Aerodynamic Analysis of Autonomous Battery Electric Truck Concepts for Drag Reduction

Abstract

This research presents an aerodynamic drag analysis of an autonomous battery electric truck (BET) by means of using computational fluid dynamics (CFD) as a simulation tool. The CFD simulation utilises the Reynolds-averaged Navier–Stokes (RANS) equations with a realizable k-𝜀 turbulence model and non-equilibrium wall functions to model the near-wall region of the domain. The simulation accuracy is validated against empirical results for the aerodynamic drag on the generic conventional model (GCM) truck, as tested in a wind tunnel. It was found that the overall aerodynamic drag of the vehicle could be reduced by approximately 35.5% without reducing the truck’s trailer loading volume. This work demonstrates that autonomous BETs can significantly reduce the overall aerodynamic drag of a truck, thereby reducing energy consumption and greenhouse gas (GHG) emissions for the land freight sector.

Keywords

• autonomous truck
• cfd analysis
• driverless truck
• long haul bet
• zero-emission truck