Evaluating the Impact of Drag Coefficient Changes on Driving Energy Using a Probability Distribution Model of Yaw Angle Based on Empirical Data from North American Highways

This study estimates the impact on driving energy of differences in aerodynamic characteristics for yaw angle from natural wind during North American Highway mode driving. A previous study[1] clarified the potential to estimate the fuel consumption impact of natural wind by integrating the CD yaw characteristics and yaw angle occurrence frequency. The natural wind was measured on a vehicle while driving a representative North American Highway test course[2]. The driving energy is predicted from the obtained yaw frequency and CD yaw sweep data in a wind tunnel. Measurements were conducted every weekday for 8 hours in 2023, covering 70% of the traffic volume. The validity of the measurement period was evaluated by the deviation from the annual average of wind direction and speed. Since yaw frequency varies depending on the road environment, it is necessary to weight the road environment type frequency when calculating the driving energy. The frequency was calculated using machine learning from more than 490,000 images of North American Highways. Based on the obtained natural wind data, a yaw frequency model was created for each vehicle speed in the US Highway driving mode. An evaluation method for the driving energy was constructed from data before and after the improvement of the CD yaw characteristics. This evaluation method is based on verification results from actual driving data. By using the yaw probability distribution that considers the road environment and traffic volume of the North American highway, the impact of the yaw angle due to natural wind on driving energy can be numerically estimated. According to this method, for a specific CD yaw sweep characteristic with a 10ct improvement in CD at a 6 degree yaw angle, this would result in an improvement in drive energy of approximately 1.1% on real US highways. This is an important index in optimizing aerodynamic characteristics and proposes a new direction for shape optimization.