Engine Exhaust NOx Estimation via Empirical Database
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Solution Overview
Problem
Existing SCR systems for reducing nitrogen oxides in exhaust streams rely on NOx sensors, which may not function accurately or reach operating temperature promptly, leading to inefficiencies and diagnostic challenges.
Innovation Solution
A controller-based system that estimates NOx levels using a database of empirically-derived data correlated with engine speed and equivalence ratio, allowing for accurate reductant dosing and diagnostic checks even when NOx sensors are not ready or functioning correctly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a NOx sensor is used to measure NOx levels in the exhaust stream, then the SCR system can regulate reductant injection, but the sensor may not function accurately or reach operating temperature promptly
Solution Approach 1:
The patent introduces an intermediary computational model that uses readily available sensor data (engine speed, equivalence ratio, operating conditions) to estimate NOx levels. This intermediary system bridges the gap when direct NOx measurement is unavailable or unreliable, allowing the SCR control system to function without depending solely on the NOx sensor's readiness.
Solution Approach 2:
The patent creates a computational copy or model of NOx behavior based on empirical data and engine operating parameters. Instead of relying on the physical NOx sensor, the system uses a virtual model that replicates NOx generation characteristics under various engine conditions, providing estimated NOx levels for control purposes.
2Measurement precision
If the control system waits for the NOx sensor to be ready, then accurate measurement may be achieved, but system efficiency and responsiveness are reduced
Solution Approach 1:
The patent performs preliminary calculations using the computational model to estimate NOx levels immediately, without waiting for sensor readiness. This preliminary action allows the SCR system to begin regulating reductant injection based on model estimates while the sensor warms up, maintaining system productivity and responsiveness throughout the sensor's warm-up period.
Solution Approach 2:
The system uses its own existing operational data (engine speed, equivalence ratio, operating conditions) to self-determine NOx levels through the computational model, rather than passively waiting for external sensor input. This self-service capability allows continuous operation without interruption for sensor readiness.
3Reliability
If a computational model is used to estimate NOx levels, then reductant dosing can proceed without sensor readiness, but the system complexity increases
Solution Approach 1:
The patent transforms the control approach by changing from direct physical measurement to computational estimation using existing parameters. The computational model processes standard engine operating parameters (speed, equivalence ratio, conditions) through empirical relationships to generate NOx estimates, adding computational logic but not requiring additional physical sensors or complex hardware modifications.
Data Source
AI summary
An engine assembly includes a controller and at least one data storage medium storing a database. The database includes empirically-derived NOx values based on engine equivalence ratio and engine speed at predetermined reference conditions. The controller is configured to retrieve a NOx value from the database that corresponds to a measured value of the equivalence ratio and a measured value of the engine speed, and to modify the NOx value to compensate for differences between the reference conditions and the actual operating conditions of the engine assembly.