本文以特斯拉電動車18650電池陣列作為原型，透過簡化電池發熱特性，研究其在具有不同散熱條件之空腔中，透過實際物理模型進行熱傳及對流實驗，以此結合逆向熱傳導方法，並運用計算流體力學之計算結果，比較經驗公式以觀察不同紊流模型造成模擬結果之差異，選出適合用於計算之紊流模型，並在計算後彙整結果，結合後處理使流場與溫度場可視化，以此觀察不同條件下帶給電池組熱傳特性影響及空腔中對流方式變化，找尋出適合之電池模型散熱方式。
比對了實驗數據及數值分析之結果，Zero-eq在本模型中具有較優良之計算能力，其在自然對流時選定模型時與經驗公式所計算得到之熱傳導係數h比較之最大誤差僅為6%，在自然對流時具有開口之空腔相對無開口之空腔，空氣溫度都能有所降低，而電池組具有最佳散熱性能為側邊具有上側及下側開口之空腔及頂部開放之空腔，而強制對流雖無經驗公式可做比較，但相較於其他紊流模型具有較好的收斂性及節省30%計算時間，在強制對流中，任一組之散熱性能皆優於於自然對流之組別，其單一溫度最高可達17K之溫差，而在強制對流之組別中，不同開口位置會改變場域中之流道，影響其不同位置電池之散熱能力，其中以側板具有上方及下方開口之組別電池組整體溫度較低，較為適合電池組之散熱。

By comparing the experimental data with the numerical analysis results, the Zero-eq model exhibits superior computational capabilities in this model. The maximum discrepancy in the heat transfer coefficient (h) calculated by the Zero-eq model and the empirical formula for natural convection is only 6%. In natural convection, the presence of openings in the cavity leads to a decrease in air temperature. The cavity configuration with side openings at the upper and lower parts and top open exhibits the best heat dissipation performance for the battery pack. Although there are no empirical formulas for comparison in forced convection, the Zero-eq model demonstrates better convergence and saves 30% of computation time compared to other turbulence models. In forced convection, all groups exhibit better heat dissipation performance than the natural convection group, with a maximum temperature difference of 17K. Different opening positions in the forced convection group alter the flow channels in the domain, affecting the heat dissipation capabilities of batteries at different locations. The group with side openings at the upper and lower parts shows lower overall battery temperatures and is more suitable for battery cooling.

Keywords: Computational Fluid Dynamics, Inverse Heat Conduction, Natural

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