Embedded Model Predictive Control of Tankless Gas Water Heaters to Enhance Users' Comfort

被引:0
作者
Conceicao, Cheila [1 ]
Quinta, Andre [1 ,2 ,3 ]
Ferreira, Jorge A. F. [1 ,2 ,3 ]
Martins, Nelson [1 ,2 ,3 ]
dos Santos, Marco P. Soares [1 ,2 ,3 ]
机构
[1] Univ Aveiro, Dept Mech Engn, P-3810193 Aveiro, Portugal
[2] Univ Aveiro, TEMA Ctr Mech Technol & Automat, P-3810193 Aveiro, Portugal
[3] LASI Intelligent Syst Associate Lab, P-4800058 Guimaraes, Portugal
关键词
tankless gas water heater; domestic hot water; thermal comfort; model predictive control; hardware-in-the-loop simulation; low-cost embedded control; PERFORMANCE; ALGORITHM; ENERGY; MPC; GENERATION; PUMP;
D O I
10.3390/machines11100951
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Water heating is a significant part of households' energy consumption, and tankless gas water heaters (TGWHs) are commonly used. One of the limitations of these devices is the difficulty of keeping hot water temperature setpoints when changes in water flow occur. As these changes are usually unexpected, the controllers typically used in these devices cannot anticipate them, strongly affecting the users' comfort. Moreover, considerable water and energy waste are associated with the long-time response to cold starts. This work proposes the development of a model predictive control (MPC) to be deployed in low-cost hardware, such that the users' thermal comfort and water savings can be improved. Matlab/Simulink were used to develop, validate and automatically generate C code for implementing the controller in microcontroller-based systems. Hardware-in-the-loop simulations were performed to evaluate the performance of the MPC algorithm in 8-bit and 32-bit microcontrollers. A 6.8% higher comfort index was obtained using the implementation on the 32-bit microcontroller compared to the current deployments; concerning the 8-bit microcontroller, a 4.2% higher comfort index was achieved. These applications in low-cost hardware highlight that users' thermal comfort can be successfully enhanced while ensuring operation safety. Additionally, the environmental impact can be significantly reduced by decreasing water and energy consumption in cold starts of TGWHs.
引用
收藏
页数:20
相关论文
共 50 条
  • [31] Optimizing space cooling of a nearly zero energy building via model predictive control: Energy cost vs comfort
    Ascione, Fabrizio
    Masi, Rosa Francesca De
    Festa, Valentino
    Mauro, Gerardo Maria
    Vanoli, Giuseppe Peter
    ENERGY AND BUILDINGS, 2023, 278
  • [32] Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems
    Chakrabarty, Ankush
    Zavitsanou, Stamatina
    Doyle, Francis J., III
    Dassau, Eyal
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2018, 65 (03) : 575 - 586
  • [33] Research and Implementation of Model Predictive Control for Aircraft Engines with Embedded Distributed Architecture
    Sheng H.-L.
    Gu Z.-C.
    Chen Q.
    Liu Q.
    Yin B.-X.
    Wang Z.
    Zhang T.-H.
    Tuijin Jishu/Journal of Propulsion Technology, 2023, 44 (11):
  • [34] Thermal comfort-conscious eco-climate control for electric vehicles using model predictive control
    Kwak, Kyoung Hyun
    Chen, Youyi
    Kim, Jaewoong
    Kim, Youngki
    Jung, Dewey D.
    CONTROL ENGINEERING PRACTICE, 2023, 136
  • [35] Ride Comfort Improvements on Disturbed Railroads Using Model Predictive Control
    Posseckert, Alexander
    Luedicke, Daniel
    VEHICLES, 2023, 5 (04): : 1353 - 1366
  • [36] Curve Tilting With Nonlinear Model Predictive Control for Enhancing Motion Comfort
    Zheng, Yanggu
    Shyrokau, Barys
    Keviczky, Tamas
    Al Sakka, Monzer
    Dhaens, Miguel
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2022, 30 (04) : 1538 - 1549
  • [37] Ride Comfort Improvements of Railway Vehicles Using Model Predictive Control
    Posseckert, Alexander
    Luedicke, Daniel
    ADVANCES IN DYNAMICS OF VEHICLES ON ROADS AND TRACKS III, VOL 1, IAVSD 2023, 2025, : 417 - 428
  • [38] Optimizing building comfort temperature regulation via model predictive control
    Alvarez, J. D.
    Redondo, J. L.
    Camponogara, E.
    Normey-Rico, J.
    Berenguel, M.
    Ortigosa, P. M.
    ENERGY AND BUILDINGS, 2013, 57 : 361 - 372
  • [39] Model Predictive Control of a Laboratory Gas Turbine
    Surendran, Swathi
    Chandrawanshi, Ritesh
    Kulkarni, Sanjeet
    Bhartiya, Sharad
    Nataraj, Paluri S. V.
    Sampath, Suresh
    2016 INDIAN CONTROL CONFERENCE (ICC), 2016, : 79 - 84
  • [40] Optimizing Occupant Comfort in a Room Using the Predictive Control Model as a Thermal Control Strategy
    Boicu, Mihaela-Gabriela
    Stamatescu, Grigore
    Fagarasan, Ioana
    Vasluianu, Mihaela
    Neculoiu, Giorgian
    Dobrea, Marius-Alexandru
    SENSORS, 2024, 24 (12)