On-road aerodynamic state estimation using sparse pressure sensors with application to truck platooning

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Authors

Chan, Ryan

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thesis

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eng

Keyword

aerodynamic , pressure , sparse , state estimation , platoon , energy

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Abstract

Experimental research on truck platooning is typically conducted using one of three methods: 1. wind-tunnel testing (often supported by computational fluid dynamics); 2. controlled track testing; and 3. on-road testing. While wind-tunnel and track- testing benefit from the ease of repeatability and control, they suffer from a dearth of real-world effects via complex boundary conditions, unpredictable driving behavior, and varying local environmental influences. On-road testing is more realistic but often avoided because of the perceived complexity of the experimental setup. The first goal of this thesis is to minimize the complexity of on-road experimental setups while maintaining the feasibility of pressure sensors to predict aerodynamic states during platooning. Pressure sensors are placed on five locations on a test vehicle: the front license plate; the center of the rear surface; above the front windshield; and the right and left corners of the front bumper. The second goal is to establish relationships between all five pressure sensors including the pressure differences and the frequency spectra of the right and left sensors to estimate platooning distance, wind conditions, and effects due to roadside vegetation density. Surprisingly, it is found that the estimations from these sensors improve as the complexity of the environment increases. In the most complex scenarios with high-tree densities and traffic, the effects of wind are minimized and spectral energy is maximized. The front-back and right-left pressure differences, along with the energy computed from the power spectral density of the latter, develop a data-driven surface that identifies the efficiency of platooning under different weather conditions.

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