NOx Sensor Signal Separation for Urea Dosage Control
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Solution Overview
Problem
Existing systems face challenges in accurately estimating concentrations of nitrogen oxides NOX and ammonia NH3 in exhaust gases downstream from a catalyst, due to cross-sensitivity of NOX sensors, which complicates urea dosage regulation and diagnostic processes.
Innovation Solution
A method and system that utilize a catalyst model and estimation functions to separate the sensor signal into respective concentrations of NOX and NH3 by defining deviation parameters, allowing for continuous estimation and robust urea dosage regulation, even in systems without a catalyst model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a NOX sensor is used to monitor exhaust gases downstream from the catalyst, then the sensor provides information about nitrogen oxide concentrations, but the sensor signal becomes cross-sensitive to ammonia concentrations making accurate measurement difficult
Solution Approach 1:
The patent segments the combined sensor signal into separate contributions from nitrogen oxides and ammonia by using a catalyst model that describes their respective behaviors. The sensor signal is mathematically divided into y_NOx (nitrogen oxide component) and y_NH3 (ammonia component), allowing precise measurement of nitrogen oxides despite cross-sensitivity.
Solution Approach 2:
The catalyst model acts as an intermediary that translates the cross-sensitive sensor signal into separate concentration estimates. By introducing deviation parameters that capture differences between model predictions and actual sensor readings, the system mediates between the ambiguous sensor output and the desired precise concentration measurements.
2Reliability
If urea dosage is increased to ensure complete nitrogen oxide reduction, then emission requirements are met, but urea consumption increases
Solution Approach 1:
The patent implements feedback control by continuously monitoring the separated nitrogen oxide concentration signal and using it to adjust urea dosage. The estimated y_NOx signal provides real-time information about actual nitrogen oxide levels downstream, enabling the control system to optimize urea injection to maintain complete reduction while minimizing excess urea consumption.
Solution Approach 2:
The system dynamically changes the urea dosage parameter based on actual operating conditions and nitrogen oxide concentrations. By adjusting the urea injection rate according to the separated sensor signal and catalyst model, the system adapts to varying load conditions, ensuring reliable nitrogen oxide reduction while optimizing urea consumption across different operating points.
3Reliability
If a larger catalyst is used to ensure complete nitrogen oxide conversion under all conditions, then emission requirements are met, but the catalyst system size and cost increase
Solution Approach 1:
The patent replaces the need for a larger physical catalyst system with a computational approach using a catalyst model and signal separation algorithm. Instead of increasing catalyst volume to handle all possible operating conditions, the system uses mathematical modeling and feedback control to achieve complete nitrogen oxide conversion with a compact catalyst, substituting computational complexity for mechanical size.
4Measurement precision
If the catalyst model is made more complex to accurately represent real catalyst behavior, then estimation accuracy improves, but system complexity and computational requirements increase
Solution Approach 1:
The patent manages model complexity by using a manageable number of deviation parameters (typically 1-3 parameters) that capture the essential differences between the catalyst model and real behavior. This parameter-based approach allows the model to remain computationally efficient while still achieving accurate concentration estimates, balancing model fidelity with system complexity.
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
This approach enables precise monitoring and regulation of urea dosage, reduces urea consumption, meets emission requirements with a smaller catalyst, and improves diagnostic capabilities for the catalyst system.
Implementation Method 1
a sensor signal ysensor provided by an NOX sensor 131 which is situated downstream of the catalyst 110 and is cross-sensitive for ammonia NH3
Implementation Method 2
The catalyst system 100, which comprises an SCR (selective catalytic reduction) catalyst 110
Implementation Method 3
The urea is usually in the form of an aqueous solution which is vaporised and decomposes to form ammonia
Implementation Method 4
The ammonia then constitutes the active reducing agent in the catalyst 110 and reacts with nitrogen oxides NOX in the exhaust gases to form nitrogen gas and water
Data Source
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AI summary
The present invention relates to a method and a system for estimation of respective concentrations of nitrogen oxides NO x and concentrations of ammonia NH 3 in exhaust gases downstream from a catalyst (110), said estimation being based on a catalyst model and on a measured sensor signal ? sensor from a nitrogen oxide sensor which is so situated that it is placed in contact with said exhaust gases. According to the present invention, the measured sensor signal ? sensor is compared with an estimated signal which depends on at least two estimation functions and represents the catalyst model's match with said measured sensor signal ? sensor . This comparison is then used in determination of at least one deviation parameter for the respective said at least two estimation functions, where each said at least one deviation parameter describes a systematic deviation from reality for at least one input signal, one variable or one condition for said catalyst model. According to the invention an estimation is also made of the respective concentrations of nitrogen oxides NO x and ammonia NH 3 on the basis of the respective at least estimation functions and of said at least one deviation parameter.