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Design and Aerodynamic Optimization of a Rear Wing with a Drag Reduction System for a Formula Hybrid Racecar

dc.contributor.advisorMartinelli, Luigi
dc.contributor.authorStein, Noah S.
dc.date.accessioned2025-08-13T19:17:17Z
dc.date.available2025-08-13T19:17:17Z
dc.date.issued2025-04-22
dc.description.abstractThis thesis focuses on the design of a two-element rear wing with a driver-actuated drag reduction system (DRS) for an electric Formula Student racecar. A physical design space is first defined around Princeton Racing Electric’s MK3 car and brief vehicle dynamics calculations are done to establish a minimum downforce requirement for tested conditions in the Formula Hybrid Electric competition. High-lift, low Reynold’s number airfoils are modified to be compliant with the Formula Hybrid competition rules and analyzed initially in Xfoil. This is followed by two- and three-dimensional CFD analyses using Fidelity Pointwise for meshing and ANSYS Fluent for flow simulation and analysis. These simulations inform the optimal geometric configuration of the two wing elements and endplates to maximize the downforce/drag ratio under the analyzed conditions. The DRS design is informed by further CFD analysis and is implemented as an electromechanical system capable of being switched between high downforce and low drag configurations where needed to achieve the fastest lap times. The final rear wing design is capable of producing 128.5 N of downforce, 96% above the calculated requirement, while reducing drag by 83% when the DRS is activated. The thesis presents a finalized wing geometry with measurements, highlights and discusses general aerodynamic trends, and presents opportunities for further study and improvement on the design.
dc.identifier.urihttps://theses-dissertations.princeton.edu/handle/88435/dsp01bn999b21q
dc.language.isoen_US
dc.titleDesign and Aerodynamic Optimization of a Rear Wing with a Drag Reduction System for a Formula Hybrid Racecar
dc.typePrinceton University Senior Theses
dspace.entity.typePublication
dspace.workflow.startDateTime2025-04-22T21:25:30.636Z
pu.contributor.authorid920285807
pu.date.classyear2025
pu.departmentMechanical & Aerospace Engr

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