Developing the AC17 Efficiency Test for Mobile Air Conditioners

Paper #:
  • 2013-01-0569

  • 2013-04-08
  • 10.4271/2013-01-0569
Sciance, F., Nelson, B., Yassine, M., Patti, A. et al., "Developing the AC17 Efficiency Test for Mobile Air Conditioners," SAE Technical Paper 2013-01-0569, 2013, doi:10.4271/2013-01-0569.
Chrysler, Ford, General Motors, the U.S. Environmental Protection Agency (EPA) and the California Air Resources Board (CARB) have collaborated over the past two years to develop an efficiency test for mobile air conditioner (MAC) systems. Because the effect of efficiency differences between different MAC systems and different technologies is relatively small compared to overall vehicle fuel consumption, quantifying these differences has been challenging. The objective of this program was to develop a single dynamic test procedure that is capable of discerning small efficiency differences, and is generally representative of mobile air conditioner usage in the United States. The test was designed to be conducted in existing test facilities, using existing equipment, and within a sufficiently short time to fit standard test facility scheduling.Representative ambient climate conditions for the U.S. were chosen, as well as other test parameters, and a solar load was included. The procedure was then performed by the OEMs on a wide range of vehicles to assess repeatability, accuracy, and other parameters. While these evaluations continue, and the results have been at times mixed, the test is robust and the overall experience with the test has been positive.Repeatability and accuracy have been good, but MAC CO₂ emissions are small compared to test-to-test variations in CO₂ emissions associated with other vehicle functions, especially on hybrid vehicles. Thus, even with normal test repeatability levels, the benefits of individual MAC technologies cannot always be discerned. Work continues to understand the performance of the test, including potential improvements and supplements. The new test is a useful addition to the tools we can use to assess MAC efficiency in order to make MAC improvements in the future.
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