{"id":4931,"date":"2021-11-26T10:49:57","date_gmt":"2021-11-25T23:49:57","guid":{"rendered":"https:\/\/www.computationalfluiddynamics.com.au\/?p=3743"},"modified":"2025-04-15T15:46:18","modified_gmt":"2025-04-15T04:46:18","slug":"ecu-r_analysing-fsae-flow-fields-using-cfd","status":"publish","type":"post","link":"https:\/\/www.leapaust.com.au\/blog\/cfd\/ecu-r_analysing-fsae-flow-fields-using-cfd\/","title":{"rendered":"Guest Blog by ECU-R: Analysing F-SAE Aerodynamic Flow Fields Using CFD"},"content":{"rendered":"
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ECU-R<\/strong> (Edith Cowan University Racing)<\/a><\/span> has been designing and manufacturing its first ever EV (Electric Vehicle) for Formula Student – a global engineering competition focused on the development of high-performance open wheel race cars. Competition is fierce and producing a competitive car requires teamwork, high-quality design, extensive manufacturing, and project management. This blog will focus on how ECU-R uses simulation to \u2018drive\u2019 design within the aerodynamics department.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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ECU-R 2021 Electric Vehicle (Rendered in Keyshot<\/span><\/a>)<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Before talking specifically about aerodynamics, a note should be made about how the team approaches design using simulation. If ECU-R had infinite monetary and human resources, then thousands of components could be designed and physically tested until the best solution was found. However, since this is not the case, time and cost-effective design methods must be utilised. Without LEAP\u2019s support not only would the team lack the experience of industry level software<\/strong>, but countless components would not be optimised – a large detriment to performance.<\/p>

Ansys CFD is used consistently by the aerodynamics department to evaluate concepts, perform optimisations, and create aero maps. The majority of the team\u2019s CFD isn\u2019t automated optimisation and thus it is the initial validation<\/strong> to the designer\u2019s concept. This approach places a larger emphasis on conceptual thinking and flow field interpretation which is advantageous when dealing with limited computational power.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Figure 2: Wheel Hub FEA (Simulated in Ansys Mechanical)<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Insights from post-processing of simulations provide the designer with the ability to identify problematic aspects of the flow such as separations, undesirable structures, and poor use of flow energy. New ideas can then be brainstormed and used in subsequent designs to better address these issues, thereby improving the overall flow around the car.<\/p>

Post-processing visualisation has the large benefit of design justification without the need to manufacture parts. Therefore these \u2018new ideas\u2019 more rapidly develop allowing for more optimised geometry and greater performance.<\/p>

The main goals<\/strong> for the EV\u2019s new aerodynamics package were:<\/p>