Fuzzy Logic Curve Matching for Engine Air-Fuel Control
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Solution Overview
Problem
Current methods for analyzing time series data are complex and lack an efficient mechanism to identify patterns, making it difficult to apply solutions effectively, especially in real-time systems like automobile engines where air-fuel mixture adjustments are needed based on varying factors.
Innovation Solution
The implementation of a Fuzzy Logic-based controller that analyzes time series data from sensors, matches trends against standard curves, and adjusts system behavior accordingly, using a Fuzzy Controller embedded in the automobile engine's control system to optimize the air-fuel mixture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex mathematical methods are used for matching time series data curves, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mathematical curve matching methods with a fuzzy logic-based pattern recognition system. Instead of using sophisticated mathematical algorithms to compute similarity between time series curves, the invention uses fuzzy sets and linguistic variables to represent and match patterns, thereby reducing computational complexity while maintaining recognition accuracy.
Solution Approach 2:
The patent transforms the problem from matching raw time series data curves to matching extracted features (peaks, valleys, inflection points) using fuzzy logic. By changing the parameters from continuous curve values to discrete feature points with linguistic descriptors, the system achieves simpler computation while preserving essential pattern information.
2Ease of operation
If natural language description of curve shapes is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The patent introduces fuzzy sets and linguistic variables as an intermediary layer between natural language pattern descriptions and the actual time series data matching. This intermediary allows operators to specify patterns using simple linguistic terms (e.g., 'increasing', 'decreasing', 'peak') while the fuzzy logic system handles the complexity of translating these terms into precise matching operations.
3Productivity
If real-time sensor analysis is performed, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent segments the time series data into characteristic features (peaks, valleys, inflection points) rather than analyzing the entire continuous data stream. This segmentation reduces the amount of data that needs to be processed in real-time, enabling faster analysis while maintaining the capability to detect important pattern changes for immediate control adjustments.
Data Source
AI summary
Disclosed is a controller that includes a curve matching mechanism. The curve matching mechanism employs Fuzzy Logic to compare input curves to standard curves and to thereby characterize the input curves. Also disclosed in an automotive environment for the curve matching mechanism in which a Fuzzy Controller is used to receive time series data (i.e., input curves) and to present the input curves to the curve matching mechanism. The controller then uses the output of the curve matching mechanism to adjust engine function.