利用先进的元建模方法提高瞬态共轭热问题的仿真效率和质量

IF 0.5 Q4 TRANSPORTATION SCIENCE & TECHNOLOGY
Simon Peissner, B. Weigand
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引用次数: 0

摘要

在热防护领域,详细的三维计算流体动力学(3D-CFD)模拟被广泛用于分析整车的热行为。一个目标是在开发过程的早期阶段确定可能违反组件温度限制的情况。在纯电动汽车(bev)中,暂态负载情况在评估接近真实车辆运行的部件和车辆系统方面发挥着越来越重要的作用。在运行瞬态负载场景时,最先进的3D模拟方法需要大量的时间和计算工作量。一个主要原因是问题的共轭特性,这意味着组件内部的传导和对周围空气的对流同时发生。这需要详细考虑流体和构造领域。因此,本文推导了一种高效的电动汽车瞬态部件温度仿真方法。该方法是通过样品流动模拟提取换热系数和参考温度,并构建对流元模型。然后通过低维元模型提供对流传热,瞬时计算固体组分温度。量纲分析确定元建模的最小可能参数空间。对两种不同类型的元模型——标量回归模型和向量适当正交分解(POD)方法进行了检验和比较。该研究首先使用一个通用平板测试案例,检验了传热公式在不同流量和组件温度条件下的适用性。低Biot数(Bi)对于获得准确的温度预测至关重要,因为传热系数是在均匀温度壁上导出的。该方法随后应用于电机室的样品组件。在试验台上的实测和瞬态载荷情况下的耦合仿真对比验证了数值方法的有效性。扩展到全车应用是可行的。新方法提供了一个高度准确的温度预测和提高计算效率,特别是敏感性研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Simulation Efficiency and Quality of Transient Conjugate Thermal Problems by Using an Advanced Meta-modeling Approach
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.
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