Model Predictive Climate Control of Electric Vehicles for Improved Battery Lifetime

Abstract

The battery is still an obstacle to the development of electric vehicles (EVs) due to its high cost, low capacity and limited lifetime. Harsh power fluctuations and high power peaks during driving can accelerate the battery lifetime degradation. In this paper, we optimize the energy consumption of the EV battery by jointly controlling the heating, ventilation, and air-conditioning (HVAC) system and the drive system to improve the battery lifetime. Firstly, we establish the powertrain model of the EV to obtain the future propulsion power requirements during the driving process, and nonlinear models are developed to estimate the thermal load and dynamic behavior of the HVAC system and the cabin. Then, we propose a nonlinear model predictive climate control scheme for automotive HVAC system to minimize the expected power variations and power peaks of the EV battery and enable the cabin temperature within the comfort range by using the knowledge of predictive driving energy demands. At last, we compare the performance of the proposed nonlinear model predictive control (NMPC) approach and the traditional on-off switching controller of automotive HVAC system. Simulation results demonstrate the effectiveness of our proposed algorithm in improving the EV battery lifetime.