Browse Publications Technical Papers 2012-01-2052

Application of Sleeper Cab Thermal Management Technologies to Reduce Idle Climate Control Loads in Long-Haul Trucks 2012-01-2052

In the United States, an intercity long-haul truck averages approximately 1,800 hrs per year for idling, primarily for sleeper cab hotel loads, consuming 838 million gallons of diesel fuel across the entire long-haul fleet [1]. Including workday idling, over 2 billion gallons of fuel are used annually for truck idling [2]. The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) is working on solutions to reduce idling fuel use through the CoolCab project. The objective of the CoolCab project is to work closely with industry to design efficient thermal management systems for long-haul trucks that minimize engine idling and fuel use while maintaining the cab occupant comfort.
NREL conducted an experimental test program at their Vehicle Testing and Integration Facility in collaboration with Volvo Trucks, Aearo Technologies LLC / E-A-R Thermal Acoustic Systems - a 3M company, 3M Corporation, and Dometic Environmental Corporation. The impact of thermal load reduction technologies on idle reduction systems was characterized by conducting thermal soak tests, overall heat transfer tests, and 10-hour rest period A/C tests. Technologies evaluated included advanced insulation packages, a solar reflective film applied to the vehicle's opaque exterior surfaces, a truck featuring both film and insulation, and a battery-powered A/C system. The results demonstrated technologies that reduce heating and cooling loads for long-haul truck idling by 36% and 34%, respectively, which yielded a 23% reduction in battery pack capacity of the idle reduction system.
Data was also collected for the development and validation of a CoolCalc heating, ventilating and air conditioning (HVAC) truck cab model. CoolCalc is an easy-to-use, simplified, physics-based HVAC load estimation tool developed by NREL that requires no meshing, has flexible geometry, excludes unnecessary detail, and is less time-intensive than more detailed computer-aided engineering modeling approaches [3]. This paper documents the approach, results, and conclusions from the collaborative research project.


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