Journal Article


Aerodynamic optimisation of a front wheel wake related bodywork on a novel electric formula car using metaheuristic approach

Abstract

Aerodynamic drag reduction is a critical part in the design of a novel electric, entry level, formula car due to the modest energy density provided by the contemporary Lithium-ion battery cells. In order to improve track performance, aerodynamic development must focus on components which do not generate considerable amount of downforce. Rotating front wheels are identified as the least aerodynamic part of the race car, since it is responsible for the third of the overall drag forces and producing moderate amounts of lift. In the present study, a parameterised wheel pod geometry is used to improve the overall aerodynamic performance of an open wheel race car. The model is driven by seven parameters, which entails huge flexibility of the bodywork design. First, an unsteady Computational Fluid Dynamics (CFD) simulation was developed and validated to visualise the oscillating flow behaviour and obtain averaged surface force measurements. In expectation of a highly turbulent and complex wheel wake structure, the traditional iterative optimisation method had to be excluded. The exploration of the optimal bodywork was executed by a single objective aerodynamic optimisation framework, coupled with CFD simulations. The objective target was to minimise overall drag force while the simulation must agree on the pre-set restrictions and leave downforce unharmed. SHERPA search algorithm was applied along with Kriging response surface surrogate modelling. The convergence of the objective history indicated acceptable fidelity of the predictions for the location of the global minimum of the 8-dimension design space. The race car equipped with the best design wheel pod generated 11.1% less overall drag, while aerodynamic efficiency was improved by 17.1%.

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Authors

Diosy, Miklos
Bell, Daniel

Oxford Brookes departments

Faculty of Technology, Design and Environment\School of Engineering, Computing and Mathematics

Dates

Year of publication: 2018
Date of RADAR deposit: 2019-06-07


Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License


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