Knock Sensor Feedback for Engine Event Timing
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Solution Overview
Problem
Existing methods for determining the timing of engine events in combustion engines are expensive, complex, and often require operator input or specific engine-type dependencies, making them inefficient and costly.
Innovation Solution
A control system that utilizes feedback from a knock sensor to estimate engine events by applying an Empirical Transform Function (ETF) based on Fourier transforms of knock and engine parameter signals, allowing for the adjustment of engine operation without the need for expensive sensors or complex algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing techniques are used to determine the location of engine events, then measurement precision may be adequate, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses a knock sensor to detect vibrations that correlate with engine events, creating a simplified proxy measurement system. Instead of directly measuring complex engine parameters with sophisticated sensors, the system copies the information through vibration analysis, achieving adequate measurement precision with reduced device complexity
Solution Approach 2:
The patent replaces complex mechanical measurement systems with signal processing approaches. By using Fourier transforms and empirical transfer functions to analyze knock sensor signals, the system substitutes direct mechanical measurement with computational analysis, reducing both device complexity and cost while maintaining measurement capability
2Measurement precision
If existing techniques are used to determine the location of engine events, then measurement precision may be adequate, but cost increases significantly
Solution Approach 1:
The patent employs a knock sensor, which is a relatively inexpensive component compared to sophisticated engine event measurement systems. The system accepts that the sensor operates in a harsh environment and focuses on extracting useful information through signal processing, achieving cost-effective measurement by using simple, replaceable sensors rather than expensive durable measurement devices
Solution Approach 2:
The patent replaces expensive mechanical measurement systems with computational signal processing. By using Fourier transforms and empirical transfer functions to analyze knock sensor signals, the system substitutes costly hardware with software-based analysis, significantly reducing the overall system cost while maintaining measurement precision
3Measurement precision
If existing techniques are used to determine the location of engine events, then measurement precision may be adequate, but operator input and engine-specific calibration are required
Solution Approach 1:
The patent implements a system that performs self-calibration through the training phase, where the control system learns the empirical transfer function by analyzing correlations between knock sensor signals and actual engine events. Once trained, the system operates autonomously without requiring operator input or engine-specific calibration, achieving ease of operation while maintaining measurement precision across different engine types
Solution Approach 2:
The patent uses feedback from the knock sensor signals to continuously refine and update the empirical transfer function. The system analyzes the correlation between detected vibrations and engine events, automatically adjusting its measurement approach based on observed patterns, thereby eliminating the need for manual calibration and operator intervention
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 enables accurate and cost-effective estimation of engine events, such as peak firing pressure, allowing for optimized engine performance without operator input and reducing the complexity of calculations.
Implementation Method 1
receive feedback from at least one knock sensor coupled to a reciprocating engine
Implementation Method 2
receive feedback from at least one knock sensor coupled to a reciprocating engine
Implementation Method 3
determine a plurality of Empirical Transfer Function Estimates (ETFEs), where a respective ETFE of the plurality of ETFEs is based at least on a Fourier transform of a respective knock signal of the plurality of knock signals and on a Fourier transform of a respective engine parameter signal of the plurality of engine parameter signals
Data Source
AI summary
Systems and methods for estimating an engine event location are disclosed herein. In one embodiment, a control system is configured to receive feedback from at least one vibration sensor coupled to a reciprocating engine, estimate an engine parameter based at least on the feedback and an Empirical Transform Function (ETF), estimate a location of an engine event based on the engine parameter, and adjust operation of the reciprocating engine based at least on the location of the engine event.