Thermal Controller Research Articles

Skin temperature patterns during exercise that act as a thermal controller of the body

Skin temperature patterns during exercise that act as a thermal controller of the body

Non-linear cascade control with gain-scheduling and startup control strategy study for thermionic space reactor TOPAZ-II

The TOPAZ-II thermionic space reactor system, which was designed by the Soviet Union, is characterized by its high degree of nonlinearity and positive temperature reactivity feedback. The thermionic space reactor exhibits characteristics of high inertia and significant delay in controlling its electrical power and outlet temperature. The simple PID controller is difficult to achieve good performance. To carry out controller design for thermionic space reactor, the simulation platform for thermionic space reactor is developed based on coupling between reactor system thermal-hydraulic code RESYS and control system simulator in this study. After that, based on the cascade control strategy and gain-scheduling, the reactor thermal controller, electric power controller, outlet temperature controller applicable for the full power range is designed with transfer function model and frequency domain analysis method. To validate the nonlinear electric power controller performance, the continuous minor step disturbances, major step disturbances, and ramp variation of electric power setpoint is simulated. The performance of outlet temperature controller is verified with the simulation result of step and ramp variation of outlet temperature setpoint. Thereafter, the start-up process of the thermionic space reactor TOPAZ-II is simulated and analyzed. The simulation result reveals that the controller designed in this paper can overcome the nonlinearity of the thermionic space reactor system and has good performance throughout the entire power range. Compared to traditional simple PID controller, the cascade controller has better performance and can achieve good control performance even in situations where simple PID controllers cannot function properly.

Water and Thermal Management in PEM Fuel Cells Using Feasible Humidity Plots and Model Predictive Controllers

Water and thermal management are critical for the performance, efficiency and longevity of PEM fuel cells (PEMFCs). Effective water and thermal management require the design of control systems that can maintain the water balance and temperature at stable and optimal levels. In this paper, we consider a stack of PEM fuel cells integrated with a water recovery and cooling system. A mechanistic dynamic model is developed to be able to predict the water content and temperature in response to the fuel cell inputs. Water management uses a cascade arrangement of a supervisory Model Predictive Controller (MPC) and local anode and cathode PID humidity controllers to balance the membrane water content. Thermal management consists of a separate MPC controller to regulate the fuel stack temperature. One novelty of this work lies in identifying and utilizing the feasible region for the relative humidities of the anode and cathode when controlling the membrane water content. We introduce the feasible humidity plots (FHP) which define the feasible values for the anode and cathode relative humidities for a given fuel cell design and its operating conditions. This useful information helps to assign the set-point values to the local PID humidity controllers of the water management system. It is shown by simulations that the water and thermal management MPC controllers work in tandem and successfully track the desired set-point changes in humidity and temperature while rejecting external disturbances such as load changes. In addition, the control system is robust against modeling errors and possible model-plant mismatch introduced by fuel cell aging.

Multi-objective optimization of combined heat and power system integrated with multi-energy storage systems for rural communities

Renewable-based combined heat and power system (CHPS) benefit communities by enhancing energy resilience and reducing energy costs and emissions. Considering its reliability issues, previous studies integrated two or more energy sources or employed energy storage systems, compromising emission reduction or imposing an economic burden. To address this challenge, this study introduces three energy system schemes (ESSs) based on renewable, non-renewable, and hybrid energy resources. Each ESS includes various feasible configurations integrated with energy storage systems, such as batteries and hydrogen, resulting in 22 configurations modeled, optimized, and systematically investigated using HOMER software, considering energy-economic-environmental (3E) criteria to select the optimal system configuration (OSC). The introduced CHPS configurations are presented in a practical case study of a remote community in Pakistan. Results showcased that OSC belongs to a hybrid ESS with the following characteristics: (a) COE (0.127 $/kWh) and NPC (0.192 M$) are minimum among other configurations, (b) capacity shortage and unmet electric load are 0.21 % and 0.14 %, and (c) CO2 is reduced by 67.49 % compared to the base case. Furthermore, the 3E effect of adding a thermal load controller and batteries to the OSC is explored. The 3E results are inclusively compared with the existing literature, revealing that OSC is economical, reliable, and eco-friendly.

