TY - GEN
T1 - Gray-Box Modeling of the Vehicle Cabin and Comparison of Model Accuracy using Different Zonal Distributions
AU - Xiong, Yuxin
AU - Gottig, Roland
AU - Sedlbauer, Klaus
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Thermal models are essential for the climate control system of vehicles, as they provide crucial information on the occupants' thermal comfort and help optimize the heating, ventilation, and air conditioning (HVAC) system performance. A control-oriented cabin model should deliver accurate predictions while ensuring fast computational performance. With increasing expectations for thermal comfort, the predictability of zonal temperatures has become an essential aspect. This paper established various cabin models (mono-zone, 4-zone, and 8-zone model) using the gray-box modeling method. The parameters of these models were identified using measurements from real-world test drives based on available vehicle sensors and ten additional air temperature sensors. The goal is to develop a suitable cabin model and to determine a reasonable zonal distribution. Three model variants yielded promising results, with the average coefficient of determination (R²) calculated as 0.83 (mono-zone), 0.75 (4-zone), and 0.74 (8-zone).
AB - Thermal models are essential for the climate control system of vehicles, as they provide crucial information on the occupants' thermal comfort and help optimize the heating, ventilation, and air conditioning (HVAC) system performance. A control-oriented cabin model should deliver accurate predictions while ensuring fast computational performance. With increasing expectations for thermal comfort, the predictability of zonal temperatures has become an essential aspect. This paper established various cabin models (mono-zone, 4-zone, and 8-zone model) using the gray-box modeling method. The parameters of these models were identified using measurements from real-world test drives based on available vehicle sensors and ten additional air temperature sensors. The goal is to develop a suitable cabin model and to determine a reasonable zonal distribution. Three model variants yielded promising results, with the average coefficient of determination (R²) calculated as 0.83 (mono-zone), 0.75 (4-zone), and 0.74 (8-zone).
KW - Zonal cabin model
KW - gray-box modeling
KW - real-world test drive
KW - thermal comfort
KW - vehicle thermal management
UR - http://www.scopus.com/inward/record.url?scp=85173878327&partnerID=8YFLogxK
U2 - 10.1109/CCTA54093.2023.10253429
DO - 10.1109/CCTA54093.2023.10253429
M3 - Conference contribution
AN - SCOPUS:85173878327
T3 - 2023 IEEE Conference on Control Technology and Applications, CCTA 2023
SP - 714
EP - 720
BT - 2023 IEEE Conference on Control Technology and Applications, CCTA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Conference on Control Technology and Applications, CCTA 2023
Y2 - 16 August 2023 through 18 August 2023
ER -