2018/03/02 by Hao Wang, Wang, Hao, Ilya Kolmanovsky +5
Engineering · #Advanced Battery Technologies Research #Electric and Hybrid Vehicle Technologies #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Refrigeration and Air Conditioning Technologies #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1803.00720
openalex publication_date 2018/03/02 · openalex created_date 2018/03/29 · openalex updated_date 2026/07/28
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.