Experimental evaluation of various flow meters using gaseous CO2

The need for accurate flow measurement within the Carbon Capture, Utilisation and Storage (CCUS) transport network is widely reported and understood as a requirement of Emission Trading Schemes and commercial contracts. In meeting this requirement, traceable calibration is needed in conditions which closely mimic the process conditions. However, currently accredited calibration facilities cannot meet the conditions for calibrating in gaseous CO2 and so a likely alternative solution for these custody transfer flow meters is to be calibrated with an alternative fluid and the calibration transferred. In this article, which was produced under the framework of the EMPIR project “Metrology for Decarbonising the Gas Grid”, the authors will investigate this approach with a number of flow meters tested in natural gas, nitrogen gas and finally in carbon dioxide gas at varying pressures. The results of which will suggest that orifice and Coriolis meters can be calibrated in another fluid however, an ultrasonic meter would require further work and potentially require calibration in CO2. This article will also investigate the effects of impurities in a CO2 gas stream for a rotary displacement flow meter and a thermal mass flow controller compared against a piston prover which provides a primary reference flow standard.

Design of refrigerated micro-flow thermal mass flow controller

Design of refrigerated micro-flow thermal mass flow controller

Field test of machine-learning based mean radiant temperature estimation methods for thermal comfort-integrated air-conditioning control improvement and energy savings

Advanced control strategies for heating, ventilation, and air-conditioning (HVAC) systems aim to enhance both buildings' energy efficiency and occupant thermal comfort. Despite their potential, real-world demonstration studies on such advanced technologies are still lacking. This study presents a field demonstration of a real-time predicted mean vote (PMV)-based HVAC control strategy in a typical residential building under hot and dry climate conditions. This study introduces an advanced thermal comfort-based controller (TCC) for the PMV-based HVAC control. TCC continually assesses indoor and outdoor thermal conditions and adjusts the HVAC setpoint temperature to optimize real-time energy use while ensuring satisfactory indoor thermal comfort. Machine learning models for the PMV-based HVAC control system are employed to estimate a mean radiant temperature (MRT) point, which is one of the variables used to calculate real-time PMV values. Three machine learning models (i.e., linear regression, regression trees, and artificial neural network) are adopted in this study with non-stationary real-time input values, including times, pre-determined setpoints, and indoor and outdoor temperatures. The developed TCC is installed in a full-scale experimental house in Kuwait, which is under hot and dry climate conditions, to assess the house's indoor thermal comfort and AC energy efficiency performance. Results indicate that the TCC provides better thermal comfort performance compared to the non-TCC case, including up to a 60% improvement in PMV. The proposed TCC controlled by the machine learning methods demonstrates HVAC energy savings potential of over 20% while meeting the desired thermal comfort levels in the experimental building. These findings are expected to be valuable, as they can contribute to reducing cooling energy in residential buildings in hot and dry climate conditions.

Optimal Design and Techno-Economic Analysis of a Hybrid System to Supply a Remote Fishpond with Electricity and Heat

This paper deals with the design of a hybrid system for the generation of electricity and heat that will supply a remote fishpond in eastern Serbia. The proposed hybrid system consists of a micro-hydro power plant (MHPP), a photovoltaic (PV) generator, a combined heat and power (CHP) unit with one diesel generator, batteries, a converter, a thermal load controller (TLC), and a boiler. A comprehensive techno-economic analysis is performed in the HOMER Pro software, which evaluated and compared 12 possible configurations with different combinations of system components. The results show that the optimal system has the lowest total net present cost (NPC) and the lowest levelized cost of energy (COE) amounting to 284421.0 $ and 0.178 $/kWh, respectively. Compared to a diesel/batteries/converter/boiler hybrid system, the proposed system produces 65.4 % less greenhouse gas (GHG) emissions, while the shares of electricity, heat, and renewable energy generation are increased by 31.1 %, 5.0 %, and 51.2 %, respectively. It is shown that covering the demand for heat by regenerating the waste heat from the diesel generator and excess electricity from renewables contributes to reducing the total cost of the system and the GHG emissions. This finding finally emphasised the necessity of applying TLCs in off-grid hybrid systems.

