IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v260y2022ics036054422202076x.html
   My bibliography  Save this article

Model predictive control of portable electronic devices under skin temperature constraints

Author

Listed:
  • Liu, Haoran
  • Yu, Jiaqi
  • Wang, Ruzhu

Abstract

Thermal management is becoming a major challenge for electronics, and a better temperature control algorithm that could maximize the system performance will play a greater role in fully utilizing the existing cooling capacity. Unfortunately, the simplest look-up table method is still widely used as the temperature control algorithm in current portable electronic devices, especially laptops, resulting in a significant performance loss of devices. In this paper, a general temperature control framework for a commercial laptop that considers the skin temperature constraints is proposed based on the model predictive control algorithm. In specific, a high-accuracy compact thermal model is first generated through the model order reduction method and validated by abundant experimental data. Then the proposed MPC is numerically evaluated in three test scenarios, covering different workloads and performance indexes. The results show that the proposed MPC outperforms the baseline look-up table method by achieving about 10–20% higher performance index in different test scenarios. The open-loop optimal control method is also considered to estimate the optimality of the proposed MPC. Moreover, a parametric study is conducted to analyze the influence of different control parameters, indicating broad prospects for the future application of the proposed MPC algorithm.

Suggested Citation

  • Liu, Haoran & Yu, Jiaqi & Wang, Ruzhu, 2022. "Model predictive control of portable electronic devices under skin temperature constraints," Energy, Elsevier, vol. 260(C).
  • Handle: RePEc:eee:energy:v:260:y:2022:i:c:s036054422202076x
    DOI: 10.1016/j.energy.2022.125185
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422202076X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2022.125185?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xie, Shaobo & Hu, Xiaosong & Xin, Zongke & Brighton, James, 2019. "Pontryagin’s Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 236(C), pages 893-905.
    2. Jiao, Feixiang & Zou, Yuan & Zhang, Xudong & Zhang, Bin, 2022. "Online optimal dispatch based on combined robust and stochastic model predictive control for a microgrid including EV charging station," Energy, Elsevier, vol. 247(C).
    3. Li, Tianyu & Liu, Huiying & Wang, Hui & Yao, Yongming, 2020. "Hierarchical predictive control-based economic energy management for fuel cell hybrid construction vehicles," Energy, Elsevier, vol. 198(C).
    4. Zou, Changfu & Hu, Xiaosong & Wei, Zhongbao & Tang, Xiaolin, 2017. "Electrothermal dynamics-conscious lithium-ion battery cell-level charging management via state-monitored predictive control," Energy, Elsevier, vol. 141(C), pages 250-259.
    5. Hou, Jun & Sun, Jing & Hofmann, Heath, 2018. "Control development and performance evaluation for battery/flywheel hybrid energy storage solutions to mitigate load fluctuations in all-electric ship propulsion systems," Applied Energy, Elsevier, vol. 212(C), pages 919-930.
    6. Zhong, Hao & Lei, Fei & Zhu, Wenhao & Zhang, Zhe, 2022. "An operation efficacy-oriented predictive control management for power-redistributable lithium-ion battery pack," Energy, Elsevier, vol. 251(C).
    7. Fu, Hao & Shen, Jiong & Sun, Li & Lee, Kwang Y., 2021. "In-depth characteristic analysis and wide range optimal operation of fuel cell using multi-model predictive control," Energy, Elsevier, vol. 234(C).
    8. Knudsen, Brage Rugstad & Rohde, Daniel & Kauko, Hanne, 2021. "Thermal energy storage sizing for industrial waste-heat utilization in district heating: A model predictive control approach," Energy, Elsevier, vol. 234(C).
    9. Yu, Min Gyung & Pavlak, Gregory S., 2022. "Extracting interpretable building control rules from multi-objective model predictive control data sets," Energy, Elsevier, vol. 240(C).
    10. Wang, Yujie & Zhou, Caijie & Chen, Zonghai, 2022. "Optimization of battery charging strategy based on nonlinear model predictive control," Energy, Elsevier, vol. 241(C).
    Full references (including those not matched with items on IDEAS)

