Vehicle Diagnostic Workflow Using Topology-Aware Automation
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Solution Overview
Problem
Existing vehicle diagnostic and configuration systems require detailed knowledge of vehicle configuration, network topology, and end point locations, leading to complexity, delays, and increased costs in implementing monitoring, testing, diagnostic, and maintenance operations.
Innovation Solution
A system and method for performing vehicle diagnostic and configuration operations that allows users to implement monitoring, testing, diagnostic, and maintenance (MTDM) operations without requiring detailed knowledge of vehicle configuration, using a flexible and configurable Controller V to manage communications and operations across various network zones, enabling efficient rollout of updates and configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed knowledge of vehicle configuration, network topology, and end point locations is required for diagnostic operations, then diagnostic capability and precision are improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The patent introduces an intermediary system that automatically discovers vehicle network topology and endpoint locations, acting as a mediator between the user and the complex vehicle diagnostic system. This intermediary handles the complexity of network exploration and configuration automatically, allowing users to perform diagnostics without needing detailed knowledge of the underlying system architecture.
Solution Approach 2:
The system performs self-service by automatically discovering and mapping the vehicle network topology, identifying endpoints, and configuring communication paths without requiring manual intervention or expert knowledge. The system serves itself by autonomously navigating the complex diagnostic environment and preparing the necessary configuration information.
2Measurement precision
If detailed knowledge of vehicle configuration is required for diagnostic operations, then diagnostic precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system acts as an intermediary that translates complex vehicle configuration details into simple, user-friendly diagnostic operations. It automatically handles network topology discovery and endpoint identification, presenting simplified interfaces to users while maintaining high diagnostic precision through automated configuration management.
Solution Approach 2:
The system performs preliminary actions by automatically discovering and storing vehicle network topology and endpoint information before diagnostic operations are needed. This pre-configured knowledge base enables users to perform diagnostics immediately without needing to learn complex configuration details, thus improving ease of operation while maintaining diagnostic precision.
3Reliability
If software updates are implemented frequently to improve vehicle operations, then feature capability and reliability are improved, but loss of time and productivity deteriorate due to downtime
Solution Approach 1:
The system performs preliminary configuration and diagnostic setup automatically before updates are applied, storing necessary network and endpoint information in advance. This allows updates to be deployed more quickly with minimal disruption, reducing downtime while maintaining or improving vehicle reliability through timely updates.
Solution Approach 2:
The patent replaces manual configuration and diagnostic procedures with automated electronic systems that can be updated and reconfigured remotely. This substitution enables faster deployment of updates without requiring physical intervention or extended vehicle downtime, thus improving reliability while minimizing time loss.
4Reliability
If comprehensive monitoring and diagnostic operations are performed across all vehicle components, then reliability and detection precision are improved, but use of energy and device complexity increase
Solution Approach 1:
The system applies local quality by performing comprehensive monitoring only where and when needed, rather than uniformly across all vehicle components. It uses automated network discovery to identify critical endpoints and focuses diagnostic resources on those areas, maintaining high reliability while reducing overall energy consumption by avoiding unnecessary monitoring of non-critical systems.
Data Source
AI summary
A system for performing an MTDM workflow. The system includes a vehicle data platform and a vehicle automation platform. The vehicle data platform is configured to provide a policy to a vehicle, where the policy includes an MTDM workflow element. The vehicle automation platform is configured to provide a recipe to the vehicle, where the recipe includes actions for an automated vehicle response. The vehicle data platform is further configured to receive collected data from the vehicle in response to an execution of at least one of the MTDM workflow element or the automated vehicle response by a controller of the vehicle.