Stable Temperature Control Research Articles

Active phase and amplitude temperature control method for cryostat: A case in the thermodynamic temperature international comparison system

Achieving highly stable temperature control is essential for cryostats. However, the cryocooler used in cryostats, such as the pulse tube cryocooler, produces regular sinusoidal temperature fluctuations due to its inherent working principles. To establish a highly stable temperature environment, an active phase and amplitude control method for suppressing temperature fluctuation is proposed in this paper, by which the optimal phase and amplitude can be predicted in theory. To validate this approach, a thermal response model was developed based on experiments conducted in the thermodynamic temperature international comparison cryostat at approximately 3.7 K. Based on this model, we conducted both single-stage and multi-stage active temperature control experiments. The results demonstrate that the temperature control effect is the best when the active temperature control current is added at the second cold head, the fluctuation of the comparison copper block from 3.3mK to 0.166mK with 94.9 % suppression rate. The multi-stage joint temperature control reduced the temperature fluctuation with an attenuation rate of 95.4 %. These findings offer significant potential for improving temperature stability in future thermodynamic temperature comparison experiments.

Tracking Differentiator-Based Identification Method for Temperature Predictive Control of Uncooled Heating Processes

The temperature control of uncooled heating processes presents challenges due to a substantial lag and the absence of active cooling mechanisms, which can lead to overshoot and oscillations. To address these issues, we propose an anti-disturbance identification method based on a tracking differentiator (TD) and an input-constrained temperature predictive control (ICTPC) strategy. Our approach specifically considers the impact of unknown disturbances on model identification within a second-order heating process. By employing a TD to differentiate the input and output signals, we effectively minimize the identification error caused by low-frequency disturbances, yielding a robust anti-disturbance identification technique. Following this, we establish input constraints to limit the amplitude and variation of the control input, ensuring a more controlled and predictable system response. Using the identified model, an ICTPC algorithm is designed to achieve stable temperature control in uncooled heating processes. Experimental results from a typical uncooled heating system demonstrate that our method not only significantly reduces overshoot but also effectively mitigates temperature fluctuations, leading to enhanced control performance and system stability. This study provides a practical solution for temperature control in systems without cooling capabilities, offering substantial improvements in the efficiency and quality of industrial production processes.

Design Approach for an Advanced Multi-Channel Pyrometer for Bulk Oven Processes

Industrial processes such as smelting and sintering require stable and precise temperature control of furnaces. To achieve this, accurate temperature measurements are required. Pyrometry allows for contact- less measurement of bulk materials and is particularly suitable for high temperature applications. One of the main influences on the accuracy of pyrometric measurements is the knowledge of the emissivity in the spectral measurement range. To reduce this dependence, two-color pyrometers or multi-color pyrometers can be used. With this in mind, the IRS is further developing their existing pyrometer technology by designing an advanced multi-channel pyrometer for bulk oven processes in a joint venture with Stange Elektronik GmbH and New Generation Kilns Grün GmbH. The design approach is explained here and the considered methods of achieving emissivity independent temperature measurements are examined.

Microfluidic Rheology: An Innovative Method for Viscosity Measurement of Gels and Various Pharmaceuticals.

Measuring the viscosity of pharmaceutical dosage forms is a crucial process. Viscosity provides information about the stability of the composition, the release rate of the drug, bioavailability, and, in the case of injectable drug formulations, even the force required for injection. However, measuring viscosity is a complex task with numerous challenges, especially for non-Newtonian materials, which include most pharmaceutical formulations, such as gels. Selecting the appropriate shear rate is critical. Since viscosity in many systems is highly temperature-dependent, stable temperature control is necessary during the measurement. Using microfluidics technology, it is now possible to perform rheological characterization and conduct fast and accurate measurements. Small sample volumes (even below 500 µL) are required, and viscosity determination can be carried out over a wide range of shear rates. Nevertheless, the pharmaceutical application of viscometers operating on the principle of microfluidics is not yet widespread. In our work, we compare the results of measurements taken with a microfluidic chip-based viscometer on different pharmaceutical forms (gels, solution) with those obtained using a traditional rotational viscometer, evaluating the relative advantages and disadvantages of the different methods. The microfluidics-based method enables time- and sample-efficient viscosity analysis of the examined pharmaceutical forms.

