An enhanced stochastic operating cycle description including weather and traffic models
Artikel i vetenskaplig tidskrift, 2021

The present paper extends the concept of a stochastic operating cycle (sOC) by introducing additional models for weather and traffic. In regard to the weather parameters, dynamic models for air temperature, atmospheric pressure, relative humidity, precipitation, wind speed and direction are included. The traffic models is instead based on a macroscopic approach which describes the density dynamically by means of a simple autoregressive process. The enhanced format is structured in a hierarchical fashion, allowing for ease of implementation and modularity. The novel models are parametrised starting from data available from external databases. The possibility of generating synthetic data using the statistical descriptors introduced in the paper is also discussed.

To investigate the impact of the novel parameters over energy efficiency, a sensitivity analysis is conducted with a combinatorial test design. Simulation results show that both seasonality and traffic conditions are responsible for introducing major variations in the CO2 emissions.

Stochastic modelling

Autoregressive models

Weather description

Traffic description

CO2 emissions

Operating cycle

Transport mission


Luigi Romano

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Pär Johannesson

RISE Research Institutes of Sweden

Fredrik Bruzelius

Statens Väg- och Transportforskningsinstitut (VTI)

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Bengt J H Jacobson

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Transportation Research Part D: Transport and Environment

1361-9209 (ISSN)

Vol. 97 102878

COVER – Bedömning av CO2 och energieffektivitet hos fordon i verklig användning

Energimyndigheten (2017-007895), 2018-01-01 -- 2021-12-31.

VINNOVA (2017-007895), 2018-01-01 -- 2021-12-31.


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