Vehicle Bus Platform Identification Without VIN Lookup

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Solution Overview

Problem

Existing telematics devices rely on VIN lookup services for vehicle identification, which are not available in many countries and incur fees, and fail to account for vehicle module variations within the same YMM, leading to inadequate communication configuration.

Innovation Solution

A telematics device uses machine learning to analyze vehicle bus data, identifying a vehicle platform by matching collected data with a reverse-engineered database, determining a set of configuration settings, including OBD-II PIDs, without relying on VIN lookup services.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If VIN lookup services are used for vehicle identification, then vehicle identity can be obtained, but the service is not available in many countries and incurs fees

Engineering Contradiction:

Improvevehicle identification accuracyVSAvoidglobal availability

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The telematics device performs self-identification by autonomously analyzing vehicle bus data and module information to determine vehicle platform and configuration parameters without requiring external VIN lookup services, eliminating dependency on unavailable third-party services

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system extracts vehicle identification information directly from the vehicle's own bus communication data and module responses, separating the identification process from external services by utilizing internally available vehicle data

Inventive Principle:

Principle #2Taking out (Extraction)

2Measurement precision

If VIN lookup services are used for vehicle identification, then vehicle identity can be obtained, but fees are incurred

Engineering Contradiction:

Improvevehicle identification accuracyVSAvoidinstallation cost

Core Design Contradiction:

Measurement precisionVSLoss of energy

Solution Approach 1:

The device autonomously determines vehicle platform and configuration parameters by analyzing bus communication data and module responses, eliminating the need to pay fees for external VIN lookup services

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system uses free, readily available bus communication data and module information instead of expensive commercial VIN lookup services, replacing costly external resources with inexpensive internal vehicle data

Inventive Principle:

Principle #27Cheap short-living objects (Disposable)

3Ease of manufacture

If vehicle identification is based on YMM (year, make, model), then general configuration can be obtained, but vehicle module variations within the same YMM are not accounted for

Engineering Contradiction:

Improveconfiguration simplicityVSAvoidcommunication configuration accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The system transitions from uniform YMM-based configuration to platform-specific configuration by identifying the actual vehicle platform through bus data analysis, allowing different configuration parameters for different platforms even within the same YMM, thereby accounting for module variations

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The configuration approach changes from static YMM-based settings to dynamic platform-identified settings, where the system adaptively determines the correct vehicle platform and retrieves appropriate configuration parameters based on actual bus communication characteristics

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12541684B2Systems and methods for identifying a vehicle platform using machine learning on vehicle bus data

Publication Date: 2026.02.03 CALAMP CORP

AI summary

Embodiments of the invention include a vehicle telematics system that obtains vehicle bus data for a time period, determines identification information regarding a vehicle platform using a machine learning process on the vehicle bus data, and obtains a set of communication data for communicating with at least one vehicle module on the vehicle bus based on the identified vehicle platform.