Aerodynamic Methods of Maintaining Advanced Driver-Assistance System Sensor Operability in Adverse Conditions

表面污染或脏污的影响一直是汽车行业的一个长期问题，研究可以追溯到20世纪60年代。到目前为止，污染物积聚的影响在很大程度上是表面现象。然而，随着自动驾驶和其他先进驾驶辅助系统（ADAS）的出现，表面污染可能会产生更严重的影响。ADAS依靠传感器来监测其运行的外部环境，而表面污染风险阻碍了这一能力，限制了功能并增加了道路交通事故的可能性。拉夫堡大学先前的研究表明，使用高保真（拉格朗日粒子跟踪的分离涡模拟）数值方法进行的实验研究和计算模拟之间可以找到非常好的一致性。这些研究主要集中在SUV型几何形状的后部的污染上。该项目将考虑车辆周围ADAS传感器位置上的喷雾和悬浮在ADAS传感器前面的喷雾。这将包括考虑其他车辆的污染、高湍流尾流。该项目的第一个目标将是使用实验和计算研究，以找到在基线配置的传感器条件下预期的污染水平。使用这些数据，目的是量化污染物积累的影响，并确定可能的缓解空气动力学设计。工作的主体将是研究使用空气动力学控制方法，以减少道路喷雾对ADAS系统的影响。数据分析方法，如适当的正交分解（POD）技术，将被用来确定主要的流动结构负责污染和突出机制，以减少颗粒夹带到车辆尾流。第一个将是研究减少从车轮夹带到车辆尾流中的喷雾量的方法，第二个将考虑主动装置，例如空气屏障，其产生局部高能空气流，以帮助保护传感器免受撞击污染物的影响。方法将在模拟中发展，然后在实验中进行测试。除了考虑减少污染方面的有效性外，还将确定能源使用或等效车辆阻力增加方面的“成本”。

The impacts of surface contamination, or soiling, have been a long-standing issue in the automotive industry, with research going back as far as the 1960s. Until now, the impact of contaminant build-up has been largely cosmetic. However, with the advent of autonomy and other advanced driver-assistance systems (ADAS), surface contamination may have more serious repercussions. ADAS rely on sensors to monitor the external environment in which they operate and surface contamination risks obstructing this ability, limiting functionality and increasing the likelihood of road traffic accidents.Previous studies at Loughborough University have shown that very good levels of agreement can be found between experimental studies and computational simulations using a high-fidelity (Detached Eddy Simulation with Lagrangian particle tracking) numerical method. These studies have largely concentrated on the soiling of the rear of SUV type geometries. This project will consider the spray on, and suspended in front of, ADAS sensor locations around the vehicle. This will include consideration of the contaminated, high turbulent, wake of other vehicles. The first aim of the project will be to use experimental and computational studies to find the level of contamination that can be expected at sensor conditions for a baseline configuration. Using this data, the intent is to quantify the effects of contaminant build-up and identify possible mitigatory aerodynamic designs.The main body of the work will be to investigate the use of aerodynamic control methods to reduce the impact of road spray on ADAS systems. Data analysis methods such as proper orthogonal decomposition (POD) techniques will be used to identify the main flow structures responsible for contamination and highlight mechanisms to reduce particle entrainment into vehicle wakes.These will fall into two categories; the first will be to investigate methods of reducing the amount of spray that is entrained into the vehicle wake from the wheels, the second will consider active devices, such as air barriers, that generate streams of local, high-energy air, to help shield sensors from impinging contaminants. Methods will be developed in simulation before tested in experiment. As well as considering the effectiveness in terms of contamination reduction, the 'cost' in terms of energy use or equivalently vehicle drag increase will be determined.