Thermal comfort-conscious eco-climate control for electric vehicles using model predictive control

被引:8
作者
Kwak, Kyoung Hyun [1 ]
Chen, Youyi [1 ]
Kim, Jaewoong [2 ]
Kim, Youngki [1 ]
Jung, Dewey D. [1 ]
机构
[1] Univ Michigan Dearborn, Dept Mech Engn, Dearborn, MI 48128 USA
[2] Hyundai Kia Motor Co, Hwaseong, South Korea
关键词
Heating ventilation and air-conditioning; (HVAC) control; Model predictive control; Thermal comfort; Reheating; Energy efficiency; Electric vehicles; CABIN; TEMPERATURE; MANAGEMENT;
D O I
10.1016/j.conengprac.2023.105527
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the heating, ventilation, and air-conditioning (HVAC) system of electric vehicles (EVs), an electric heater is often used for a reheating process that warms up the chilled evaporator outlet air for thermal comfort before it is supplied to the cabin. The usage of the electric heater can significantly reduce the driving range of an EV. Therefore, optimal control of the HVAC system with consideration of the reheating process becomes essential for an increased driving range. In addition, considering the primary role of cabin climate control, it is desirable to intelligently consider the passengers' thermal comfort in climate control design. In this paper, thermal comfort-conscious eco-climate control (TCC-ECC) based on model predictive control (MPC) is proposed to enhance the energy efficiency of the HVAC operation while ensuring passengers' thermal comfort. The MPC design uses a reduced-order HVAC system model based on an ideal vapor-compression cycle. For the integration of thermal comfort into the MPC, a new approach is proposed to obtain an approximate solution of a predictive mean vote (PMV)-based thermal comfort model, which aims to balance computational efficiency and prediction accuracy. With the proposed TCC-ECC, a parametric study is conducted to analyze the impact of weighting factors on energy consumption and thermal comfort under two different thermal load conditions. Then, the performance of the tuned TCC-ECC is evaluated in comparison with a rule-based (RB) controller and the baseline eco-climate control (ECC) without considering thermal comfort. In the performance evaluation, the proposed TCC-ECC demonstrates that with the inclusion of thermal comfort it performs better in terms of energy efficiency and thermal comfort than manually adjusting a target cabin temperature depending on the environmental thermal load. The energy consumption of the proposed TCC-ECC is 22.5% and 35.24% less than that of the RB controller at an ambient temperature of 24 degrees C and 35 degrees C, respectively, and 14.5% and 18.5% less than the baseline ECC at the same conditions, respectively.
引用
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页数:16
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