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• W2794156355 abstract "This paper considers an application of model predictive control to automotive air conditioning (A/C) system in future connected and automated vehicles (CAVs) with battery electric or hybrid electric powertrains. A control-oriented prediction model for A/C system is proposed, identified, and validated against a higher fidelity simulation model (CoolSim). Based on the developed prediction model, a nonlinear model predictive control (NMPC) problem is formulated and solved online to minimize the energy consumption of the A/C system. Simulation results illustrate the desirable characteristics of the proposed NMPC solution such as being able to enforce physical constraints of the A/C system and maintain cabin temperature within a specified range. Moreover, it is shown that by utilizing the vehicle speed preview and through coordinated adjustment of the cabin temperature constraints, energy efficiency improvements of up to 9% can be achieved." @default.
• W2794156355 created "2018-03-29" @default.
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• W2794156355 date "2018-03-01" @default.
• W2794156355 modified "2023-10-18" @default.
• W2794156355 title "Model Predictive Climate Control of Connected and Automated Vehicles for Improved Energy Efficiency" @default.
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• W2794156355 doi "https://doi.org/10.48550/arxiv.1803.00720" @default.
• W2794156355 hasPublicationYear "2018" @default.
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