Internal Combustion Engine Adaptation via Adjacency Matrix
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Solution Overview
Problem
Current methods for optimizing internal combustion engines are inefficient and unsafe due to the lack of consideration for environmental conditions and system states during the adaptation of sensors and actuators, leading to unnecessary measurement data recordings and suboptimal adjustment processes.
Innovation Solution
A method that uses a control program to prioritize and sequence adaptation processes based on the quality of individual adaptation processes, ambient conditions, and operating point parameters, represented through an adjacency matrix, ensuring that adjustments are only made when suitable conditions are met, thereby optimizing the interaction between sensors, actuators, and the control unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If adaptation processes are carried out without considering environmental conditions and system states, then the optimization process can proceed continuously, but unnecessary measurement data recordings are performed and adjustment processes are carried out under unsuitable conditions reducing safety and efficiency
Solution Approach 1:
The control program checks environmental conditions and system states before initiating adaptation processes. This preliminary verification ensures that only suitable conditions exist before starting measurement data recordings and adjustment operations, preventing wasteful operations under unsuitable conditions while maintaining continuous optimization capability when conditions are favorable
Solution Approach 2:
The control program continuously monitors environmental conditions and system states, using this feedback information to determine whether adaptation processes should be initiated. The monitoring of quality of individual adaptation processes, ambient conditions, and operating point parameters creates a closed-loop system that dynamically adjusts the optimization process based on current conditions, eliminating unnecessary operations
2Device complexity
If all adaptation processes are started simultaneously without quality dependency checking, then the optimization process is simpler to implement, but the interaction dependencies between mechatronic subsystems are not respected leading to unsafe or inefficient adjustments
Solution Approach 1:
The control program is segmented into distinct functional modules: one for checking environmental conditions, another for monitoring system states, a third for evaluating quality of individual adaptation processes, and a fourth for determining initiation criteria. This modular segmentation makes the complex dependency management more manageable while ensuring that adaptation processes are started only when quality dependencies and environmental conditions are satisfied, guaranteeing safe and efficient adjustments
Solution Approach 2:
The control program dynamically determines which adaptation processes to initiate based on real-time evaluation of quality dependencies, ambient conditions, and system states. Rather than a static simultaneous startup approach, the system adaptively selects and sequences adaptation processes based on current conditions, ensuring that dependent processes are started only after their prerequisites are met, thereby ensuring reliability while managing complexity
3Adaptability or versatility
If adaptation processes are initiated without checking ambient conditions and operating point parameters, then the optimization can proceed at any time, but adjustments are made under unsuitable conditions reducing the security and efficiency of the mechatronic system
Solution Approach 1:
The control program changes the parameter of initiation criteria by introducing checks for environmental conditions and system states as gatekeepers for adaptation process startup. This parameter change transforms the optimization process from one that can run continuously to one that dynamically adapts its operation based on environmental and system parameters, ensuring that adjustments are only made when security and efficiency conditions are met while maintaining flexibility when conditions are favorable
Data Source
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AI summary
The method involves describing cooperation of an internal combustion engine (1), sensors (2-7), actuators and a control device (1e) by functional correlation. Individual adaptation processes are executed during development of the engine for optimal cooperation of the sensors, actuators and engine. An adjacency matrix is formed by partial matrices, and a reference-adjacency matrix is formed, where the processes are started and executed based on quality of the processes, environmental conditions, system condition of the engine and comparison of the reference matrix with the adjacency matrix.