(534b) Predictive Strategies for Control of Indoor Air Quality
We develop a first-principles model that relates the concentration of PM, HCHO and O3 in a room to the ventilation rate and energy consumption of the HVAC system. Different pollutants have different penetration factors, deposition velocities and indoor emission rates. Therefore, the concentration of each type of pollutant is described by a separate differential equation with the above mentioned quantities as parameters determined from experiments in the published literature. The model captures real-world situations such as pollutants entering the room from outside and pollutants generated in the room due to human activities like cooking.
Next, we use the model to identify optimal operational settings. We solve two problems: (1) identify âsteady-stateâ ventilation rate for idealized periodic variations in pollutants in the room, and (2) develop and deploy model predictive control as an online optimization strategy to calculate optimal ventilation rate at each time instant based on instantaneous measured fluctuations in indoor and outdoor conditions. The objective function of the optimization problem is the energy consumption of the system and the pollutant concentrations (either instantaneous or time-averaged) are expressed as constraints. The proposed optimization strategies show considerable reduction in energy usage compared to the existing standards, without jeopardizing indoor air quality or posing health concerns.
 Boor, B.E., Siegel, J.A., Novoselac, A., âMonolayer and multilayer particle deposits on hard surfaces: literature review and implications for particle resuspension in the indoor environment.â Aerosol Science and Technology, 47(8): 831-847 (2013)
 Morawska, L., Afshari, A., Bae, G.N., Buonanno, G., Chao, C.Y.H., Hanninen, O., Hofmann, W., Isaxon, C., Jayaratne, E.R., Pasanen, P., Salthammer, T., âIndoor aerosols: from personal exposure to risk assessment.â Indoor Air, 23(6): 462-487 (2013)