Reviewed by Lexie CornerJan 8 2025
In a study published in Physics of Fluids by AIP Publishing, researchers from Wuhan University of Technology in Wuhan, China, investigated methods to enhance the aerodynamic performance of autonomous vehicles (AVs). The study focused on reducing drag caused by externally mounted sensors, including cameras and light detection and ranging (LiDAR) instruments, which are essential for AV operation.
Deformation control volumes are set for the front sensor, front-side sensor, roof sensor, and rear-side sensor, which significantly impact the aerodynamic drag coefficient. The sensor shapes can be modified by adjusting the control points on these control volumes. Image Credit: Yiping Wang
AVs are increasingly utilized in logistics distribution and low-speed public transportation as advancements in information technology and artificial intelligence continue.
While research has primarily focused on improving safety through control algorithms, less attention has been given to aerodynamic performance, which is critical for reducing energy consumption and extending driving range. Challenges associated with aerodynamic drag have limited AVs from achieving acceleration performance comparable to conventional vehicles.
Externally mounted sensors significantly increase aerodynamic drag, particularly by increasing the proportion of interference drag within the total aerodynamic drag. Considering these factors — the interactions among sensors and the impact of geometric dimensions on interference drag — it is essential to perform a comprehensive optimization of the sensors during the design phase.
Yiping Wang, Study Author and Professor, Wuhan University of Technology
To address these challenges, the researchers used a combination of computational and experimental methods. They developed an automated computational platform that integrated experimental design with a surrogate model and an optimization algorithm to refine the structural shapes of AV sensors.
Simulations were conducted for both baseline and optimized models to evaluate drag reduction and aerodynamic performance improvements. Wind tunnel experiments were performed to validate the simulation results.
The study found a 3.44 % reduction in overall aerodynamic drag following design optimization. The optimized model exhibited improved aerodynamic performance during unsteady simulations and achieved a 5.99 % reduction in the aerodynamic drag coefficient compared to the baseline model.
Additionally, the optimized design enhanced airflow, resulting in better pressure distribution at the rear of the vehicle and reduced turbulence around the sensors.
Wang concluded, “Looking ahead, our findings could inform the design of more aerodynamically efficient autonomous vehicles, enabling them to travel longer distances. This is especially important as the adoption of autonomous vehicles increases, not only in passenger transport but also in delivery and logistics applications.”
Journal Reference:
Zhao, J., et. al. (2024) Numerical and experimental investigations of the aerodynamic drag characteristics and reduction of an autonomous vehicle. Physics of Fluids. doi.org/10.1063/5.0242941