학술논문
Construction of Thermal Boundary Surrogate Model Using Multiple Regression Analysis and Deep Learning for Prediction of Coolant Temperature / 冷却水温予測のための重回帰分析と深層学習を活用した熱境界サロゲートモデルの構築
Document Type
Journal Article
Author
Source
自動車技術会論文集 / Transactions of Society of Automotive Engineers of Japan. 2023, 54(4):764
Subject
Language
Japanese
ISSN
0287-8321
1883-0811
1883-0811
Abstract
Engine coolant temperature prediction utilizes Conjugate Heat Transfer (CHT) analysis. However, identifying the combustion chamber walltemperature based on actual measurements is a time-consuming process. The purpose of this paper is to develop a surrogate model that canpredict the combustion chamber wall temperature faster than conventional methods. We propose that a surrogate model utilizing multipleregression analysis and deep learning can achieve high explanability and high efficiency.