Data-driven adaptive building thermal controller tuning with constraints: A primal–dual contextual Bayesian optimization approach

We study the problem of tuning the parameters of a room temperature controller to minimize its energy consumption, subject to the constraint that the daily cumulative thermal discomfort of the occupants is below a given threshold. We formulate it as an online constrained black-box optimization problem where, on each day, we observe some relevant environmental context and adaptively select the controller parameters. In this paper, we propose to use a data-driven Primal-Dual Contextual Bayesian Optimization (PDCBO) approach to solve this problem.In a simulation case study on a single room, we apply our algorithm to tune the parameters of a Proportional Integral (PI) heating controller and the pre-heating time. Our results show that PDCBO can save up to 4.7% energy consumption compared to other state-of-the-art Bayesian optimization-based methods while keeping the daily thermal discomfort below the given tolerable threshold on average. Additionally, PDCBO can automatically track time-varying tolerable thresholds while existing methods fail to do so. We then study an alternative constrained tuning problem where we aim to minimize the thermal discomfort with a given energy budget. With this formulation, PDCBO reduces the average discomfort by up to 63% compared to state-of-the-art safe optimization methods while keeping the average daily energy consumption below the required threshold.

Thermogravitational Convection in a Controlled Rotating Darcy-Brinkman Nanofluids Layer Saturated in an Anisotropic Porous Medium Subjected to Internal Heat Source

Thermogravitational convection in a controlled rotating Darcy-Brinkman nanofluids layer saturated in an anisotropic porous medium heated from below is Thermogravitational convection in a controlled rotating Darcy-Brinkman nanofluids layer saturated in an anisotropic porous medium heated from below is investigated. The presence of a uniformly distributed internal heat source and considers the Brinkman model for different boundary conditions: rigid-rigid, free-free, and lower-rigid and upper-free are considered. The effect of a control strategy involving sensors located at the top plate and actuators positioned at the bottom plate of the nanofluids layer is analysed. Linear stability analysis based on normal mode technique is employed. The resulting eigenvalue problem is solved numerically using the Galerkin method implemented with Maple software. The model used for the nanofluids associates with the mechanisms of Brownian motion and thermophoresis. The influences of the internal heat source strength, mechanical anisotropy parameter, modified diffusivity ratio, nanoparticles concentration Darcy-Rayleigh number and nanofluids Lewis number are found to advance the onset of convection. Conversely, the Darcy number, thermal anisotropy parameter, porosity, rotation, and controller effects are observed to slow down the process of convective instability.investigated. The presence of a uniformly distributed internal heat source and considers the Brinkman model for different boundary conditions: rigid-rigid, free-free, and lower-rigid and upper-free are considered. The effect of a control strategy involving sensors located at the top plate and actuators positioned at the bottom plate of the nanofluids layer is analysed. Linear stability analysis based on normal mode technique is employed. The resulting eigenvalue problem is solved numerically using the Galerkin method implemented with Maple software. The model used for the nanofluids associates with the mechanisms of Brownian motion and thermophoresis. The influences of the internal heat source strength, mechanical anisotropy parameter, modified diffusivity ratio, nanoparticles concentration Darcy-Rayleigh number and nanofluids Lewis number are found to advance the onset of convection. Conversely, the Darcy number, thermal anisotropy parameter, porosity, rotation, and controller effects are observed to slow down the process of convective instability.

