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This paper considers an application of model predictive control to automotiveair conditioning (A/C) system in future connected and automated vehicles (CAVs)with battery electric or hybrid electric powertrains. A control-orientedprediction model for A/C system is proposed, identified, and validated againsta higher fidelity simulation model (CoolSim). Based on the developed predictionmodel, a nonlinear model predictive control (NMPC) problem is formulated andsolved online to minimize the energy consumption of the A/C system. Simulationresults illustrate the desirable characteristics of the proposed NMPC solutionsuch as being able to enforce physical constraints of the A/C system andmaintain cabin temperature within a specified range. Moreover, it is shown thatby utilizing the vehicle speed preview and through coordinated adjustment ofthe cabin temperature constraints, energy efficiency improvements of up to 9%can be achieved.

Model Predictive Climate Control of Connected and Automated Vehicles for Improved Energy Efficiency