Engine Component Diagnostic Compensation Learning Strategy

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Solution Overview

Problem

Existing diagnostic strategies for internal combustion engine components often result in intrusive tests due to the influence of learning compensation from one component on the diagnostic observation of another, leading to performance deviations and failure to meet certain performance targets.

Innovation Solution

A compensation learning strategy is employed where an electronic controller identifies and counters drift in operating parameters by applying direct parameter compensation without altering the actuator command, using mathematical relationships or look-up tables to maintain pre-combustion temperature and reduce emissions effectively.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If learning compensation is applied to counteract drift in the first operating parameter, then the first mode of operation performance is improved, but the diagnostic observation of the second operating parameter becomes intrusive and may fail to meet performance targets

Engineering Contradiction:

Improvefirst mode of operation performanceVSAvoiddiagnostic observation of second operating parameter

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The patent segments the compensation application by creating two distinct compensation pathways: command compensation (applied to actuator commands) for the first operating parameter, and parameter compensation (applied directly to the operating parameter) for the second operating parameter. This segmentation allows independent handling of each parameter's diagnostic requirements without mutual interference.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary compensation mechanism that translates command compensation into parameter compensation through a mathematical relationship or lookup table. This intermediary layer enables the system to maintain the benefits of learning compensation while providing a clean diagnostic pathway for the second parameter by applying compensation indirectly rather than directly to the actuator command.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If command compensation is applied to counteract drift in the first operating parameter, then drift correction is achieved, but the actuator command is altered which may affect overall system performance

Engineering Contradiction:

Improvedrift correctionVSAvoidsystem performance

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The patent creates a copied version of the compensation effect by translating command compensation into parameter compensation. Instead of directly modifying the actuator command, the system copies the compensation effect and applies it to the operating parameter through a mathematical relationship or lookup table, thereby achieving drift correction without altering the original actuator command structure.

Inventive Principle:

Principle #26Copying

3Adaptability or versatility

If learning function is used to observe a second component parameter linked to a first component parameter, then diagnostic capability is enhanced, but the learning compensation of the first parameter influences the observation of the second parameter

Engineering Contradiction:

Improvediagnostic capabilityVSAvoidobservation accuracy of second parameter

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The patent extracts the compensation effect from the actuator command pathway and applies it separately to the operating parameter through parameter compensation. This extraction removes the interfering influence of learning compensation from the diagnostic observation of the second parameter, allowing the learning function to enhance diagnostic capability without compromising observation accuracy.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS10578045B1System and method for enhancing robustness of engine component diagnostic using compensation learning strategy

Publication Date: 2020.03.03 GM GLOBAL TECHNOLOGY OPERATIONS LLC

AI summary

A method using compensation learning strategy for a diagnostic of an internal combustion engine component includes operating the component via an actuator command to establish a first operating parameter representative of a first mode of component operation. The method also includes identifying a drift in the first parameter negatively affecting the first mode of operation. The method additionally includes determining compensation to the actuator command to counteract the first parameter drift during the first mode of operation. The method also includes determining compensation to the first parameter using the determined actuator command compensation. The method additionally includes applying the determined parameter compensation directly to the first parameter. The method also includes operating the component using the actuator command to establish a second operating parameter representative of a second mode of component operation. Furthermore, the method includes identifying a drift in the second parameter negatively affecting the second mode of operation.