The gas water heater control system design based on fuzzy control

Wang, Li; Zang, Haihe; Ning, Yi

doi:10.1109/iceice.2011.5778171

Cited by 7 publications

(4 citation statements)

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“…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%

“…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]. In this scope, neuro-fuzzy control was also proposed to overcome the complexity of mathematical problems [13,14].…”

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

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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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Section: Linear Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Conceição,

Quintã,

Ferreira

et al. 2023

Machines

View full text Add to dashboard Cite

show abstract

“…The study reported that the Python algorithm can be encoded within just a couple of lines in the MATLAB environment. Wang et al (2011) proposed a few controller schemes for improving the outlet temperature stabilization of TGWH systems with a fuzzy control system intended as a black box gain scheduler regarding the parameters of a PID controller. Haissig and Woessner (2000) studied an adaptive fuzzy control code that would adapt to changing conditions such as water flow rate and inlet water temperature and automatically adjust the feed-forward curves of the gas valve control.…”

Section: Introductionmentioning

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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“…Several advanced control strategies were proposed to improve TGWH water temperature stabilization, in (Wang, Zang and Ning, 2011), a fuzzy controller is proposed as a black-box gain scheduler for the parameters of a PID controller. An adaptive fuzzy control algorithm is presented in (Haissig and Woessner, 2000) that is adapted to the changing conditions (water flow rate and inlet water temperature) and automatically adjusts the feedforward curves of the gas valve controller.…”

Section: Introductionmentioning

confidence: 99%

Predictive control strategies for optimizing temperature stability in instantaneous hot water systems

Ehtiwesh

Quintã

Ferreira

2021

Science and Technology for the Built Environment

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Domestic hot water production is responsible for a significant part of domestic energy consumption; instantaneous gas heating devices are widely used because they don't require reservoirs, therefore have a competitive use/consumption ratio compared to other technologies. However, users' perception of comfort is severely affected by sudden changes in temperature outside the desired temperature. The instability of the water temperature with overshoots and undershoots is the most common disadvantage, which occurs mainly due to sudden changes in the water flow requested by users and the response delays inherent to the heating system. Traditional heat cell power controllers have difficulties in responding to these problems in a timely manner, as they don't have the capacity to anticipate the effects of sudden variations in water flowrate.In this work, predictive control strategies were developed which, due to its predictive nature, allows anticipating and correcting the negative effects of sudden variations of water flowrate in the temperature. A comparative analysis of model based predictive controllers (MPCs), with and without adaptive function, with traditional controllers used in the tankless gas water heaters (TGWHs) was carried out. Tests in a simulated environment demonstrated better performances in the stabilization of temperature during sudden changes in water flowrates.

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The gas water heater control system design based on fuzzy control

Cited by 7 publications

References 0 publications

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

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

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

Predictive control strategies for optimizing temperature stability in instantaneous hot water systems

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