Development of an artificial intelligence-based cooling load map for buses in Türkiye

IF 5.4 3区工程技术 Q2 ENERGY & FUELS Thermal Science and Engineering Progress Pub Date : 2025-05-01 Epub Date: 2025-03-16 DOI:10.1016/j.tsep.2025.103516

Şaban Ünal , Mehmet Bilgili , Orhan Büyükalaca , Hakan Akgün

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Abstract

Accurate calculation of air-conditioning cooling load is a prerequisite for optimal design of vehicle air-conditioning systems. This study aims to develop a monthly average bus cooling load map for Türkiye using an artificial neural network (ANN) approach. For this purpose, the Radiant Time Series (RTS) method recommended by ASHRAE was used as the cooling load calculation method. The cooling load values obtained for all 81 cities of Türkiye then utilized to train the ANN model, and a cooling load map was created that allows for the determination of the cooling load value for buses across the country. A comparison of the results from the RTS and ANN methods revealed high similarity, with Adana showing the highest cooling load and Ardahan the lowest in both models. The difference between maximum cooling load values from RTS and ANN ranged from 13.4% to 8.8% across test cities. Ultimately, the ANN approach offers a rapid and reliable means of calculating bus cooling loads, allowing for predictive adjustments to air-conditioning systems and potential energy savings.

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基于人工智能的公共汽车冷负荷图的开发

空调冷负荷的准确计算是车载空调系统优化设计的前提。本研究旨在利用人工神经网络（ANN）方法为泰国 rkiye开发月平均公交车冷负荷图。为此，采用ASHRAE推荐的辐射时间序列（RTS）方法作为冷负荷计算方法。然后，rkiye所有81个城市的冷负荷值被用于训练人工神经网络模型，并创建了一个冷负荷图，可以确定全国公共汽车的冷负荷值。RTS和ANN方法的结果比较显示出高度的相似性，在两种模型中，Adana的冷却负荷最高，而Ardahan的冷却负荷最低。在测试城市中，RTS和ANN的最大冷负荷值之间的差异从13.4%到8.8%不等。最终，人工神经网络方法提供了一种快速可靠的计算公共汽车冷负荷的方法，允许对空调系统进行预测性调整和潜在的节能。

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来源期刊

Thermal Science and Engineering Progress Chemical Engineering-Fluid Flow and Transfer Processes

CiteScore

7.20

自引率

10.40%

发文量

327

审稿时长

41 days

期刊介绍： Thermal Science and Engineering Progress (TSEP) publishes original, high-quality research articles that span activities ranging from fundamental scientific research and discussion of the more controversial thermodynamic theories, to developments in thermal engineering that are in many instances examples of the way scientists and engineers are addressing the challenges facing a growing population – smart cities and global warming – maximising thermodynamic efficiencies and minimising all heat losses. It is intended that these will be of current relevance and interest to industry, academia and other practitioners. It is evident that many specialised journals in thermal and, to some extent, in fluid disciplines tend to focus on topics that can be classified as fundamental in nature, or are ‘applied’ and near-market. Thermal Science and Engineering Progress will bridge the gap between these two areas, allowing authors to make an easy choice, should they or a journal editor feel that their papers are ‘out of scope’ when considering other journals. The range of topics covered by Thermal Science and Engineering Progress addresses the rapid rate of development being made in thermal transfer processes as they affect traditional fields, and important growth in the topical research areas of aerospace, thermal biological and medical systems, electronics and nano-technologies, renewable energy systems, food production (including agriculture), and the need to minimise man-made thermal impacts on climate change. Review articles on appropriate topics for TSEP are encouraged, although until TSEP is fully established, these will be limited in number. Before submitting such articles, please contact one of the Editors, or a member of the Editorial Advisory Board with an outline of your proposal and your expertise in the area of your review.