Multi-criteria decision analysis for the planning of island microgrid system: A case study of Yongxing island, China

Remote island communities often struggle to meet energy needs affordably, sustainably, and reliably. Island microgrid (IM) systems offer a promising solution; however, optimal planning considering diverse components and alternatives remains challenging. Using China's Yongxing Island as a case study, we propose a novel indicator system integrating economic, resilience, energy, and environmental dimensions. The indicator system is integrated with the HOMER Pro software and the reference point method to identify the optimal energy configuration of Yongxing Island's IM system. Moreover, a comprehensive uncertainty analysis is conducted on the optimal configuration to reveal how optimal configuration results change relative to changes in energy demand, energy prices, and investment costs of technologies and to demonstrate how the system would cope with disturbance. To meet Yongxing Island's 2030 energy demand (including electricity, thermal, and hydrogen), the best energy configuration scheme for the microgrid is the combination of photovoltaic panels, wind turbines, diesel generators, energy storage batteries, external grid, electrolyzers, diesel reformers, hydrogen tanks, thermal load controllers, boilers, and power converters. Moreover, wind turbines dominate power supply and would change the sizing and hourly power generation under uncertainties. Thermal demand relies on thermal load controllers, while electrolyzers and diesel reformers address hydrogen demand.

Evaluation of a pedestrian call extension and cancelation system at a signalized midblock crossing

ABSTRACT Unnecessary vehicular delay occurs at actuated signalized intersections during ‘ghost’ pedestrian intervals when a pedestrian activates the pushbutton then jaywalks. Safety issues arise when pedestrians remain in the crosswalk at the end of the Flashing Don’t Walk phase, and vehicles receive a circular green. A Pedestrian Call Extension and Cancelation System was evaluated at a signalized midblock crossing in Hillsboro, OR. Thermal sensors and controller logic were implemented to detect pedestrians and passively cancel or extend calls. A Case 1-after study was conducted to evaluate how vehicular delay and pedestrian behavior was impacted by the system. 1,649 observations Case 1 and 3,002 observations after system installation were recorded. Pedestrian delay did not change, but average vehicular stop time delay significantly decreased by 12 sec. 76 extensions occurred with 99.2% accuracy. Findings suggest that transportation agencies could improve driver waiting time and pedestrian safety by using dynamic passive pedestrian detection.

Experimental study of stability and pollutant emissions of turbulent biogas flames under microsecond pulsed plasma

Biogas is a mixture of methane (50–80%.vol), carbon dioxide (20–45%.vol), and in smaller proportions of N2, O2, H2S, and NH3. For a high rate of CO2 in the biogas, the combustion can generate strong instabilities and the flame can be very lifted from the burner and even blown. To overcome these problems of instabilities and flame extinction, the use of a microsecond pulsed plasma is considered for this study. This study aims to characterize the effects of microsecond pulsed discharges on the stabilization and emission characteristics of non-premixed swirling biogas/air flames at different operating conditions of combustion (CO2 rate, power, and equivalence ratio) and plasma (pulse repetition frequency and input electrical voltage). The plasma is performed above a coaxial burner with a swirler of the oxidizer. It is generated by a DC-pulsed power generator with a high voltage (HV) pulse duration of a few microseconds. The burner consists of two concentric tubes and a central metal rod used as a cathode for the plasma. The outer tube contains a swirler and supplies the oxidant flow, and the inner tube delivers the fuel (methane, biogas) around the central metal rod. High voltage pulses are applied on two anode tungsten wires that are symmetrically arranged from either side of the cathode to obtain two plasma zones in the stabilization region of the flame. The burner is placed in a parallelepiped combustion chamber with a volume of 100x48x48 cm3. Mass flow rates of air and fuel are regulated by thermal mass flow controllers (Brooks SLA5851S). OH* chemiluminescence measurements are done to describe the structure and the flame stability throughout the lift-off heights (Hf) variation. Results showed that plasma generated by microsecond HV pulses can improve flame stability by decreasing its Hf especially at low fuel velocities. In this regard, the optical emission spectra (OES) were visualized. The results reveal that the pulsed plasma generates chemically active species such as excited N2*, CH*, OH* molecules, and H* atoms, leading to improved flame stability. Their intensities' dependence on the pulse repetition frequency, the sight position of the OES, the concentration of CO2 in the fuel, and the fuel velocities were investigated in detail. Furthermore, the NOx and CO emissions in the burned gas are investigated over a wide range of repetition pulse frequencies. It is seen that the microsecond pulsed plasma slightly increases the NOx emission and reduces CO concentration in the flue gases.

