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Optimization of the Aerodynamic Lift and Drag of LYNK&CO 03+ with Simulation and Wind Tunnel Test
Technical Paper
2020-01-0672
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Based on the first sedan of the LYNK&CO brand from Geely, the high-performance configuration equipped with an additional aerodynamic package was developed. The aerodynamic package including front wheel deflectors, front lip, side skirts, rear spoiler, and rear diffuser, was required to be upgraded to generate enough aerodynamic downforce for better handling stability, without compromising the aerodynamic drag of the vehicle too much to keep a low fuel consumption.
Starting from the baseline configuration of the aerodynamics package provided by the design studio, the components were optimized for aerodynamic drag and lift using the simulation approach with PowerFLOW in combination with a design space exploration method. As a result, the targets for the aerodynamic coefficients of the vehicle and in particular a good trade-off between lift and drag were achieved. Wind tunnel testing was involved to calibrate the simulation results at the beginning and to validate the optimized design at the end of the aerodynamic development. A consistently good agreement between the simulation and experiment was achieved.
Authors
- Qian Feng - Geely Automobile Research Institute
- Biaoneng Luo - Geely Automobile Research Institute
- Huixiang Zhang - Geely Automobile Research Institute
- Hong Peng - Geely Automobile Research Institute
- Zhenying Zhu - Geely Automobile Research Institute
- Zhi Ding - Geely Automobile Research Institute
- Ling Zhu - Geely Automobile Research Institute
- Weiliang Xie - Dassault Systemes(Shanghai) Information Technology Co.
- Bo Li - Dassault Systemes(Shanghai) Information Technology Co.
- Xiaowei Zhao - Dassault Systemes(Shanghai) Information Technology Co.
Topic
Citation
Feng, Q., Luo, B., Zhang, H., Peng, H. et al., "Optimization of the Aerodynamic Lift and Drag of LYNK&CO 03+ with Simulation and Wind Tunnel Test," SAE Technical Paper 2020-01-0672, 2020, https://doi.org/10.4271/2020-01-0672.Data Sets - Support Documents
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