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Passengers are exposed to roadway pollutants due to entrainment of outside air into the vehicle cabin. Previous works found cabin air-recirculation can reduce pollutant particle concentrations significantly. However simultaneous increase of CO₂ concentrations in the cabin prevented wide use of recirculation mode for such purpose. A mathematical model was developed to predict CO₂ concentrations in vehicle cabin air during air-recirculation mode. The model predicts temporal CO₂ concentration changes as a function of cabin volume, vehicle body leakage, and number of passengers. This model can be used to design and control air-recirculation mode for a variety of vehicle conditions.

More than a hundred million Air Quality Sensors (AQS) have been used since the late 80s to improve in-cabin air quality on high-end cars. This is more than a billion dollars spent. A study conducted in two major cities (USA & Europe) showed that a novel method based on high-resolution air quality maps outperforms the use of on-board AQS. The total passenger exposure to pollution was compared for several flap management algorithm cases: flap always open, random open/close, map-based algorithm, and AQS-based algorithm. The results are likely to disrupt the AQS market since the map-based method is a pure software solution with lower cost per vehicle than the sensor itself. The data volume used to calculate the air quality maps was sufficient to obtain good average correlations between individual trip pollution profiles and the map Air Quality Indices (AQI) along the trip path.

The proliferation of electric vehicles (EVs) is resulting in a big transition in the automotive industry, with the goal of reducing greenhouse gas emissions and improving energy efficiency. There are a variety of different architectural configurations and power distribution strategies that can be optimized for drivability performance, all-electric range, and overall efficiency. This paper describes the efforts of the research team in exploring different EV architectures to better understand their impacts on system performance in terms of energy efficiency and vehicle drivability. In search for an ideal powertrain architecture for a shared-use EV, the research team conducted a comprehensive analysis of a various EV architectures (including RWD and AWD) with different motor parameters, considering a spectrum of targeted vehicle technology specifications such as acceleration and braking performance, and fuel economy.