Injection System Correction Curve for Fuel Pressure Control
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Solution Overview
Problem
Existing injection systems face challenges in accurately controlling fuel pressure due to component tolerances and drifts, leading to deteriorated controller behavior and safety issues, as they struggle to account for the sum tolerance of various components involved in the system.
Innovation Solution
A learning function is implemented to detect and correct deviations in the pump characteristic curve by calculating a correction characteristic curve that accounts for the sum tolerance of all components, using a PIDT1 controller and pre-checking devices to adapt the fuel pump and engine characteristic maps, thereby improving the system's robustness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a learning function is implemented to detect and correct deviations in the pump characteristic curve, then the accuracy of fuel pressure control is improved, but the device complexity increases
Solution Approach 1:
The patent implements a learning function that continuously monitors the actual pump characteristic curve and compares it with the nominal curve, using feedback to detect deviations and automatically compute correction values. This closed-loop feedback mechanism enables accurate fuel pressure control by adaptively compensating for component tolerances and drifts without requiring manual recalibration.
Solution Approach 2:
The control unit performs self-learning by automatically detecting deviations in the pump characteristic curve during normal operation and generating correction values without external intervention. The system serves itself by continuously adapting the characteristic curve based on measured deviations, eliminating the need for manual adjustment or external calibration equipment.
2Reliability
If correction values are computed and stored for component tolerances and drifts, then the reliability of the injection system is improved, but the loss of information increases due to additional data storage requirements
Solution Approach 1:
The patent extracts only the essential correction information from the complex deviation analysis, storing specifically the correction values for the characteristic curve rather than all raw measurement data. This selective extraction approach maintains reliability by preserving the critical correction parameters while minimizing data storage requirements by excluding redundant information.
Solution Approach 2:
The system transforms the raw deviation data into corrected characteristic curve parameters, changing the form of stored information from detailed measurement data to condensed correction values. This parameter transformation reduces information storage requirements while maintaining the essential correction functionality needed for reliable operation.
3Manufacturing precision
If the learning function detects the sum tolerance of multiple components, then the manufacturing precision of the system is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent merges the tolerance detection of multiple individual components into a single integrated learning function that measures the overall system characteristic curve. Instead of separately detecting and measuring each component's tolerance, the system combines them into a unified pump characteristic curve measurement, simplifying the detection process while maintaining comprehensive tolerance control.
Solution Approach 2:
The learning function acts as an intermediary that translates complex multi-component tolerance interactions into a single measurable pump characteristic curve. This intermediary approach simplifies measurement by using the overall system behavior as a proxy for individual component tolerances, making the detection process more manageable while still achieving precise manufacturing control.
Data Source
AI summary
A method for determining a correction characteristic curve for adapting a characteristic curve of an injection system, in which the correction characteristic curve includes at least one deviation of a measured characteristic curve from a setpoint characteristic curve, the at least one deviation including a sum tolerance of at least two components of the injection system, which have an effect on the characteristic curve.