The operating cycle representation of road transport missions
Doctoral thesis, 2023
Where many conventional approaches fail, the operating cycle format (OC) has revealed great potential in describing road operations in a way that is, to a large extent, independent of both vehicle and driver. More specifically, the framework consists of three levels of representation. The first, called the bird's-eye view, serves mainly as a classification tool and makes use of metrics and labels to completely characterise the overall application of a vehicle during its lifetime. The second description, the stochastic operating cycle (sOC), condenses the main properties of a road operation using elementary statistics. It is conceived as an intermediate representation with a higher resolution. Finally, the deterministic operating cycle (dOC) is the most detailed description of a transport mission and collects deterministic models to be used in simulations.
In previous studies, the OC format was demonstrated to work in theory, but some margins for improvement could still be identified. Furthermore, the benefits deriving from the use of the OC were explored only partially.
The first objective of this thesis consists in extending the OC representation to include stochastic models for weather, traffic, and mission properties, which were missing in the original formulation. The new models are built to be parsimonious and to facilitate parametrisation and implementation starting from real data. This enables reproducing and simulating realistic environments where a transport mission may take place, with a substantial gain in accuracy.
The second purpose of this work is to showcase how the OC concept can be used in practical applications concerning the design and sale phases. To this end, the relationships existing between the three levels of representation included in the format are formalised mathematically by exploiting the stochastic nature of the sOC, which acts as a bridge between the bird’s-eye view and the dOC. It is argued that the three descriptions can work synergically to support manufacturers in their internal processes of classification, optimal development and selection, and virtual testing of energy-efficient vehicles.
operating cycle
transport application
road mission
probability distributions
stochastic processes
energy estimation
Author
Luigi Romano
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Engineering and Autonomous Systems
An enhanced stochastic operating cycle description including weather and traffic models
Transportation Research Part D: Transport and Environment,;Vol. 97(2021)
Journal article
A classification method of road transport missions and applications using the operating cycle format
IEEE Access,;Vol. 10(2022)p. 73087-73121
Journal article
Development of the Västra Götaland operating cycle for long-haul heavy-duty vehicles
IEEE Access,;Vol. 11(2023)p. 73268-73302
Journal article
A method to build energy-metric-optimal (EMO) classification systems for road transport missions
2023 IEEE Vehicle Power and Propulsion Conference,;(2023)
Paper in proceeding
Stochastic modeling of mission stops and variable cargo weight for heavy-duty trucks
2023 IEEE Vehicle Power and Propulsion Conference,;(2023)
Paper in proceeding
COVER – Real world CO2 assessment and Vehicle enERgy efficiency
Swedish Energy Agency (2017-007895), 2018-01-01 -- 2021-12-31.
VINNOVA (2017-007895), 2018-01-01 -- 2021-12-31.
Driving Forces
Sustainable development
Areas of Advance
Transport
Energy
Subject Categories
Transport Systems and Logistics
Vehicle Engineering
ISBN
978-91-7905-888-3
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5354
Publisher
Chalmers
Chalmers campus Johanneberg, lecture hall Vasa C, Vasa Hus 2-3, Vera Sandbergs Allé 8.
Opponent: Kari Tammi, Associate Professor at Aalto University, Finland