Techno-economic analysis of a renewable-based hybrid energy system for utility and transportation facilities in a remote community of Northern Alberta

Many off-grid communities in Canada are dependent on diesel generators to fulfill their utility and transportation needs, causing destructive environmental impact. This study aims to optimize and investigate the techno-economic feasibility of a hybrid renewable energy system to satisfy the 1.6 MWh/day electricity, 184.2 kWh/day thermal, and 428.38 kg/year hydrogen demand simultaneously, Trout Lake, a remote community of Northern Alberta. A novel hybrid energy system consisting of solar PV, wind turbine, electrolyzer, hydrogen tank, battery, fuel cell, hydrogen boiler, and thermal load controller has been proposed to generate electricity, heat, and hydrogen by renewables which reduce carbon emission utilizing the excess energy (EE). Five different scenarios were developed in HOMER Pro software, and the results were compared to identify the best combination of hybrid renewable energy systems. The results indicate that the fifth scenario is the optimal renewable energy system that provides a lower cost of energy (COE) at $0.675/kWh and can reduce 99.99% carbon emission compared to the diesel-based system. Additionally, the utilization of thermal load controller, battery, and fuel cell improved the system's reliability, increasing renewable fraction (RF) (93.5%) and reducing EE (58.3%) significantly. In comparison to the diesel-based systems, it is also discovered that battery energy storage is the most affordable option, while fuel cells are the more expensive choice for remote community. Sensitivity analyses are performed to measure the impact of different dominating factors on COE, EE, and RF.

Giant room-temperature electrical switching effects in water-in-oil emulsions

Thermally-triggered electrical switching materials are of urgent demand for developing novel temperature sensors, overheat protection circuits, thermal controllers, battery management systems against overheating, etc. Here, we report a water-in-oil emulsion system with giant electrical switching ratios at room temperature prepared by a simple and efficient method. The temperature-sensitive phase transition process of alkanes as the oil phase causes the formation and collapse of conductive paths in the emulsion, resulting in electrical switching ratios of up to 6 orders of magnitude. The emulsions have good thermal cycle stability, and the switching ratio remains essentially unchanged after 100 cycles. The switching temperature can be easily adjusted by using alkanes of various chain lengths. In addition, the similar electrical switching effect is observed in four emulsions containing different neutral salts, ensuring the tunability and versatility of the system. The electrical switching emulsions offer a promising avenue to developing future high-performance, energy-saving, and low-cost electrical switching systems.

Разработка нейросетевого регулятора для дизеля

The paper considers issues of using a neural network in the thermal engine controller in order to improve the quality of its control and setting conveniences. The study object was a speed controller for the D500 promising locomotive diesel engine. Tasks for design and development of a neural network controller were formulated, and the network input signals were determined. To adjust the neural network, the reinforcement learning method was introduced, where it interacted with the diesel engine computer model in a closed system. The criterion in setting up the network was the accuracy of the control program execution. A system of rewards was assigned, according to which the network was learning. Based on the results of studying the neural network controller influence on the quality of the control system operation, the network minimum possible composition for solving the problem presented was determined. Study results are presented in the form of graphs of rewards alteration during the learning process for various options of the neural network controller structure, as well as the control system simulated transient processes over the entire range of the diesel engine speed.

Real-time process monitoring and closed-loop control on laser power via a customized laser powder bed fusion platform

Additive manufacturing (AM) is one of the most effective ways to fabricate parts with complex geometries using various materials. However, AM also suffers from printing quality issues resulting from the defects such as over-melt, lack of fusion, swelling, etc. One of the root causes of those issues is that the process parameters remain constant during the entire printing process, regardless of the dynamic heat accumulation and various printing feature sizes. For instance, raster is the most common scanning strategy in the laser powder bed fusion (L-PBF) process. The length of the raster line varies depending on the printing feature size. When scanning small features, the raster line is short, resulting in heat accumulations and over-melt. These variabilities may cause severe quality issues and thus suggest adaptive process parameters be applied. Aiming to address this challenge, this study develops a closed-loop control system to regulate the laser power based on melt pool thermal emission to avoid over-melt, balling, and high surface roughness. The control target is determined by correlating the printing quality (dimensional printing error in this study) with the thermal emission through thin-line printing trials using variable power. A high-speed thermal sensor and controller are designed, tuned, and implemented on a newly developed L-PBF testbed. The system successfully maintains a low dimensional error by regulating the laser power at 2 kHz. A significant improvement in printing quality was achieved, as validated by both microscopic imaging and 3D scanning.

