Development of simplified air drag models including crosswinds for commercial heavy vehicle combinations
Artikel i vetenskaplig tidskrift, 2024

Accurate range prediction requires good knowledge of the prevailing wind conditions and how they affect the energy consumption of the ego vehicle. A few different simplified vehicle air drag models that explicitly include the effect from crosswinds are presented and compared through some objective criteria. The models are developed from the normal air drag equation where the effect from wind is implicit and therefore often forgotten or neglected. The purpose is to find a low-complexity model complementing CFD models and wind tunnel tests, that can be used for range estimation and predictive energy management algorithms. To simplify online estimation, a requirement is that the air drag models only contain a few tuning parameters. The models are validated against CFD calculations for a few vehicle combinations and the best models show good accuracy for air attack angles up to at least 60 degrees. It is shown that the parameters of the simplified models can loosely be connected to some basic geometrical attributes of a vehicle combination so it should be possible to give at least a rough estimate of the parameters of a simplified model based on these geometrical attributes. This is useful for making a first estimate of the aerodynamic properties of a vehicle combination after major changes in the exterior, e.g. when adding a trailer. It also highlights that the size and the shape of the vehicle side may be mainly responsible for the high longitudinal air drag sensitivity to crosswinds for large vehicle combinations.

estimation

Side-wind

yaw

model

drag

crosswind

simplified

Författare

Mikael Askerdal

Volvo Group

Chalmers, Elektroteknik, System- och reglerteknik

Jonas Fredriksson

Chalmers, Elektroteknik, System- och reglerteknik

Leo Laine

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Volvo Group

Vehicle System Dynamics

0042-3114 (ISSN) 1744-5159 (eISSN)

Vol. 62 5 1085-1102

Nytta och förtroende för elektriska fordon (U-FEEL)

Volvo Group, 2022-10-01 -- 2025-09-30.

Energimyndigheten (P2022-00948), 2022-10-01 -- 2025-09-30.

Volvo Group, 2022-10-01 -- 2025-09-30.

Scania CV AB, 2022-10-01 -- 2025-09-30.

Volvo Cars, 2022-10-01 -- 2025-09-30.

Ämneskategorier

Farkostteknik

DOI

10.1080/00423114.2023.2213786

Mer information

Senast uppdaterat

2024-09-17