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Aerodynamic Drag Reduction of a Square-Back Car Model Using Linear Genetic Programming and Physic-Based Control

Abstract : The thesis aims to develop effective active flow control strategies for aerodynamic drag reduction of road vehicles.We experimentally examine the effects of fluidic actuation on the wake past a simplified square-back car model.The actuation is performed with pulsed jets at trailing edges and the flow is monitored with 16 pressure sensors distributed at the rear side. We address the challenging nonlinear turbulence control---which is often beyond the capabilities of model-oriented approach---by developing a simple yet powerful model-free control strategy: the data-driven linear genetic programming control (LGPC). This method explores and exploits strongly nonlinear dynamics in an unsupervised manner with no or little prior knowledge about the system. The control problem is to find a control logic which optimizes a given cost function by employing linear genetic programming as an easy and simple regression solver in a high-dimensional control search space. In particular, the present work advances and generalizes the previous studies of genetic programming control by comprising multi-frequency forcing, sensor-based feedback including also time-history information feedback and combinations thereof in the control search space. The performance of LGPC is successfully demonstrated on the drag control experiments of the car model where the investigated turbulent wake exhibits a spanwise symmetry and a wall-normal asymmetry. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. The consumed actuation energy accounts for only 30% of the aerodynamic power saving. In this research, we also study the turbulent wakes having a lateral asymmetry: an intermittent bi-modal wake at zero yaw and an asymmetric wake at a moderate yaw angle of 5 degree. For the bimodal wake exhibiting are flectional symmetry-breaking, a physics-based opposition feedback control is inferred from the previous open loop control tests. The controller successfully suppresses the bi-modality of the wake and renders a symmetrized wake with a concomitant drag reduction. For the asymmetric wake at yaw, we infer from the single-frequency forcing results a bi-frequency control at the windward edge comprising two frequencies having one order of magnitude difference. This bi-frequency actuation combines the favorable effects of fluidic boat-tailing and balance control of the shear layers. Importantly, LGPC is also applied to this yawed situation and converges to the same bi-frequency actuation. The control strategies proposed in the present study open promising new paths for the control of drag reduction in more complex conditions such as the varying oncoming velocity and wind gust.
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Submitted on : Tuesday, January 16, 2018 - 12:07:12 PM
Last modification on : Wednesday, November 3, 2021 - 5:57:23 AM
Long-term archiving on: : Sunday, May 6, 2018 - 11:31:08 AM


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  • HAL Id : tel-01685306, version 1



Ruiying Li. Aerodynamic Drag Reduction of a Square-Back Car Model Using Linear Genetic Programming and Physic-Based Control. Other. ISAE-ENSMA Ecole Nationale Supérieure de Mécanique et d'Aérotechique - Poitiers, 2017. English. ⟨NNT : 2017ESMA0014⟩. ⟨tel-01685306⟩



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