    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.
    1. Zhou, Hongxu & Yu, Zhongwei & Wu, Xiaohua & Fan, Zhanfeng & Yin, Xiaofeng & Zhou, Lingxue, 2023. "Dynamic programming improved online fuzzy power distribution in a demonstration fuel cell hybrid bus," Energy, Elsevier, vol. 284(C).
    2. Yaqian Wang & Xiaohong Jiao, 2022. "Dual Heuristic Dynamic Programming Based Energy Management Control for Hybrid Electric Vehicles," Energies, MDPI, vol. 15(9), pages 1-19, April.
    3. Hou, Jun & Song, Ziyou, 2020. "A hierarchical energy management strategy for hybrid energy storage via vehicle-to-cloud connectivity," Applied Energy, Elsevier, vol. 257(C).
    4. Li, Niansi & Liu, Xiaoyong & Yu, Bendong & Li, Liang & Xu, Jianqiang & Tan, Qiong, 2021. "Study on the environmental adaptability of lithium-ion battery powered UAV under extreme temperature conditions," Energy, Elsevier, vol. 219(C).
    5. Ramadan, Mohamad & Murr, Rabih & Khaled, Mahmoud & Olabi, Abdul Ghani, 2018. "Mixed numerical - Experimental approach to enhance the heat pump performance by drain water heat recovery," Energy, Elsevier, vol. 149(C), pages 1010-1021.
    6. Du, Guodong & Zou, Yuan & Zhang, Xudong & Liu, Teng & Wu, Jinlong & He, Dingbo, 2020. "Deep reinforcement learning based energy management for a hybrid electric vehicle," Energy, Elsevier, vol. 201(C).
    7. Anselma, Pier Giuseppe, 2022. "Computationally efficient evaluation of fuel and electrical energy economy of plug-in hybrid electric vehicles with smooth driving constraints," Applied Energy, Elsevier, vol. 307(C).
    8. Hou, Jun & Song, Ziyou & Park, Hyeongjun & Hofmann, Heath & Sun, Jing, 2018. "Implementation and evaluation of real-time model predictive control for load fluctuations mitigation in all-electric ship propulsion systems," Applied Energy, Elsevier, vol. 230(C), pages 62-77.
    9. Penghui Qiang & Peng Wu & Tao Pan & Huaiquan Zang, 2021. "Real-Time Approximate Equivalent Consumption Minimization Strategy Based on the Single-Shaft Parallel Hybrid Powertrain," Energies, MDPI, vol. 14(23), pages 1-22, November.
    10. Elkadeem, Mohamed R. & Kotb, Kotb M. & Abido, Mohamed A. & Hasanien, Hany M. & Atiya, Eman G. & Almakhles, Dhafer & Elmorshedy, Mahmoud F., 2024. "Techno-enviro-socio-economic design and finite set model predictive current control of a grid-connected large-scale hybrid solar/wind energy system: A case study of Sokhna Industrial Zone, Egypt," Energy, Elsevier, vol. 289(C).
    11. Chen, Jiaxin & Shu, Hong & Tang, Xiaolin & Liu, Teng & Wang, Weida, 2022. "Deep reinforcement learning-based multi-objective control of hybrid power system combined with road recognition under time-varying environment," Energy, Elsevier, vol. 239(PC).
    12. Song, Yuguang & Xia, Mingchao & Yang, Liu & Chen, Qifang & Su, Su, 2023. "Multi-granularity source-load-storage cooperative dispatch based on combined robust optimization and stochastic optimization for a highway service area micro-energy grid," Renewable Energy, Elsevier, vol. 205(C), pages 747-762.
    13. Tang, Ruoli & An, Qing & Xu, Fan & Zhang, Xiaodi & Li, Xin & Lai, Jingang & Dong, Zhengcheng, 2020. "Optimal operation of hybrid energy system for intelligent ship: An ultrahigh-dimensional model and control method," Energy, Elsevier, vol. 211(C).
    14. Fengqi Zhang & Lihua Wang & Serdar Coskun & Hui Pang & Yahui Cui & Junqiang Xi, 2020. "Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook," Energies, MDPI, vol. 13(13), pages 1-35, June.
    15. Saletti, Costanza & Morini, Mirko & Gambarotta, Agostino, 2022. "Smart management of integrated energy systems through co-optimization with long and short horizons," Energy, Elsevier, vol. 250(C).
    16. Chen, Xiaoyuan & Jiang, Shan & Chen, Yu & Lei, Yi & Zhang, Donghui & Zhang, Mingshun & Gou, Huayu & Shen, Boyang, 2022. "A 10 MW class data center with ultra-dense high-efficiency energy distribution: Design and economic evaluation of superconducting DC busbar networks," Energy, Elsevier, vol. 250(C).
    17. Qi, Chunyang & Zhu, Yiwen & Song, Chuanxue & Yan, Guangfu & Xiao, Feng & Da wang, & Zhang, Xu & Cao, Jingwei & Song, Shixin, 2022. "Hierarchical reinforcement learning based energy management strategy for hybrid electric vehicle," Energy, Elsevier, vol. 238(PA).
    18. Jichao Liu & Yanyan Liang & Zheng Chen & Wenpeng Chen, 2023. "Energy Management Strategies for Hybrid Loaders: Classification, Comparison and Prospect," Energies, MDPI, vol. 16(7), pages 1-23, March.
    19. Meng, Lingyu & See, K.W. & Wang, Guofa & Wang, Yunpeng & Zhang, Yong & Zang, Caiyun & Xie, Bin, 2022. "Explosion-proof lithium-ion battery pack – In-depth investigation and experimental study on the design criteria," Energy, Elsevier, vol. 249(C).
    20. Tri Cuong Do & Hoai Vu Anh Truong & Hoang Vu Dao & Cong Minh Ho & Xuan Dinh To & Tri Dung Dang & Kyoung Kwan Ahn, 2019. "Energy Management Strategy of a PEM Fuel Cell Excavator with a Supercapacitor/Battery Hybrid Power Source," Energies, MDPI, vol. 12(22), pages 1-24, November.

    Corrections

    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:eee:energy:v:260:y:2022:i:c:s036054422202076x. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.