{"title":"Enhancing Simulation Efficiency and Quality of Transient Conjugate\n Thermal Problems by Using an Advanced Meta-modeling Approach","authors":"Simon Peissner, B. Weigand","doi":"10.4271/15-16-03-0016","DOIUrl":null,"url":null,"abstract":"In the field of thermal protection, detailed three-dimensional computational\n fluid dynamics (3D-CFD) simulations are widely used to analyze the thermal\n behavior on a full vehicle level. One target is to identify potential violations\n of component temperature limits at an early stage of the development process. In\n battery electric vehicles (BEVs), transient load cases play an increasing role\n in evaluating components and vehicle systems close to real-world vehicle\n operation. The state-of-the-art 3D simulation methodologies require significant\n time and computational effort when running transient load scenarios. One main\n reason is the conjugate characteristic of the problem, meaning that conduction\n within the component and convection into the surrounding air occur\n simultaneously. This requires a detailed consideration of both the fluid and\n structural domains.\n\n \nTherefore, this article derives a time-efficient simulation methodology for\n transient component temperatures in electric vehicles. The approach is to\n extract heat transfer coefficients and reference temperatures from sample flow\n simulations and to construct convective meta-models. Solid component\n temperatures are then transiently computed whereby the low-dimensional\n meta-models provide the convective heat transfer. Dimensional analysis\n determines the smallest possible parameter space for the meta-modeling. Two\n different types of meta-models, a scalar regression model and a vector proper\n orthogonal decomposition (POD) approach, are tested and compared.\n\n \nThe study examines at first the applicability of the heat transfer formulation\n under different flow and component temperature conditions using a generic flat\n plate test case. A low Biot number (Bi) is crucial to receive accurate\n temperature predictions as heat transfer coefficients are derived on uniform\n temperature walls. The methodology is subsequently applied to a sample component\n in the motor compartment. Measurements on a test rig and a transient load case\n comparison with a coupled simulation prove the validity of the numerical\n procedure. Scaling to full-vehicle applications is feasible. The new methodology\n delivers a highly accurate temperature prediction and increases computation\n efficiency, especially for sensitivity studies.","PeriodicalId":29661,"journal":{"name":"SAE International Journal of Passenger Vehicle Systems","volume":" ","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SAE International Journal of Passenger Vehicle Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4271/15-16-03-0016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
In the field of thermal protection, detailed three-dimensional computational
fluid dynamics (3D-CFD) simulations are widely used to analyze the thermal
behavior on a full vehicle level. One target is to identify potential violations
of component temperature limits at an early stage of the development process. In
battery electric vehicles (BEVs), transient load cases play an increasing role
in evaluating components and vehicle systems close to real-world vehicle
operation. The state-of-the-art 3D simulation methodologies require significant
time and computational effort when running transient load scenarios. One main
reason is the conjugate characteristic of the problem, meaning that conduction
within the component and convection into the surrounding air occur
simultaneously. This requires a detailed consideration of both the fluid and
structural domains.
Therefore, this article derives a time-efficient simulation methodology for
transient component temperatures in electric vehicles. The approach is to
extract heat transfer coefficients and reference temperatures from sample flow
simulations and to construct convective meta-models. Solid component
temperatures are then transiently computed whereby the low-dimensional
meta-models provide the convective heat transfer. Dimensional analysis
determines the smallest possible parameter space for the meta-modeling. Two
different types of meta-models, a scalar regression model and a vector proper
orthogonal decomposition (POD) approach, are tested and compared.
The study examines at first the applicability of the heat transfer formulation
under different flow and component temperature conditions using a generic flat
plate test case. A low Biot number (Bi) is crucial to receive accurate
temperature predictions as heat transfer coefficients are derived on uniform
temperature walls. The methodology is subsequently applied to a sample component
in the motor compartment. Measurements on a test rig and a transient load case
comparison with a coupled simulation prove the validity of the numerical
procedure. Scaling to full-vehicle applications is feasible. The new methodology
delivers a highly accurate temperature prediction and increases computation
efficiency, especially for sensitivity studies.