Canon Map — Stunspot’s Guide to Automotive Systems

The Automotive Systems Canon maps vehicle knowledge as a causal system: machine physics, platform architecture, manufacturing reality, ownership economics, regulation, energy infrastructure, diagnostic evidence, and practitioner workflow.

This page explains the report sequence. For upload guidance, see Knowledge Packs. For workflow guidance, see How to Use This Canon.

Canon Logic

The sequence moves from legibility to mechanism to context to judgment.

1. A-D make the field legible. They define the vehicle as a multi-role artifact, establish physical primitives, explain platforms and architecture, and situate automotive technology inside industrial and cultural change.
2. E-J map the operating domains. They cover propulsion, chassis behavior, body/cabin/interface systems, electrical/software architectures, manufacturing quality, supply chain constraints, and ownership economics.
3. K-M map external pressure and specialized trade-offs. They cover safety law, regulation, emissions, energy transition, EV infrastructure, environmental burdens, motorsport, modification, durability, and ruleset constraints.
4. N-O convert knowledge into field judgment. They establish diagnostic discipline, root-cause logic, inspection systems, repair verification, build sheets, restoration maps, and decision artifacts.

The canon’s center of gravity is not “cars as objects.” It is automotive systems as interacting constraints.

Source Reports

A-D — Foundations: How the Field Becomes Legible

• A. Automotive Systems Reality Model — Mobility, Machines, Markets, and Institutions as One Causal System
  Defines the vehicle as a multi-role artifact: mobility machine, financed asset, safety envelope, repair object, emissions source, data node, cultural signal, and lifecycle burden. Use this report to prevent narrow reasoning that treats a vehicle as only engineering, only market, or only brand reputation.

• B. Automotive Systems Physics — Motion, Energy, Traction, Heat, Structure, and Control
  Establishes the physical grammar of automotive reasoning: force, mass, torque, power, drag, heat, traction, braking, structure, and feedback control. Use this report when a claim needs to be reduced to physical mechanisms.

• C. Automotive Systems Architecture — Platforms, Packaging, Interfaces, Modularity, and Design Constraint Logic
  Explains how platforms, hardpoints, packaging decisions, modularity, interfaces, and architecture choices constrain what a vehicle can become. Use this report for vehicle design analysis, platform comparisons, EV-retrofit limitations, and architectural trade-offs.

• D. Automotive Systems Evolution — Design Eras, Technology Diffusion, Cultural Meaning, and Industrial Change
  Places vehicles inside historical, industrial, and cultural transitions. Use this report to explain why technologies diffuse unevenly, why design eras matter, and why automotive meaning changes across markets and time.

E-J — Operating Domains: Where the Real Work Happens

• E. Automotive Propulsion Systems — Internal Combustion, Hybrid, Electric, Fuel, Air, Heat, and Drivetrain Logic
  Treats the powertrain as an energy-conversion chain across energy, torque, heat, control, and failure paths. Use this report for ICE, hybrid, EV, drivetrain, cooling, emissions, efficiency, and propulsion failure analysis.

• F. Automotive Chassis and Vehicle Dynamics Systems — Suspension, Steering, Brakes, Tires, Handling, Ride, and Road Feel
  Maps the mechanical systems that convert driver intent and road contact into stability, comfort, braking, grip, and handling. Use this report for tire, suspension, steering, brake, ride-quality, and dynamics questions.

• G. Automotive Body, Cabin, and Human Interface Systems — Exterior Design, Interior Ergonomics, Safety Space, Visibility, Comfort, and Meaning
  Covers the vehicle as occupied space, visual object, crash shell, ergonomic environment, and symbolic artifact. Use this report for cabin usability, design meaning, visibility, comfort, safety packaging, and human-interface critique.

