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Air conditioner power consumption accounts for a large fraction of the total power used by hybrid and electric vehicles. This study examined the effects of three different cabin air ventilation settings on mobile air conditioner (MAC) power consumption, such as fresh mode with air conditioner on (ACF), fresh mode with air conditioner off (ACO), and air recirculation mode with air conditioner on (ACR). Tests were carried out for both indoor chassis dynamometer and on-road tests using a 2012 Toyota Prius plug-in hybrid electric vehicle. Real-time power consumption and fuel economy were calculated from On-Board Diagnostic-II (OBD-II) data and compared with results from the carbon balance method. MAC consumed 28.4% of the total vehicle power in ACR mode when tested with the Supplemental Federal Test Procedure (SFTP) SC03 driving cycle on the dynamometer, which was 6.1% less than in ACF mode. On the other hand, ACR and ACF mode did not show significant differences for the less aggressive on-road tests. This is likely due to the significantly lower driving loads experienced in the local driving route compared to the SC03 driving cycle. On-road and SC03 test results suggested that more aggressive driving tends to magnify the effects of the vehicle HVAC (heating, ventilation, and air conditioning) system settings. ACR conditions improved relative fuel economy (or vehicle energy efficiency) to that of ACO conditions by ~20% and ~8% compared to ACF conditions for SC03 and on-road tests, respectively. Furthermore, vehicle cabin air quality was measured and analyzed for the on-road tests. ACR conditions significantly reduced in-cabin particle concentrations, in terms of aerosol diffusion charger signal, by 92% compared to outside ambient conditions. These results indicate that cabin air recirculation is a promising method to improve vehicle fuel economy and improve cabin air quality.

Recently, there are discussions about whether current sampling and measurement practices for the regulated gravimetric PM measurement are sufficiently accurate in quantifying PM at the proposed 3 and 1 mg/mi emission standards for light-duty vehicles. In this study, a series of modifications were made to the existing gravimetric PM measurement method, aiming to preserve the integrity of the method while increasing the robustness and decreasing the testing variability. The experiments were conducted with a Higher (~2 mg/mile) and a Lower (0.1-0.2 mg/mile) PM Source Vehicle over the Federal Test Procedure (FTP) and US06 cycles, providing PM emissions with various solid/semi-volatile compositions and size distributions. The results showed the suggested modifications, i.e., increased filter face velocities (from 100 to 150 cm/s) and combined filters (single filter vs. 3/4 filters), could increase the collected filter mass without introducing statistically significant differences in the measured PM mass emission rates. No statistically significant improvements were seen in the measurement variability with the Higher PM Source Vehicle. For the Lower PM Source Vehicle; however, the 4-phase cumulative filter showed a statistically significant reduction in PM mass measurement variability, while not impacting the measured PM mass emissions, but these improvements must be weighed against the increased testing costs/time required for the longer test time.

Vehicle cabin air quality depends on various parameters such as number of passengers, fan speed, and vehicle speed. In addition to controlling the temperature inside the vehicle, HVAC control system has evolved to improve cabin air quality as well. However, there is no standard test method to ensure reliable and repeatable comparison among different cars. The current study defined Cabin Air Quality Index (CAQI) and proposed a test method to determine CAQI. CAQI particles showed dependence on the choice of metrics among particle number (PN), particle surface area (PS), and particle mass (PM). CAQI particles is less than 1 while CAQI CO2 is larger than 1. The proposed test method is promising but needs further improvement for smaller coefficient of variations (COVs).

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