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Side mirrors are a known source of aerodynamically generated noise in vehicles. In this work we focus on mirrors for heavy duty trucks, they are large, often not designed with main focus on aero-acoustics and are located in a cumbersome position on the up-right A-pillar of European trucks. First the test method itself is discussed. To allow fast and cost effective design loops a bespoke vehicle, where the powertrain is separated from the cab, is developed. This vehicle can be run on a standard test track. While running the tests the wind speed is monitored, any variations are then compensated for in the post processing allowing averaging over longer time periods. For the mirror tests the door of the vehicle was especially trimmed to reduce other transmission paths into the cab than the side window. Additionally other possible aeroacoustic sources were reduced as much as practically possible.

The purpose of this study is to determine the effect of tire operating conditions, such as the tire inflation pressure, speed, and load on the change of the first mode of vibration. A wide base FEA tire (445/50R22.5) is virtually tested on a 2.5m diameter circular drum with a 10mm cleat using PAM-Crash code. The varying parameters are altered separately and are as follows: inflation pressure, varying from 50 psi to 165 psi, rotational speed, changing from 20 km/h to 100 km/h, and the applied load will fluctuate from 1,500 lbs. to 9000 lbs. Through a comparison of previous literature, the PAM-Crash FFT algorithmic results have been validated.

The rigid-ring tire model is a simplified tire model that describes a tire's behaviour under known conditions through various in-plane and out-of-plane parameters. The complex structure of the tire model is simplified into a spring-mass-damper system and can have its behaviour parameterized using principles of mechanical vibrations. By designing non-linear simulations of the tire model in specific situations, these parameters can be determined. They include, but are not limited to, the cornering stiffness, vertical damping constants, self-aligning torque stiffness and relaxation length. In addition, off-road parameters can be determined using similar methods to parameterize the tire model's behaviour in soft soils. By using Finite Element Analysis (FEA) modeling methods, validated soil models are introduced to the simulations to find additional soft soil parameters.

Annual fuel use for long-haul truck rest period idling is estimated at 667 million gallons in the United States. The U.S. Department of Energy's National Renewable Energy Laboratory's CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck climate control systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In order for candidate idle reduction technologies to be implemented at the original equipment manufacturer and fleet level, their effectiveness must be quantified. To address this need, a number of promising candidate technologies were evaluated through experimentation and modeling to determine their effectiveness in reducing rest period HVAC loads.