Engine Control Learning During Non-Learning Processes
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Solution Overview
Problem
Internal combustion engines with automatic stop systems face challenges in performing learning processes due to rare loadless and idle conditions, leading to increased fuel consumption as existing methods inhibit engine stop only through non-learning processes without optimizing fuel savings.
Innovation Solution
Parallelizing learning processes with verification and/or restoration processes that inhibit engine stop without altering engine speed, allowing learning processes to occur during non-learning processes like air-conditioner activation or battery recharging, which absorb torque or alter engine parameters within predetermined limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the engine stop is inhibited only through non-learning processes, then learning processes can be performed, but fuel consumption increases due to unnecessary idle operation
Solution Approach 1:
The system dynamically changes the operating parameters of the engine by allowing it to operate under load during learning processes rather than maintaining idle conditions. This parameter change from idle speed to loaded operation reduces fuel consumption while still enabling learning processes to occur through the parallel execution mechanism.
Solution Approach 2:
The system ensures continuous useful action by allowing the engine to remain operational and perform useful work (driving the vehicle) while simultaneously executing learning processes. This eliminates the need to idle the engine specifically for learning, as learning can occur during normal operation, thus avoiding wasted fuel consumption.
2Measurement precision
If the engine operates in loadless and idle conditions for learning processes, then learning can be performed, but the engine stop system cannot function properly
Solution Approach 1:
The system segments the learning process into multiple smaller steps that can be executed sequentially during different phases of engine operation. This allows the learning process to be divided into stages, where some steps can be performed during idle conditions and others during loaded operation, enabling the engine stop system to function while still completing the learning process.
Solution Approach 2:
The system dynamically adapts the learning process execution to the current operating conditions. When the engine is under load, the learning process continues in parallel; when idle conditions occur, the learning process can be completed or paused. This dynamic approach allows the engine stop system to operate normally while still achieving learning objectives.
3Reliability
If verification and restoration processes inhibit engine stop, then engine control is maintained, but fuel savings are reduced
Solution Approach 1:
The system merges the verification/restoration processes with the learning process execution. By combining these functions into a unified control strategy where learning processes are prioritized and allowed to run in parallel with verification activities, the system maintains engine control reliability while minimizing the inhibition of engine stop, thus optimizing fuel savings.
Data Source
AI summary
System for controlling an internal combustion engine, the system comprising stop means to stop automatically an internal combustion engine according to a predefined operating condition of the internal combustion engine, verification and/or restoration means to verify or to restore a first component of the internal combustion engine, learning means to learn a control variable of a second component of the internal combustion engine, inhibition means of the stop means to prevent/ignore an engine stop, wherein only the verification and/or restoration means, when activated, are suitable to cause an activation of the inhibition means, and wherein the learning means are enabled to activate only when the verification and/or restoration means are active.