Vehicle Diagnostics Using Mode $06 and IUMPR Fault Isolation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle diagnostic systems face challenges in accurately interpreting large amounts of data generated by modern vehicles, leading to ambiguous diagnostic results and difficulties in identifying underlying fault conditions, which are often beyond the capabilities of vehicle owners and even professional mechanics.
Innovation Solution
A diagnostic system and method that utilizes a data acquisition and transfer device (DAT) to analyze vehicle data, including diagnostic trouble codes and live data, to identify fault conditions through drive cycles, In-Use Monitor Performance Ratios (IUMPR), and Mode $06 data, employing machine learning to autonomously diagnose and initiate special tests on components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive vehicle data analysis is performed to improve diagnostic accuracy, then diagnostic precision is improved, but device complexity and user capability requirements increase
Solution Approach 1:
The patent introduces an automated diagnostic system that acts as an intermediary between the vehicle's complex data systems and the end user. This system automatically retrieves DTCs, analyzes monitor data, performs drive cycle management, and presents simplified diagnostic conclusions, thereby maintaining high diagnostic accuracy while shielding users from system complexity.
Solution Approach 2:
The diagnostic system performs self-service by automatically executing diagnostic routines, retrieving necessary data, managing drive cycles, and generating diagnostic reports without requiring user expertise in data analysis. The system independently processes complex analytical tasks while presenting simplified results to users.
2Loss of information
If comprehensive vehicle data is collected and analyzed, then diagnostic information completeness is improved, but difficulty of detecting and measuring fault conditions increases
Solution Approach 1:
The patent segments the comprehensive diagnostic data into structured components including DTCs, monitor data, drive cycle status, and IUMPR metrics. Each segment is analyzed separately by dedicated system functions, making the complex diagnostic process manageable while maintaining complete information utilization.
Solution Approach 2:
The automated diagnostic system serves as an intermediary that processes and interprets complex diagnostic data, transforming raw comprehensive information into actionable diagnostic conclusions. The system handles the complexity of analyzing multiple data sources while presenting simplified fault condition assessments to users.
3Productivity
If automated diagnostic analysis is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The diagnostic system performs self-service by automatically executing diagnostic routines, retrieving data, analyzing results, and generating reports without requiring manual intervention for each diagnostic step. This automation significantly improves diagnostic productivity while the system manages its own complexity internally.
Solution Approach 2:
The system performs preliminary actions by pre-configuring diagnostic routines, pre-identifying necessary data parameters, and pre-managing drive cycle requirements. This preliminary preparation enables efficient automated execution while consolidating complexity into pre-established system structures.
4Loss of information
If detailed diagnostic data is presented to users, then diagnostic information completeness is improved, but ease of operation decreases
Solution Approach 1:
The patent segments diagnostic information into hierarchical levels of detail. The system maintains complete diagnostic data internally while presenting segmented, organized results to users based on their needs. Critical fault information is highlighted separately from comprehensive technical data, improving ease of operation while preserving information completeness.
Solution Approach 2:
The automated diagnostic system acts as an intermediary that translates comprehensive technical diagnostic data into user-friendly diagnostic conclusions. The system filters and presents only the most relevant information to users while maintaining access to complete diagnostic data for further analysis if needed.
Data Source
AI summary
An automotive diagnostic method aimed at focusing diagnostic data retrieval and analysis on a possible fault condition includes receiving vehicle data from a vehicle at a data acquisition and transfer device (DAT) and analyzing the vehicle data to identify a possible fault condition. A drive cycle associated with the identified possible fault condition is identified, and driving conditions are monitored to identify completion of the identified drive cycle. Upon completion of the identified drive cycle, vehicle data is analyzed to identify an abnormal monitor. Vehicle data is also analyzed to identify an abnormal value of In-Use Monitor Performance Ratio (IUMPR) associated with the abnormal monitor. When an abnormal value of IUMPR is identified, a likely diagnostic condition associated with the identified abnormal IUMPR is further identified.