• H. Automotive Electrical, Electronic, and Software Systems — Sensors, Networks, Control Modules, Diagnostics, ADAS, Infotainment, and Software-Defined Vehicles
  Frames the modern vehicle as a distributed cyber-physical control system governed by signal, power, network, control, diagnostic, security, and software lifecycle paths. Use this report for ECUs, CAN, diagnostics, ADAS, OTA updates, software-defined vehicles, and electrical faults.

• I. Automotive Manufacturing, Supply Chain, and Quality Systems — Factories, Suppliers, Materials, Tolerances, Cost Structures, and Production Reality
  Explains how factory processes, supplier tiers, material choices, tolerances, tooling, cost structures, and quality systems shape the final vehicle. Use this report for production reality, quality variation, supply constraints, and manufacturing trade-offs.

• J. Automotive Market, Ownership, and Lifecycle Economics — Buying, Selling, Depreciation, Financing, Insurance, Maintenance Cost, and Residual Value
  Maps automotive value across purchase, finance, depreciation, insurance, repair cost, maintenance burden, and residual value. Use this report for ownership decisions, total cost of ownership, fleet economics, and used-car risk framing.

K-M — Pressure Domains: Law, Energy, Environment, Performance, and Modification

• K. Automotive Safety, Regulation, and Compliance Systems — Crashworthiness, Emissions, Homologation, Liability, Recalls, and Public Risk
  Covers the legal and public-risk systems that reshape design, testing, recalls, liability, emissions compliance, and homologation. Use this report when safety, legality, compliance, or public-risk claims matter.

• L. Automotive Energy Transition and Environmental Systems — EV Adoption, Hybridization, Fuels, Charging, Batteries, Emissions, and Infrastructure Burdens
  Maps the transition from fuel-centered vehicles to electrified, hybridized, infrastructure-dependent energy systems. Use this report for EV adoption, charging, battery burdens, emissions trade-offs, fuel pathways, and infrastructure constraints.

• M. Automotive Performance, Motorsport, and Modification Systems — Speed, Durability, Rulesets, Tuning, Aftermarket Engineering, and Competitive Trade-Offs
  Explains performance as a system balance problem, not a horsepower contest. Use this report for tuning, motorsport, aftermarket builds, durability, brakes, cooling, ruleset constraints, and modification risk.

N-O — Failure and Execution: How Knowledge Becomes Judgment

• N. Automotive Failure Modes and Diagnostic Logic — Breakdowns, Wear, Noise, Leaks, Codes, Misfires, Vibrations, Intermittents, and Root Cause Discipline
  Establishes automotive field medicine: complaint, symptom, sign, failure mode, failed component, causal mechanism, root cause, repair action, and verification. Use this report whenever a diagnostic answer needs to avoid parts-changing theater.

• O. Automotive Execution Artifacts and Practitioner Workflows — Inspection Systems, Service Plans, Buying Checklists, Restoration Maps, Build Sheets, and Decision Tools
  Converts theory into checklists, worksheets, matrices, protocols, logs, decision trees, risk registers, service plans, build sheets, and handoff notes. Use this report when the output should become a practical field artifact.

Compiled Packs

Use compiled packs when an AI tool performs better with fewer, larger files.

• [KNOWLEDGE] - Automotive Systems - Vol. 1 A-D Automotive Systems Foundations - How the Field Becomes Legible.md
• [KNOWLEDGE] - Automotive Systems - Vol. 2 E-J Automotive Systems Operating Domains - Where the Real Work Happens.md
• [KNOWLEDGE] - Automotive Systems - Vol. 4 N-O Automotive Systems Failure, Diagnosis, and Execution - How Knowledge Becomes Judgment.md

Reports K-M are present as individual source reports and included in the omnibus. They are not currently packaged as a separate compiled Vol. 3 bundle in this release.

Omnibus

• [KNOWLEDGE] - Automotive Systems - Omnibus.md

Use the omnibus for one-file import, local archive, broad search, or systems that can handle large single-file knowledge sources without losing retrieval precision.