Low-cost, open-source device for simultaneously subjecting rodents to different circadian cycles of light, food, and temperature.

Exposure of experimental rodents to controlled cycles of light, food, and temperature is important when investigating alterations in circadian cycles that profoundly influence health and disease. However, applying such stimuli simultaneously is difficult in practice. We aimed to design, build, test, and open-source describe a simple device that subjects a conventional mouse cage to independent cycles of physiologically relevant environmental variables. The device is based on a box enclosing the rodent cage to modify the light, feeding, and temperature environments. The device provides temperature-controlled air conditioning (heating or cooling) by a Peltier module and includes programmable feeding and illumination. All functions are set by a user-friendly front panel for independent cycle programming. Bench testing with a model simulating the CO2 production of mice in the cage showed: a) suitable air renewal (by measuring actual ambient CO2), b) controlled realistic illumination at the mouse enclosure (measured by a photometer), c) stable temperature control, and d) correct cycling of light, feeding, and temperature. The cost of all the supplies (retail purchased by e-commerce) was <300 US$. Detailed technical information is open-source provided, allowing for any user to reliably reproduce or modify the device. This approach can considerably facilitate circadian research since using one of the described low-cost devices for any mouse group with a given light-food-temperature paradigm allows for all the experiments to be performed simultaneously, thereby requiring no changes in the light/temperature of a general-use laboratory.

Optimal control of three-dimensional unsteady partial differential equations with convection term in continuous casting

In this paper, we investigate an optimal control problem (OCP) for three-dimensional (3D) unsteady partial differential equations with convection term (UPDECT), extensively applied to the solidification process of billets. Firstly, we introduce the mathematical model of OCP and adopt a life cycle model method (LCMM) to numerically solve the 3D UPDECT. Secondly, the Lipschitz continuity of the cost function gradient is proved using the adjoint approach as a numerical method for designing optimal control systems. The cost function gradient of OCP for 3D UPDECT is analyzed based on a Hamiltonian costate system. Thirdly, we propose a modified trinomial conjugate gradient method (MTCGM) to solve the OCP for 3D UPDECT and prove the global convergence of MTCGM. Finally, the MTCGM is applied to the experimental simulation of continuous casting. According to experiment results, the optimizer based on MTCGM can significantly accelerate the convergence speed and reduce the iterative numbers, and the MTCGM provides a more stable temperature control effect.

Experimental investigation on the characteristics of a controllable separate heat pipe-based cold storage temperature control system

PCM cold storage systems have been widely employed in household refrigerators due to their economy and efficiency. However, the PCM heat transfer process is out of effective control, limiting the accurate temperature control ability of the system. Herein, a controllable separated heat pipe that can regulate heat transfer is introduced into the PCM cold storage system to resolve its issues. A novel controllable separate heat pipe-based cold storage temperature control system is proposed. The dynamic temperature control ability and cold storage characteristics of the system under various operating conditions are revealed through experiments. As a result, the spatial inhomogeneity of the temperature field of the PCM is discovered which is related to the unsteady heat transfer between the PCMs in different regions and to the on–off state of the controllable separate heat pipe. In the discharging mode, the stable temperature control time of the compartment decreases by 53% when the temperature decreases from 7 °C to 1 °C. In addition, a lower inlet temperature of the ethylene glycol solution results in faster cold storage rates and greater temperature differences of the PCMs in different regions (the maximum temperature difference is 3.47 °C when the inlet temperature is −26 °C). Moreover, the results of door opening experiments show that the temperature can be controlled within an accuracy of 2.5 °C when the door opening time is 60 s, demonstrating the temperature regulation ability of the system. The results verify the feasibility of the technical route and provide a valuable reference for the optimization of precise temperature control systems.

Improving a Fuel Cell System’s Thermal Management by Optimizing Thermal Control with the Particle Swarm Optimization Algorithm and an Artificial Neural Network

