Soot Load Estimation Using Delta P and Model Fusion
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Solution Overview
Problem
Current methods for determining soot load in particulate filters are inaccurate and inefficient, leading to excessive fuel consumption and reduced lifespan of after-treatment systems due to improper regeneration timing.
Innovation Solution
A system that estimates soot load using a delta P soot load estimate generator and a modeled engine performance estimator, with a trust factor generator to determine which estimate to use based on engine operating characteristics, allowing for precise and efficient regeneration timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If active regeneration is performed frequently to remove soot, then soot buildup is reduced, but fuel consumption increases
Solution Approach 1:
The system changes the parameter of regeneration timing by using a trust factor signal that varies based on engine operating conditions. Instead of fixed or overly frequent regeneration, the system adapts regeneration timing parameters dynamically, performing regeneration only when the trust factor indicates high confidence in soot load estimates, thereby reducing unnecessary fuel consumption while maintaining filter performance.
2Use of energy by moving object
If active regeneration is delayed to save fuel, then fuel efficiency improves, but excessive soot builds up causing higher temperatures and reduced system life
Solution Approach 1:
The system implements feedback through the trust factor generator that continuously monitors engine operating characteristics and adjusts regeneration timing accordingly. When the trust factor is high (indicating reliable soot load estimates), the system performs regeneration at optimal times. This feedback mechanism prevents both premature regeneration (wasting fuel) and delayed regeneration (excessive soot buildup), thereby extending system life while maintaining fuel efficiency.
3Device complexity
If a single soot load estimation method is used, then the system is simple, but accuracy is insufficient leading to improper regeneration timing
Solution Approach 1:
The system merges multiple soot load estimation methods (delta P-based estimation and model-based estimation) into a unified system. The trust factor generator combines information from different sources to produce a composite trust factor signal that determines which estimation method to use. This merging approach maintains reasonable system complexity while significantly improving soot load estimation accuracy, enabling proper regeneration timing.
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
The system provides accurate soot load estimation, reducing fuel consumption and extending the life of after-treatment systems by optimizing regeneration timing and minimizing unnecessary regenerations.
Implementation Method 1
a delta P soot load estimate generator that generates a first soot load estimate as a function of a pressure drop
Implementation Method 2
the burning of the soot is exothermic, a regeneration of a particulate filter with excessive soot results in even higher temperatures
Implementation Method 3
Because the burning of the soot is exothermic
Data Source
AI summary
A system for estimating an amount of soot in an exhaust particulate filter includes a delta P soot load estimate generator configured to generate a first soot load estimate as a function of a pressure drop and a mass flow of exhaust. The system further includes a model estimate generator configured to generate a second soot load estimate as a function of a modeled engine performance. A trust factor generator is configured to determine a trust factor signal as a function of at least one engine operating characteristic, and a decision generator is configured to determine whether to use the first soot load estimate or the second soot load estimate as a function of the trust factor signal.