Comparison between Physics-Based Approaches and Neural Networks for the Energy Consumption Optimization of an Automotive Production Industrial Process
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Široký, Jan & Oldewurtel, Frauke & Cigler, Jiří & Prívara, Samuel, 2011. "Experimental analysis of model predictive control for an energy efficient building heating system," Applied Energy, Elsevier, vol. 88(9), pages 3079-3087.
- Li, Yantong & Ding, Zhixiong & Du, Yaxing, 2020. "Techno-economic optimization of open-air swimming pool heating system with PCM storage tank for winter applications," Renewable Energy, Elsevier, vol. 150(C), pages 878-890.
- Giampieri, A. & Ling-Chin, J. & Ma, Z. & Smallbone, A. & Roskilly, A.P., 2020. "A review of the current automotive manufacturing practice from an energy perspective," Applied Energy, Elsevier, vol. 261(C).
- Atmaca, Adem & Kanoglu, Mehmet, 2012. "Reducing energy consumption of a raw mill in cement industry," Energy, Elsevier, vol. 42(1), pages 261-269.
- Min, Qingfei & Lu, Yangguang & Liu, Zhiyong & Su, Chao & Wang, Bo, 2019. "Machine Learning based Digital Twin Framework for Production Optimization in Petrochemical Industry," International Journal of Information Management, Elsevier, vol. 49(C), pages 502-519.
- Seung-Hwan, Yoo & Jin-Yong, Choi & Sang-Hyun, Lee & Yun-Gyeong, Oh & Dong Koun, Yun, 2013. "Climate change impacts on water storage requirements of an agricultural reservoir considering changes in land use and rice growing season in Korea," Agricultural Water Management, Elsevier, vol. 117(C), pages 43-54.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Muhammad Fayaz & DoHyeun Kim, 2018. "Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic," Energies, MDPI, vol. 11(1), pages 1-22, January.
- Yang, Shiyu & Wan, Man Pun & Ng, Bing Feng & Dubey, Swapnil & Henze, Gregor P. & Chen, Wanyu & Baskaran, Krishnamoorthy, 2020. "Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system," Applied Energy, Elsevier, vol. 257(C).
- Muniak, Damian Piotr, 2014. "A new methodology to determine the pre-setting of the control valve in a heating installation. A general model," Applied Energy, Elsevier, vol. 135(C), pages 35-42.
- Lork, Clement & Li, Wen-Tai & Qin, Yan & Zhou, Yuren & Yuen, Chau & Tushar, Wayes & Saha, Tapan K., 2020. "An uncertainty-aware deep reinforcement learning framework for residential air conditioning energy management," Applied Energy, Elsevier, vol. 276(C).
- Gokhale, Gargya & Claessens, Bert & Develder, Chris, 2022. "Physics informed neural networks for control oriented thermal modeling of buildings," Applied Energy, Elsevier, vol. 314(C).
- Mikulčić, Hrvoje & Vujanović, Milan & Ashhab, Moh'd Sami & Duić, Neven, 2014. "Large eddy simulation of a two-phase reacting swirl flow inside a cement cyclone," Energy, Elsevier, vol. 75(C), pages 89-96.
- Molinari, Marco & Anund Vogel, Jonas & Rolando, Davide & Lundqvist, Per, 2023. "Using living labs to tackle innovation bottlenecks: the KTH Live-In Lab case study," Applied Energy, Elsevier, vol. 338(C).
- Pisello, Anna Laura & Goretti, Michele & Cotana, Franco, 2012. "A method for assessing buildings’ energy efficiency by dynamic simulation and experimental activity," Applied Energy, Elsevier, vol. 97(C), pages 419-429.
- Reynolds, Jonathan & Rezgui, Yacine & Kwan, Alan & Piriou, Solène, 2018. "A zone-level, building energy optimisation combining an artificial neural network, a genetic algorithm, and model predictive control," Energy, Elsevier, vol. 151(C), pages 729-739.
- Danfeng Zhang & Xin Wang & Liang Zhao & Huaqing Xie & Chen Guo & Feizhou Qian & Hui Dong & Yun Hu, 2023. "Numerical Investigation on Heat Transfer and Flow Resistance Characteristics of Superheater in Hydrocracking Heat Recovery Steam Generator," Energies, MDPI, vol. 16(17), pages 1-15, August.
- Ma, Peizheng & Wang, Lin-Shu & Guo, Nianhua, 2015. "Maximum window-to-wall ratio of a thermally autonomous building as a function of envelope U-value and ambient temperature amplitude," Applied Energy, Elsevier, vol. 146(C), pages 84-91.
- Mustafa Musa Jaber & Mohammed Hassan Ali & Sura Khalil Abd & Mustafa Mohammed Jassim & Ahmed Alkhayyat & Ezzulddin Hasan Kadhim & Ahmed Rashid Alkhuwaylidee & Shahad Alyousif, 2023. "RETRACTED ARTICLE: AHI: a hybrid machine learning model for complex industrial information systems," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-22, March.
- Sachin Kumar & Zairu Nisha & Jagvinder Singh & Anuj Kumar Sharma, 2022. "Sensor network driven novel hybrid model based on feature selection and SVR to predict indoor temperature for energy consumption optimisation in smart buildings," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 3048-3061, December.
- Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
- Fatigati, Fabio & Di Battista, Davide & Cipollone, Roberto, 2021. "Design improvement of volumetric pump for engine cooling in the transportation sector," Energy, Elsevier, vol. 231(C).
- Hou, Juan & Li, Haoran & Nord, Natasa, 2022. "Nonlinear model predictive control for the space heating system of a university building in Norway," Energy, Elsevier, vol. 253(C).
- Pi, Dawei & Xue, Pengyu & Wang, Weihua & Xie, Boyuan & Wang, Hongliang & Wang, Xianhui & Yin, Guodong, 2023. "Automotive platoon energy-saving: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
- Cong Zhou & Yizhen Li & Fenghao Wang & Zeyuan Wang & Qing Xia & Yuping Zhang & Jun Liu & Boyang Liu & Wanlong Cai, 2023. "A Review of the Performance Improvement Methods of Phase Change Materials: Application for the Heat Pump Heating System," Energies, MDPI, vol. 16(6), pages 1-21, March.
- Sun, Chunhua & Liu, Yiting & Cao, Shanshan & Chen, Jiali & Xia, Guoqiang & Wu, Xiangdong, 2022. "Identification of control regularity of heating stations based on cross-correlation function dynamic time delay method," Energy, Elsevier, vol. 246(C).
- Žáčeková, Eva & Váňa, Zdeněk & Cigler, Jiří, 2014. "Towards the real-life implementation of MPC for an office building: Identification issues," Applied Energy, Elsevier, vol. 135(C), pages 53-62.
More about this item
Keywords
automotive production process; paint shop; digital twin; model predictive control; artificial neural network; physics-based model;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6916-:d:1252066. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.