The 2012-2025 National fuel economy and greenhouse standards define the regulations for Corporate Average Fuel Economy (CAFE) which must be met by automobile manufacturers. Automobile manufacturer fleet CAFE is determined via a combination of on- and off-cycle methods. On-cycle certification is determined from weighted test results over EPA’s test cycles. Starting in 2017, manufacturers may supplement on cycle results with off-cycle credits. Off cycle credits may be applied for fuel saving items and technologies whose real-world benefit is not captured by on-cycle testing. There are multiple means to obtain off cycle credits; selection from a pre-defined menu, testing by 5 cycle procedures, or testing via an alternate method. For many technologies, the alternate method testing may provide the best estimate of the true fuel savings. For such technologies, it is critical to develop robust means to justify the true real world fuel economy benefits of these off-cycle credits in order to justify the carbon credit accurately. This work presents a methodology to determine the off-cycle fuel economy benefit of a 2-Layer HVAC system which reduces ventilation loss as well as reduces heat rejection of the heater core versus a vehicle using a standard system. Experimental dynamometer tests using EPA drive cycles over a broad range of ambient temperatures were conducted at Argonne National Laboratory (ANL) on a highly instrumented 2016 Lexus RX350 (3.5L, 8 speed automatic). These tests were conducted to measure differences in engine efficiency caused by changes in engine warmup due to the 2-Layer HVAC technology versus the technology being disabled (standard technology baseline). These experimental datasets were used to develop simplified response surface and lumped capacitance vehicle thermal models predictive of vehicle efficiency as a function of thermal state. These vehicle models were then integrated into the National Renewable Energy Laboratory’s (NREL) Transportation Secure Data Center (TSDC) and coupled with U.S. typical meteorological data to simulate vehicle efficiency across seasonal thermal and operational conditions for tens of thousands of drive cycles. Fuel economy benefits utilizing the 2-Layer HVAC technology are presented in addition to goodness of fit statistics of the modeling approach relative to the experimental test data.