The Comparison of P, PI and PID Strategy Performance as Temperature Controller in Active Iris Damper for Centralized Air Conditioning System

The topic of maintaining thermal comfort efficiency in the heating, ventilation and air conditioning (HVAC) sector has always been tricky due to numerous challenges. The study focused on the challenge of under-actuated zones in non – residential and commercial buildings. The active iris damper with the integration of thermal controller is proposed to control the indoor temperature. Besides, integration of PID control strategy will be a tempting control system in enhancing the thermal performance of the building. Again, the PID controller has proven good compatibility as a primary closed-loop mechanism to maintain a comfortable room temperature. The development of the control system is done through the Arduino platform with LabVIEW as the front panel and data logging platform. The Heuristic tuning method was employed to obtain optimal gains for P, PI and PID controllers. The performance of each controller was tested by observing their ability to maintain steadily at the desired temperature set point. These tests conveyed that the best controller for this application is the PID controller. It reached the desired temperature set point and maintained it even with a temperature disruption. This study indicates that an active iris damper can effectively maintain the thermal comfort performance of indoor environment with the implementation of PID strategy, thus remedying some of the problems faced by centralized air-conditioning systems.

Numerical investigation on thermal performance of thermoelectric-cooler integrated cold plate of thermal control liquid loop in spacecraft

The traditional single-phase fluid loop (SFL) and traditioanl thermal control algorithm can barely control the temperature rapidly. Thermoelectric cooler (TEC) has been proved to be a good thermal controller because of its high reliability, liquid-free characteristics, and fast response. This paper proposes a TEC-based precooling module that resides in front of the cold plate (CP), and consists of a TEC-CP system, manifesting a high compatibility between the novel precooling module and traditional SFL. The TEC-CP system was designed, and a mathematical model of heat and mass transfer was developed to numerically investigate the effects of the geometric parameters, TEC operating conditions, and liquid cooling states of the precooling module upon payload thermal performance. Through analysis, an optimal TEC-based precooling module with optimal geometric dimensions was attained, where the coolant temperature was decreased by 13.04 K, resulting in a 28.98% reduction compared to that without the precooling module. Transient results also demonstrate that the temperature response time can be within 3 min, indicating a fast response system for temperature control. Results outlined in this paper provide structural and data references for future designs of scientific rack-level thermal control loops in space stations.

Thermal modeling and controller design of an alkaline electrolysis system under dynamic operating conditions

Thermal management is vital for the efficient and safe operation of alkaline electrolysis systems. Traditional alkaline electrolysis systems use simple proportional–integral–differentiation (PID) controllers to maintain the stack temperature near the rated value. However, in renewable-to-hydrogen scenarios, the stack temperature is disturbed by load fluctuations, and the temperature overshoot phenomenon occurs which can exceed the upper limit and harm the stack. This paper focuses on the thermal modeling and controller design of an alkaline electrolysis system under dynamic operating conditions. A control-oriented thermal model is established in the form of a third-order time-delay process, which is used for simulation and controller design. Based on this model, we propose two novel controllers to reduce temperature overshoot: one is a current feed-forward PID controller (PID-I), the other is a model predictive controller (MPC). Their performances are tested on a lab-scale system and the experimental results are satisfying: the temperature overshoot is reduced by 2.2 °C with the PID-I controller, and no obvious overshoot is observed with the MPC controller. Furthermore, the thermal dynamic performance of an MW-scale alkaline electrolysis system is analyzed by simulation, which shows that the temperature overshoot phenomenon is more general in large systems. The proposed method allows for higher temperature set points which can improve system efficiency by 1%.