

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The system dynamically adjusts diagnostic testing based on operational conditions, choosing optimal moments to perform baseline measurements when vehicle state allows. The diagnostic routine adapts its timing and duration based on real-time sensor data and vehicle operating parameters, balancing measurement accuracy with operational continuity.

Inventive Principle:

Principle #15Dynamics

3Reliability

If statistical analysis algorithms are applied to sensor output data, then fault detection reliability is improved, but computational complexity increases

Engineering Contradiction:

Improvefault detection reliabilityVSAvoidcomputational complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system transforms complex sensor output data into simplified diagnostic parameters through statistical analysis, converting raw signal variations into meaningful metrics like response time, offset values, and variability indices. This parameter transformation reduces computational complexity by working with derived characteristics rather than raw data, while maintaining fault detection reliability.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system replaces complex real-time sensor analysis with pre-computed statistical thresholds and simplified comparison algorithms. By establishing baseline characteristics and diagnostic criteria in advance through statistical analysis of normal operation, the system substitutes complex adaptive algorithms with simpler threshold-based fault detection, reducing computational burden while maintaining reliability.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

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 diagnoses NOx sensor faults, preventing emissions breakthroughs and ammonia slip by accurately determining sensor offsets and response times, enabling timely corrections and maintaining optimal exhaust treatment.

Implementation Method 1

NOx sensors are often formed as small electrochemical cells that function, for example, by producing voltage or electrical current signals responsive to the amount of nitrogen oxide species flowing in the exhaust and over sensor surfaces

Methodology Applied

Scientific EffectElectrochemical sensing:

Implementation Method 2

Exhaust treatment from lean-burn engines often uses an upstream oxidation catalyst for unburned hydrocarbons and carbon monoxide, and for oxidation of some NO to NO2

Methodology Applied

Scientific EffectCatalysis: Catalysis

Implementation Method 3

The gas is then passed into contact with a catalyst material selected for a reaction between reductant material and nitrogen oxides to form nitrogen and water for release from the exhaust passage

Methodology Applied

Scientific EffectCatalysis: Catalysis