DeNOx Catalyst Regeneration Prediction via Mass Flow Analysis
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Solution Overview
Problem
Conventional methods for predicting the regeneration of DeNOx catalysts, such as lean NOx traps, face challenges in precisely estimating the NOx and NO2 amounts remaining after regeneration, which affects the timing and amount of reducing agent injection, leading to inefficiencies in NOx purification and potential overdesign of catalysts.
Innovation Solution
A method that calculates the total mass flow of reducing agents used in nitrate, NO2, and simple oxidation reactions, along with the mass flow of NO2 released and slipped from the DeNOx catalyst, considering the utilization efficiency, aging, and temperature of the catalyst, to accurately predict the NOx and NO2 masses remaining after regeneration, thereby optimizing regeneration timing and reducing agent injection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to predict NOx amount stored in LNT catalyst, then regeneration timing can be controlled, but prediction precision is insufficient leading to inefficient NOx purification
Solution Approach 1:
The patent segments the NOx purification process into distinct phases: absorption phase (lean atmosphere) and release phase (rich atmosphere). By separating these phases and modeling them independently with different kinetic parameters, the prediction precision of NOx amount is improved while maintaining purification efficiency.
Solution Approach 2:
The patent introduces temperature as a dynamic parameter that changes the kinetic constants of NOx absorption and release reactions. By modeling temperature-dependent rate constants and using real-time temperature measurements, the system achieves precise prediction of NOx storage and release, resolving the contradiction between prediction accuracy and purification efficiency.
2Reliability
If reducing agent injection is increased to ensure NOx purification, then purification reliability improves, but fuel economy deteriorates
Solution Approach 1:
The patent implements a feedback control system that uses real-time measurements of exhaust gas temperature, lambda (air-fuel ratio), and calculated NOx storage amount to dynamically adjust reducing agent injection timing and amount. This feedback mechanism ensures reliable NOx purification by injecting reducing agent only when and where needed, preventing both over-injection (wasting fuel) and under-injection (poor purification).
Solution Approach 2:
The patent performs preliminary calculation of NOx storage amount and predicts optimal regeneration timing before actual regeneration occurs. By anticipating when regeneration will be needed and preparing the appropriate reducing agent injection strategy in advance, the system ensures reliable purification while minimizing unnecessary fuel consumption.
3Productivity
If DeNOx catalyst is overdesigned with excessive noble metals, then purification performance improves, but manufacturing cost increases
Solution Approach 1:
The patent transitions from static catalyst design to dynamic control, where the catalyst's effective capacity is optimized through real-time adjustment of operating conditions (temperature, lambda, reducing agent injection). This dynamic approach allows smaller catalysts with less noble metal to achieve the same purification performance as larger, overdesigned catalysts, reducing material quantity while maintaining performance.
Solution Approach 2:
The patent uses parameter changes (temperature, air-fuel ratio, reducing agent amount) to optimize catalyst utilization. By dynamically adjusting these parameters, the system maximizes the effectiveness of the noble metal catalyst material, allowing reduced material quantity while maintaining high purification performance through optimized reaction conditions.
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 allows for precise prediction of NOx and NO2 amounts, enhancing NOx purification efficiency, improving fuel economy, and reducing the need for excessive noble metal usage in DeNOx catalysts.
Implementation Method 1
the NOx contained in the exhaust gas is reduced in the DeNOx catalyst through oxidation-reduction reaction with the reducing agents
Implementation Method 2
The LNT catalyst absorbs the NOx contained in the exhaust gas when the engine operates in a lean atmosphere
Data Source
AI summary
A method for predicting regeneration may include calculating total mass flow of reducing agent, calculating mass flow of the reducing agent used in nitrate reduction reaction, mass flow of the reducing agent used in NO2 reduction reaction, and mass flow of the reducing agent which is simply oxidized by using the total mass flow of the reducing agent, calculating mass flow of released NO2 and mass flow of reduced NO2 by using the mass flow of the reducing agent used in the nitrate reduction reaction and the mass flow of the reducing agent used in the NO2 reduction reaction, calculating mass flow of NO2 slipped from DeNOx catalyst, and calculating mass of NO2 and mass of NOx remaining at the DeNOx catalyst after regeneration based on the mass flow of the released NO2, the mass flow of the reduced NO2, and the mass flow of the slipped NO2.