Vehicle Buffer Data Archiving for Remote Diagnostic Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle diagnostic methods rely heavily on fault codes, which are insufficient for accurately diagnosing complex or unusual vehicular system failures, as they do not provide enough contextual data, and existing data logging systems are not designed for long-term use or efficient storage of operational data.
Innovation Solution
A system that temporarily stores operational data in a vehicle buffer and archives it when a fault code is generated, allowing for contextual linking with the fault code, enabling real-time diagnosis by conveying this data to a remote computing device for analysis, which can identify anomalies and predict specific failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all operational data is stored for later analysis, then diagnostic accuracy is improved, but storage requirements and system complexity increase significantly
Solution Approach 1:
The patent extracts only the essential operational data needed for diagnosis by using fault codes to represent specific undesirable operating parameters. Instead of storing all raw operational data, the system monitors operational data and stores only the fault codes that correspond to detected anomalies, dramatically reducing storage requirements while maintaining diagnostic capability.
Solution Approach 2:
The patent transforms continuous operational data into discrete fault code parameters. By converting analog operational parameters into coded representations (e.g., fault code 11 for battery voltage anomalies), the system reduces data volume while preserving diagnostic information, allowing efficient storage and retrieval without sacrificing diagnostic accuracy.
2Quantity of substance
If fault codes are used to reduce data storage, then storage efficiency is improved, but diagnostic capability for complex failures deteriorates
Solution Approach 1:
The patent performs preliminary action by pre-defining fault codes for specific undesirable operating parameters before they occur. The system monitors operational data against these predefined conditions and automatically generates fault codes when anomalies are detected, enabling efficient storage of diagnostic information without losing the ability to diagnose complex failures.
Solution Approach 2:
The patent introduces fault codes as intermediary elements between raw operational data and diagnostic analysis. These fault codes serve as compressed representations that bridge the gap between continuous operational parameters and discrete diagnostic categories, allowing efficient storage while maintaining comprehensive diagnostic capability through the structured code system.
3Quantity of substance
If operational data is not stored, then storage resources are preserved, but contextual information for accurate diagnosis is lost
Solution Approach 1:
The patent extracts and stores only the essential contextual information needed for diagnosis by generating fault codes that represent specific undesirable operating parameters. Instead of storing all operational data, the system captures only the diagnostically relevant information in compressed fault code format, preserving contextual information while conserving storage resources.
Data Source
AI summary
Operational data generated and used in a vehicle to control various vehicular systems is temporarily stored in a data buffer in the vehicle. A processor in the vehicle is configured to detect anomalous conditions, which can be based on predefined fault codes or user defined conditions (based on a single parameter or a combination of parameters). Whenever such an anomaly is detected, a diagnostic log is conveyed from the vehicle to a remote location. Such a log will include the detected anomaly, and buffered operational data. In at least one embodiment, the diagnostic log includes buffered operational data collected both before and after the anomaly. The diagnostic log is analyzed at the remote location to diagnose the cause of the anomalous condition so a decision can be made as to whether the vehicle requires immediate repair, or whether the repair can be scheduled at a later time.


