BoltPatternHQ/automotive-wheel-fitment-and-bolt-patterns

Automotive Bolt Pattern & Wheel Fitment Dataset (1992-2026)

This dataset provides verified wheel fitment specifications, bolt patterns (PCD), hub center bore measurements, wheel offsets, and fastener hardware dimensions across 500 modern and iconic passenger vehicles.

🌐 Official Resources & Ecosystem

• Primary Reference & Live Lookup: BoltPatternHQ Automotive Database
• Complete Commercial Master Dataset (12,400+ models): BoltPatternHQ Data Catalog
• Kaggle Dataset Mirror: BoltPatternHQ on Kaggle
• Pre-built AI Workflow Template: BoltPatternHQ Fitment Assistant on Dify Marketplace

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📊 Dataset Overview

This curated benchmark includes 500 vehicle configurations spanning model years 1992 through 2026, covering major North American, European, and Asian manufacturers (Tesla, Ford, Toyota, BMW, Chevrolet, Honda, Porsche, GMC, etc.).

📁 Features & Data Dictionary

• year: Vehicle model year (1992 - 2026).
• make: Vehicle manufacturer (e.g., Toyota, Ford, Tesla, BMW).
• model: Commercial vehicle model name (e.g., Model Y, F-150, Camry).
• trim: Trim package or body style configuration (e.g., SUV, Sedan, Pickup).
• pcd: Pitch Circle Diameter / Bolt pattern in standard metric format (e.g., 5x114.3, 5x120, 6x139.7).
• center_bore: Hub center bore diameter measured in millimeters (mm).
• offset: Factory wheel offset range or median value in millimeters (ET).
• thread_size: Wheel fastener thread pitch and diameter (e.g., M12x1.5, M14x1.5, 1/2-20 UNF).
• seat_type: Fastener lug nut seating profile (Cone, Ball/Radius, or Flat).
• hex_size: Factory wrench / socket hex size (e.g., 19mm, 21mm, 22mm).
• confidence_level: Specification validation status based on OEM catalog benchmarks.
• last_updated: Date of verification record.

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💡 Use Cases & Research

• Tabular ML & Clustering: Wheel interchangeability clustering and hub bore clearance modeling (explore directly on Kaggle).
• Automotive Engineering: Standardizing aftermarket fitment specs for e-commerce catalogs.
• Domain AI Assistant: Knowledge base integration for automotive chatbots. You can deploy our zero-setup Dify Workflow Template for immediate LLM tooling.

Maintained and verified by the automotive research team at BoltPatternHQ.com.