Remote Vehicle Diagnostics for Accurate Battery Assistance Dispatch
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Solution Overview
Problem
Current roadside assistance systems often dispatch vehicles that are not equipped to address the specific issues of distressed vehicles, leading to increased costs and delays due to a lack of clarity or accuracy in diagnosing vehicle problems, particularly with battery-related issues.
Innovation Solution
A remote diagnostic system that uses connected vehicle data, diagnostic trouble codes, and battery health data to differentiate between serviceable and faulty batteries, allowing for accurate decision-making on the required roadside assistance actions, such as jump starts or towing, by analyzing vehicle health reports and prognostic information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If roadside assistance vehicles are dispatched without accurate diagnostic information, then response time is reduced, but the wrong type of assistance may be dispatched requiring second dispatches
Solution Approach 1:
The system performs preliminary diagnostic actions by automatically collecting and analyzing vehicle data before dispatching assistance. The remote diagnostic server retrieves vehicle identification information, queries the database for diagnostic trouble codes and vehicle parameters, and determines the required assistance type in advance, ensuring both rapid response and accurate dispatch decisions.
Solution Approach 2:
The system implements feedback mechanisms where diagnostic trouble codes and vehicle status information are continuously monitored and fed back to the dispatch system. This feedback loop enables real-time assessment of vehicle conditions and automatic adjustment of assistance dispatch decisions based on actual vehicle diagnostics rather than estimates.
2Measurement precision
If comprehensive vehicle diagnostic data is collected and analyzed, then diagnostic accuracy is improved, but system complexity increases
Solution Approach 1:
The remote diagnostic server acts as an intermediary between the vehicle's electronic control units and the roadside assistance dispatch system. It automatically collects diagnostic data from multiple ECUs, processes the information against stored vehicle parameters and diagnostic criteria, and translates complex diagnostic results into simple dispatch instructions, reducing the complexity burden on the overall system.
Solution Approach 2:
The diagnostic system performs self-service by automatically retrieving vehicle identification information, querying diagnostic trouble codes from the database, analyzing vehicle parameters, and determining assistance requirements without human intervention. This automation handles the complexity internally while presenting simple outcomes to dispatch operators.
3Reliability
If multiple data sources are integrated for vehicle diagnostics, then reliability of diagnosis is improved, but data processing requirements increase
Solution Approach 1:
The system extracts only the essential diagnostic information needed for accurate dispatch decisions from the vast amount of available vehicle data. It selectively retrieves diagnostic trouble codes, vehicle identification information, and specific parameters relevant to determining assistance requirements, rather than processing all possible vehicle data, thus reducing processing requirements while maintaining diagnostic reliability.
Data Source
AI summary
A remote diagnostic system for a vehicle may include a power source configured to provide power to vehicle Electronic Control Modules (ECUs), an in-vehicle network to collect data from the ECUs; a modem configured to receive the collected data from the ECUs and transmit the data to a remote database; a processor configured to analyze the collected data stored in the remote database; determine a health of the vehicle based on the analysis of the collected data; and transmit an action to at least one road side assistance partner based upon the determined health of the vehicle.