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arXiv · 1803.00720

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

Hao Wang·Ilya Kolmanovsky·Mohammad Reza Amini·Jing Sun
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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.

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Hao Wang, Ilya Kolmanovsky, Mohammad Reza Amini, Jing Sun. 2018-03-02. Model Predictive Climate Control of Connected and Automated Vehicles for Improved Energy Efficiency. https://arxiv.org/abs/1803.00720

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