Vehicle Diagnosis System Using Dynamic Fault Prioritization
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Solution Overview
Problem
Diagnosing vehicle faults in modern vehicles with complex electronic systems is challenging due to the need for accurate translation of symptoms into specific vehicle systems, often resulting in an excessively large list of possible symptoms that is impractical to narrow down.
Innovation Solution
A vehicle diagnosis system that includes a data storage medium with a sortable list of probable component faults organized by vehicle year, make, and model, linked to a diagnosis program that receives user input and updates probabilities, providing a prioritized list of likely vehicle systems associated with the fault, allowing for efficient identification and correction of the fault.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a comprehensive list of all possible vehicle systems is provided to the user, then the list is complete and covers all potential faults, but the list becomes excessively large and impractical to narrow down
Solution Approach 1:
The patent segments the comprehensive list of vehicle systems into hierarchical categories and subcategories. The system divides the diagnostic process into multiple levels where users first select broad system categories, then progressively narrow down to specific components. This segmentation transforms an overwhelming single list into a manageable structured hierarchy, maintaining completeness while improving usability.
Solution Approach 2:
The system dynamically adjusts the list of displayed vehicle systems based on the user's input symptoms and selections. As users provide more specific symptom information or select categories, the system dynamically filters and reorders the remaining options to show only relevant systems. This dynamic adaptation keeps the displayed list manageable in size while maintaining comprehensive coverage of all potential faults.
2Ease of operation
If symptom-driven diagnosis is used where customers describe perceived faults, then the diagnostic process is simple and intuitive, but accurate translation of symptoms to vehicle systems becomes unreliable
Solution Approach 1:
The patent introduces an intermediary diagnostic system that acts as a bridge between customer symptom descriptions and vehicle system identification. The system includes a processor that receives customer input, compares it against a database of known symptoms and their associated vehicle systems, and generates a ranked list of probable systems. This intermediary processing layer translates imprecise customer language into accurate system identification without requiring customers to understand technical vehicle systems.
Solution Approach 2:
The system incorporates feedback mechanisms where the diagnostic results are presented to users, who can then provide additional input or clarify symptoms. The system uses this feedback to refine and re-run the diagnostic algorithm, improving the accuracy of symptom-to-system translation through iterative refinement based on user responses.
3Loss of time
If traditional symptom-driven evaluation is used without system-based analysis, then the diagnostic process is quick, but the determination of causing systems is inaccurate
Solution Approach 1:
The patent implements preliminary action by pre-organizing a comprehensive database of vehicle systems, components, and their associated symptoms before the diagnostic process begins. The system pre-calculates and stores the relationships between symptoms and potential causing systems, allowing for rapid retrieval and analysis during actual diagnostics. This preliminary preparation enables both speed and accuracy by having all necessary information readily available without requiring complex real-time analysis.
Data Source
AI summary
A method of diagnosing a vehicle fault includes receiving information on a vehicle from a customer regarding an actual vehicle fault and accessing data regarding the actual vehicle fault from the vehicle. A diagnostic program is initiated based on identifying vehicle information, the information received from the customer, and the data accessed from the vehicle. A specific vehicle system is selected for diagnosis and includes a particular vehicle component that may be associated with the actual vehicle fault. A list of diagnostic program results is received that defines multiple probable vehicle component faults for the specific vehicle system that may be associated with the actual vehicle fault. A determination on how to proceed with correcting the actual vehicle fault is made based on the list of diagnostic program results that define multiple probable vehicle component faults. A probable vehicle component fault is selected to evaluate whether it is the source of the actual vehicle fault.