Gain scheduling model predictive controller design for tankless gas water heaters with time-varying delay

Quintã, André; Ehtiwesh, Ismael A.S.; Martins, Nélson; Ferreira, José Martins

doi:10.1016/j.applthermaleng.2022.118669

Cited by 10 publications

(6 citation statements)

References 24 publications

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“…Water temperature instability from overshoots and undershoots is the most common disadvantage of TGWHs The parameter estimation and subsequent validation are performed with an associated optimization platform using a discrete state space model. The undisclosed parameters have been identified using the experimental virtual test (Quintã et al, 2022). In addition, by reason of the dominant nonlinear dynamics in TGWH behavior, an adaptive predictive control strategy has also been studied (Ehtiwesh et al, 2021).…”

Section: Case Studiesmentioning

confidence: 99%

Low-‎computational adaptive MPC algorithmization strategy for over ‎and ‎undershoots ‎instantaneous ‎water ‎heaters stability

Ehtiwesh

2023

Seatific

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Tankless gas hot water users' perceived comfort is severely affected by sudden changes deviating from the desired temperature. Water temperature instability due to overshoots and undershoots is the most common issue that appears mainly due to sudden changes in users' water flow demands and response delays inherent to the heating system. Classical controllers for heat cells have difficulties responding to temperature instability in a timely manner because they lack the capacity to anticipate the effects of sudden variations in water flow rate. Previous studies have reported the model predictive controller (MPC) with adaptive function strategy to provide the best response for stabilizing temperature, and its performance is a result of the predictive nature that allows for anticipating and correcting the negative effects on temperature from sudden flow rate variations. The present study aims to employ this strategy to a low-computational algorithm that can be embedded in low-cost hardware with limited computational and memory resources. The study's motivation is to fill the space manufacturers have left in this regard by implementing low-cost optimal-performance microcontrollers for water heaters. The algorithm results show good agreement for the responses in temperature stabilization with experimental data.

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Section: Case Studiesmentioning

confidence: 99%

Low-‎computational adaptive MPC algorithmization strategy for over ‎and ‎undershoots ‎instantaneous ‎water ‎heaters stability

Ehtiwesh

2023

Seatific

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“…A linear model established in our previous work [8] was used, as it requires low computational load and, then, it requires a processing capability that can be provided by low-cost microcontrollers. The model output was defined as the output water temperature (T)'s deviation from the input temperature (T in ), as expressed by Equation (3).…”

Section: Linear Modelmentioning

confidence: 99%

“…Combining Equations (1) and ( 3) and assuming that the inlet water temperature is approximately constant (negligible inlet temperature changes were considered for model simplification, as assumed in previous studies [5,8,9,15,57]), the output temperature deviation was defined by Equation (4).…”

Section: Linear Modelmentioning

confidence: 99%

“…Temperature stabilisation of TGWHs has been pursued by including additional hardware, namely bypass valves, mixing valves and reservoirs working as thermal capacitances [6,7]. The classical feedback controllers, proportional and proportional-integral-derivative (PID), are inappropriate for the temperature control of TGWHs [8]. Some authors propose using advanced control techniques not requiring mathematical modelling, such as fuzzy logic control [9,10] and artificial neural networks [11,12].…”

Section: Introductionmentioning

confidence: 99%

“…In this scope, neuro-fuzzy control was also proposed to overcome the complexity of mathematical problems [13,14]. Classic model predictive control (MPC), adaptive MPC and gain-schedule MPC have also been proposed for water temperature control [5,8,15]. Yuill, Henze and Coward [16][17][18] focused on control strategies for electric water heaters, from classical techniques, such as PID control, to more advanced techniques, such as predictive control.…”

Section: Introductionmentioning

confidence: 99%

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

Conceição,

Quintã,

Ferreira

et al. 2023

Machines

Self Cite

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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.

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Design of an economically sustainable energy recovery system for domestic instant geyser

Ali,

Zia-ur Rahman,

Hussain

et al. 2024

J Therm Anal Calorim

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Gain scheduling model predictive controller design for tankless gas water heaters with time-varying delay

Cited by 10 publications

References 24 publications

Low-‎computational adaptive MPC algorithmization strategy for over ‎and ‎undershoots ‎instantaneous ‎water ‎heaters stability

Low-‎computational adaptive MPC algorithmization strategy for over ‎and ‎undershoots ‎instantaneous ‎water ‎heaters stability

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

Design of an economically sustainable energy recovery system for domestic instant geyser

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