ISO 23795-1:2022

Overview

ISO 23795-1:2022 - "Intelligent transport systems - Extracting trip data using nomadic and mobile devices for estimating CO2 emissions - Part 1: Fuel consumption determination for fleet management" specifies a method to determine fuel consumption and resulting CO2 emissions by extracting per‑second speed profiles from a GNSS receiver inside a nomadic device (ND). Speed data are sent via mobile communication to a server where the mechanical energy contributions of aerodynamics, rolling friction, acceleration/braking, slope resistance and standstill are compared, in percent, to a defined reference driving cycle. The approach enables fleet managers and logistics providers to estimate fuel use and emissions without vehicle‑mounted sensors.

Key topics and technical requirements

• Data source: GNSS speed profiles collected by a nomadic device; per‑second sampling is assumed.
• Client‑server architecture: ND transmits dynamic trip data to a database/server for analysis and comparison with reference cycles.
• Energy decomposition: Fuel/energy estimation based on Newtonian physics breaking down mechanical energy into:
  • Aerodynamics
  • Rolling friction
  • Acceleration/braking (inertial forces)
  • Slope resistance
  • Standstill (idling)
• Reference comparison: Deviations from a virtual vehicle driving a known reference cycle (e.g., WLTP or other established cycles) are expressed as percentage deviations and converted to fuel units (vLPH, litres per 100 km equivalent).
• Model inputs: Static vehicle configuration parameters (mass, drag coefficient, cross‑sectional area, tyre friction, etc.) are required on the server side - the ND itself is not vehicle‑aware.
• Mathematical basis: Energy and fuel equations (fuel per distance, conversion to litres/100 km) using engine efficiency, fuel energy value and physical constants.
• Out‑of‑scope items: The method does not cover how dynamic ND data are linked to static vehicle parameters (implementation‑dependent) and does not address legal/privacy requirements for collected data.

Applications

• Fleet management: Trip‑level fuel and CO2 monitoring, benchmarking and cost reduction.
• Eco‑driving coaching: Real‑time or post‑trip feedback to drivers to improve driving behaviour.
• Logistics optimization: Route planning and driver performance KPIs based on fuel use estimates.
• Traffic and policy evaluation: Floating car measurements to assess the impact of traffic management for GHG reduction.
• Public‑private R&D deployment: Integrates with mobility projects and telematics platforms for large‑scale monitoring.

Who should use this standard

• Fleet operators and logistics service providers
• Telematics and mobility‑software developers
• Public transport authorities and urban planners
• Eco‑drive trainers and sustainability managers

Practical notes & limitations

• Implementation must supply accurate static vehicle parameters on the server for valid estimates.
• Developers must handle privacy, consent and local data‑protection compliance (not covered by ISO 23795-1:2022).
• Best for applications where non‑intrusive, GNSS‑based monitoring is preferred over vehicle‑integrated sensors.

Related standards

• WLTP (Worldwide harmonized Light vehicles Test Procedure) - reference driving cycles
• ISO 13111‑1 and ISO 13185‑3 (related ITS terminology and privacy concepts)
• ISO/TC 204 publications on intelligent transport systems

Keywords: ISO 23795-1:2022, intelligent transport systems, GNSS, nomadic device, fuel consumption determination, CO2 emissions, fleet management, speed profiles, eco‑driving.