Dynamic Oil Dilution Filtering for Engine Control
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Solution Overview
Problem
Fuel dilution of engine oil varies significantly due to factors like cold engine operation and driving style, leading to inconsistent oil change intervals, which can result in unnecessary engine controller actions affecting fuel economy and emissions, and delayed notification of oil change needs.
Innovation Solution
A method that filters the estimated oil dilution amount by adjusting the filter time constant based on the dilution level, using a larger time constant for lower dilutions to filter out transient dynamics and a smaller time constant for higher dilutions to increase sensitivity and reduce latency in oil change notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed filter time constant is used for oil dilution monitoring, then the system is simple to implement, but it cannot adapt to varying dilution levels leading to inaccurate oil change interval determination
Solution Approach 1:
The filter time constant is made dynamic rather than fixed. The system automatically adjusts the time constant based on the current oil dilution level: using a first time constant when dilution is below a threshold and a second time constant when dilution exceeds the threshold. This dynamic adaptation improves measurement precision across varying operating conditions without requiring multiple separate systems.
Solution Approach 2:
The system changes the filtering parameter (time constant) based on the measured oil dilution level. By monitoring the dilution amount and switching between different time constant values, the system optimizes the filtering characteristics to match current operating conditions, thereby improving accuracy without adding complex hardware.
2Speed
If a small filter time constant is used, then the system responds quickly to oil dilution changes, but it amplifies transient dynamics and noise leading to false oil change notifications
Solution Approach 1:
The system dynamically selects the time constant based on the current dilution level. When dilution is low, a larger time constant smooths transient fluctuations and noise. When dilution exceeds the threshold, a smaller time constant provides faster response to detect significant degradation. This dynamic adjustment resolves the contradiction between response speed and stability.
Solution Approach 2:
Different filtering characteristics (time constants) are applied to different operating conditions (low dilution vs. high dilution). This local optimization ensures that each filtering parameter is matched to the appropriate operating regime, providing both stability when needed and responsiveness when critical.
3Stability of the object's composition
If a large filter time constant is used, then the filtered output is stable and filters out transient dynamics, but it introduces latency in detecting oil degradation and delaying oil change notifications
Solution Approach 1:
The system switches between two time constant values based on the oil dilution threshold. The larger time constant provides stability during normal operation, while the smaller time constant reduces latency when dilution becomes critical. This dynamic switching eliminates the trade-off by adapting the filtering aggressiveness to the current state.
Solution Approach 2:
The filtering parameter (time constant) is changed based on the measured dilution level. This parameter adaptation allows the system to optimize between stability and response time, using aggressive filtering only when necessary to detect genuine degradation trends while maintaining stability during normal operation.
4Reliability
If engine controller takes actions based on transient oil dilution increases, then oil dilution is mitigated, but fuel economy deteriorates and emissions increase
Solution Approach 1:
The dynamic time constant selection allows the system to distinguish between transient dilution spikes and sustained degradation trends. By using appropriate filtering based on current dilution levels, the system avoids reacting to temporary fluctuations that would trigger unnecessary engine control adjustments, thereby maintaining fuel economy while still protecting against genuine oil degradation.
Solution Approach 2:
The system uses filtered oil dilution measurements as feedback to determine when engine control actions are necessary. The adaptive filtering ensures that feedback signals are based on reliable, sustained trends rather than transient noise, preventing premature or unnecessary engine control interventions that would waste fuel and increase emissions.
5Reliability
If engine temperature is increased to reduce oil dilution, then fuel dilution is mitigated, but fuel economy decreases
Solution Approach 1:
The system uses adaptively filtered oil dilution measurements as feedback to determine when temperature increase actions are necessary. By ensuring the feedback signal reflects genuine, sustained dilution problems rather than transient fluctuations, the system avoids unnecessary temperature increase actions that would consume additional fuel, while still responding appropriately to real oil degradation issues.
6Reliability
If early fuel injection timing is used to reduce oil dilution, then fuel dilution is mitigated, but particulate emissions increase
Solution Approach 1:
The system uses reliably filtered oil dilution measurements as feedback to trigger fuel injection timing adjustments. By ensuring that the feedback signal is based on sustained degradation trends rather than transient noise, the system avoids premature timing adjustments that would increase emissions, while still responding appropriately to genuine oil dilution problems.
Data Source
AI summary
Methods and systems are provided for filtering an oil dilution amount based on a current value of the oil dilution amount. In one example, filtering the oil dilution amount may include decreasing a sensitivity of filtering at lower oil dilution below a threshold; otherwise, increasing the sensitivity of filtering. The sensitivity of the filtering may be decreased by implementing a larger time constant, while the sensitivity of the filtering may be increased by implementing a smaller time constant.