Exhaust Gas Regeneration Timing via Statistical Probability
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Solution Overview
Problem
Current methods for timing the regeneration of exhaust gas systems in vehicle engines are inefficient, leading to increased thermal wear and fuel consumption due to frequent interruptions and reliance on unpredictable triggers like vehicle speed and temperature, which are not effective when routes or driving cycles are uncertain.
Innovation Solution
A method that collects data on exhaust gas regeneration capability over time to establish a statistical probability function, identifying suitable and unsuitable time periods for regeneration, allowing for improved timing to increase the success rate of regeneration processes and reduce interruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If regeneration is timed based on traditional triggers (minimum vehicle speed and/or minimum temperature), then the regeneration process can be initiated, but the success rate is low and interruptions occur frequently
Solution Approach 1:
The system performs preliminary data collection and statistical analysis to identify optimal regeneration time periods before the actual regeneration process. By analyzing historical data on exhaust gas temperature, mass flow, engine power, and engine load over time, the system pre-determines when regeneration is most likely to succeed, allowing proactive scheduling rather than reactive triggering.
Solution Approach 2:
The system continuously monitors exhaust gas parameters (temperature, mass flow) and engine operating conditions, comparing real-time data against the statistically derived probability function. This feedback mechanism allows the control system to adjust regeneration timing based on actual operating patterns, improving success rates by scheduling regenerations during periods when conditions statistically favor completion.
2Reliability
If regeneration is performed frequently to maintain system performance, then exhaust gas after-treatment units remain functional, but thermal wear increases and fuel consumption rises
Solution Approach 1:
The system pre-identifies optimal regeneration time windows based on statistical analysis of operating patterns, allowing the control system to schedule regenerations only when conditions are favorable. This prevents unnecessary regenerations during unsuitable periods (such as during driver breaks or low-load conditions), reducing fuel consumption while maintaining system reliability.
Solution Approach 2:
The system changes the timing parameter of regeneration based on statistically derived probability functions that consider multiple parameters simultaneously (exhaust gas temperature, mass flow, engine power, engine load, time of day). By optimizing the timing parameter rather than increasing regeneration frequency, the system maintains exhaust gas system performance while reducing fuel consumption associated with frequent regenerations.
3Reliability
If regeneration is scheduled during high-load engine periods to maintain temperature, then regeneration success improves, but driver comfort and operational flexibility are reduced
Solution Approach 1:
The system performs preliminary statistical analysis to identify time periods that are statistically suitable for regeneration, considering both exhaust gas conditions and operational patterns. By pre-determining optimal timing windows, the system can schedule regenerations during high-load periods when temperature conditions are favorable without forcing disruptions to driver comfort or operational flexibility.
Solution Approach 2:
The system dynamically adjusts regeneration scheduling based on real-time and historical operating data, creating a flexible approach that adapts to actual driving patterns. Rather than using fixed triggers, the system learns from operational history to identify optimal timing windows that balance regeneration success with driver comfort and operational requirements.
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 enhances the success rate of regeneration by avoiding unsuitable times for regeneration, reducing thermal wear and fuel consumption, and allowing for more efficient scheduling of regeneration processes, especially for downstream units like SCR systems.
Implementation Method 1
regeneration is typically performed, by increasing the temperature of the exhaust gas. This way, combustible accumulated substances in a DPF can be burned off
Implementation Method 2
combustible accumulated substances in a DPF can be burned off
Data Source
AI summary
A method for timing of a regeneration process of an exhaust gas system of a vehicle engine includes collecting, during operation of the vehicle, data on an exhaust gas regeneration capability as a function of time, establishing, from the collected data, a statistical probability function for the exhaust gas regeneration capability as a function of time, and identifying, from the probability function, one or several time periods that statistically are suitable and/or unsuitable for carrying out a regeneration process. A method for regeneration of an exhaust gas system of a vehicle engine is also provided.