Fuel Injector Pressure Sensing for Wear-Adaptive Rate Modeling
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Solution Overview
Problem
Existing fuel injector systems suffer from inaccuracies in fuel injection modeling due to sensor signal amplitude changes caused by wear, leading to systematic errors in injection quantity estimation.
Innovation Solution
A method that uses time and volume flow rate data derived from a pressure sensor to correct an injection rate model, independent of sensor signal amplitude, by employing correlations between these data points and nozzle needle stroke, and adjusting the model based on actual injector conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed linear correlation between pressure drop and maximum injection rate is used, then the calculation is simple, but the injection quantity estimate becomes inaccurate due to sensor drift over time
Solution Approach 1:
The patent transforms the static fixed linear correlation into a dynamic adaptive model. The injection rate model is continuously corrected using actual sensor measurements from pressure sensors, allowing the system to adapt to sensor drift and wear over time. This dynamic adjustment maintains accuracy without requiring complex manual recalibration.
Solution Approach 2:
The patent implements feedback by using actual sensor signals from the pressure sensors to correct the injection rate model. The measured pressure data is fed back into the system to continuously update and refine the model parameters, ensuring that the injection quantity estimates remain accurate despite sensor degradation.
2Ease of operation
If sensor signal amplitude is used for injection quantity estimation, then the method is straightforward, but accuracy deteriorates due to wear-induced amplitude changes
Solution Approach 1:
The patent changes from using absolute sensor signal amplitude to using normalized pressure ratios and differential pressure measurements. These modified parameters are insensitive to sensor drift and wear, maintaining reliability while keeping the estimation method straightforward. The system uses ratios of pressure differences that cancel out the effects of amplitude degradation.
3Use of energy by moving object
If a simplified trapezoidal injection rate model is used, then computing resources are saved, but model accuracy decreases due to deviations from actual injection curves
Solution Approach 1:
The patent applies partial correction to the simplified trapezoidal model by using sensor data to adjust only the critical parameters (such as peak injection rate and timing) rather than reconstructing the entire injection curve. This maintains computational efficiency while improving accuracy where it matters most for injection quantity estimation.
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 enhances the accuracy of fuel injection modeling by minimizing model errors and accounting for injector wear, ensuring precise fuel delivery throughout its service life.
Implementation Method 1
the pressure in the control chamber is measured by means of a pressure sensor integrated into the injector
Implementation Method 2
Control of the pressure in the control chamber is accomplished by means of a control valve that regulates the pressure in the control chamber electromagnetically
Implementation Method 3
the pressure in a control chamber that applies a hydraulic closing force to the nozzle needle
Data Source
AI summary
The invention relates to a method for actuating an injector (1), in particular a fuel injector, wherein the stroke movement of a nozzle needle (2) for opening and closing at least one injection opening (3) is controlled by means of the pressure in a control chamber (4), and the pressure in the control chamber (4) is measured by means of a pressure sensor (5) integrated into the injector (1), wherein characteristic information, in particular time and volume flow rate data, is derived from the sensor signals from the pressure sensor (5) for the stroke movement of the nozzle needle (3) and is used to correct an injection rate model that is based on previously measured time and volume flow rate data.