Climatic Aerodynamics

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Vehicles with advanced driver assist systems and autonomous vehicles (AVs) heavily rely on the input of various sensors (Optical, Radar, Lidar, etc.) to capture environmental and traffic data. However, different sensor types require different boundary conditions regarding applicability and performance (e.g., cameras and lidar need unobstructed optical view while radar might be covered with certain materials). Field-of-view, packaging, design requirements, etc., may require sensors to be applied in areas prone to soiling and contamination (e.g., rain, snow, spray, dust, etc.) This requires a comprehensive and detailed examination of the soiling of vehicles, the mechanisms of soiling, and the effect of precipitation on sensor visibility, as well as extensive data, but they are lacking. This makes sensing and perception in adverse weather conditions one of the most difficult problems to solve in the development of autonomous vehicle systems. My research group is investigating questions such as: How much does the placement of sensors help prevent soiling due to aerodynamic effects? What is the best way to keep sensors clean in adverse weather such as rain, snow, dust, etc.? Would sensor housing materials and coatings with different surface properties and geometries coupled with aerodynamics enhance soiling mitigation?

Research Highlights

Methodology development for road vehicle and autonomous sensor soiling studies

Modern vehicles and emerging autonomous vehicles are equipped with a variety of sensors to perceive the surrounding environment, such as optical cameras, LiDAR, RADAR, and ultrasonic sensors. These sensors need to be able to maintain performance during adverse weather conditions. Sensor performance in weather is not very well understood nor quantified, owing to the lack of evaluation tools and methods.

While outdoor testing is realistic, it is challenging to obtain repeatable results quickly. A novel rain simulation system was developed to be implemented in a wind tunnel to replicate realistic driving-in-rain conditions, shown in Figure. The project is conducted by PhD student Wing Yi Pao and undergraduate student Long Li, in collaboration with Magna International. The rain simulation system is patent pending and has won the CSME national student design competition under the prize category of “Technical Prowess in Mechanical Engineering” in 2022.

The team is currently constructing a drive-thru climate tunnel to bridge the gap between outdoor and indoor wind tunnel testing. The team is also working on quantification and soiling mitigation strategies to improve sensor performance in different driving-in-rain conditions. The evaluation metrics take into account a combination of realistic characteristics, including rainfall intensity, raindrop size distribution, raindrop impact, vehicle aerodynamics, and surface properties.

Development of flow control methods for drag and soiling mitigation over a generic vehicle

The carbon emissions from classic vehicles affect the environment, thus, electric vehicles are gaining more attention in recent years. However, a lot of the battery energy density of modern electric vehicles is used to overcome aerodynamic drag, which impacts the vehicle's range. On the other hand, vehicle aerodynamics is known to affect rear window soiling, soiling not only impairs the driver's vision but also degrades sensors and cameras' performance for autonomous vehicles, which are vital for safety. Despite the importance of the above issues, vehicle stability remains one of the most important aspects of any solution that does not impact the above negatively. The literature has so far addressed only one of these issues at a time, hampering the collective interaction and impact on vehicle performance.

At present, the team is developing methods to simultaneously solve all of the above problems arising from collaborative interaction. PhD student, Naseeb Ahmed Siddiqui is employing state-of-the-art experimental and numerical methods to generate new insights into the design, development, testing, validation, and analysis of vehicles.

Implementing one of the flow control methods, there is a positive effect on the above-mentioned issues, including drag and soiling mitigation. Such passive methods are energy efficient since they do not require any energy input and can be implemented with little modification. The method is being studied numerically and experimentally for a detailed analysis. Below is the three-dimensional flow structure using Q-Criterion. Some of the results are already published in top journals like Physics of Fluid, International Journal of Heat and Fluid Flow, and conferences like the American Society of mechanical engineers (ASME).