The thermal management of proton exchange membrane fuel cell systems plays a significant role in a stack’s lifetime, performance, and reliability. However, it is challenging to manage the thermal system precisely due to the multiple coupling relationships between the stack’s components, its operating environment, and its thermal management system. In addition, temperature hysteresis (temporal inconsistency of temperature with electrochemical reactions and fluid mechanics) imposes more difficulties on thermal control. We aim to develop an effective thermal control model for the fuel cell system to improve the temperature regulation accuracy and response speed and thus achieve highly stable temperature control. A dynamic mechanistic model is first developed based on the physical processes of the stack and its thermal management system. The model is then validated through experiments. Based on this dynamic mechanistic model, a control model is proposed for stack thermal management with the particle swarm optimization algorithm and an artificial neural network. It is applied and compared with the traditional PID algorithm. The simulation results indicate that the regulation time of the coolant inlet temperature as the current changes is reduced by more than 74%, and the overshoot is reduced by more than 50%. Therefore, the control model can enhance the dynamic response capability and temperature control precision under complex operating conditions with constantly changing load current and preset stack temperature, ensuring the temperature’s stability and thus improving the fuel cell system’s reliability and durability.

Ensuring the thermal regime of spacecraft structures

The main requirement for the smooth operation of the spacecraft is its stable thermal regime. A particularly difficult task is to ensure a stable temperature control system of the device, taking into account strict restrictions on energy and mass costs for temperature control devices. These tasks need to be solved at every stage of the creation of satellites. At each stage, thermal calculations are carried out with the choice of optimal thermophysical parameters. This amount of work is about a tenth of all work with the satellite. The need for theoretical and experimental refinement of calculation methods is an urgent task that will significantly reduce the material and time costs of designing, testing and fine-tuning the device. Therefore, the calculation and analysis of the thermal regimes of spacecraft is an important stage in the design of satellites. Ground thermal vacuum tests are very costly, both in time and financially. The essence of the concept is to conduct only stationary thermal modes under conditions of maximum and minimum thermal loads on the satellite as a whole and its individual external elements, followed by ensuring convergence of test results with calculated results. And the confirmation of intermediate requirements to ensure the specified thermal conditions is carried out by calculation. The article considers the tasks of ensuring the thermal regime of spacecraft structures. Classification of devices used to ensure the thermal regime. Ground-based testing of the thermal regime of communication satellites during thermal vacuum tests. Ensuring the thermal regime of the communication spacecraft during ground-based electrical tests. Thermal regime of spacecraft structures during transportation from the manufacturer to the technical position.

Heat Integration of Liquid Hydrogen-Fueled Hybrid Electric Ship Propulsion System

This study introduced the methodology for integrating ethylene glycol/water mixture (GW) systems which supply heat energy to the liquid hydrogen (LH2) fuel gas supply system (FGSS), and manage the temperature conditions of the battery system. All systems were designed and simulated based on the power demand of a 2 MW class platform supply vessel assumed as the target ship. The LH2 FGSS model is based on Aspen HYSYS V11 and the cell model that makes up the battery system is implemented based on a Thevenin model with four parameters. Through three different simulation cases, the integrated GW system significantly reduced electric power consumption for the GW heater during ship operations, achieving reductions of 1.38% (Case 1), 16.29% (Case 2), and 27.52% (Case 3). The energy-saving ratio showed decreases of 1.86% (Case 1), 21.01% (Case 2), and 33.80% (Case 3) in overall energy usage within the GW system. Furthermore, an examination of the battery system’s thermal management in the integrated GW system demonstrated stable cell temperature control within ±3 K of the target temperature, making this integration a viable solution for maintaining normal operating temperatures, despite relatively higher fluctuations compared to an independent GW system.

A Kalman-filtering-based BRDF online measurement method for variable temperature surfaces

Bidirectional Reflectance Distribution Function (BRDF) at variable temperature is important in many applications such as thermal imaging and target detection. However, ensuring long-term stable high temperature control is complex and energy consuming, making online measurements essential. Existing BRDF systems are mainly designed for room temperature measurements, and the widely used quadrature demodulator requires a large amount of stored measurement data and complicate post-processing calculations. In this paper, the Kalman-based demodulator was modified by adding a forgetting factor to improve the demodulation speed and flexibility. This demodulator was implemented on FPGA in both numerical simulations and experiments. The detection of BRDF was demodulated online, reducing measurement time and resource consumption by half compared to the quadrature demodulator. The proposed demodulator can be utilized for further analysis of high-temperature BRDF characteristics of material surfaces.

Cloud–edge collaborative control for roaster furnace: A hybrid first-principles and data-driven method

Temperature stability control of the roaster furnace is an important yet challenging problem due to the fluctuation of feed compositions. To solve this problem, a first-principles and data-driven cloud–edge collaborative control (CECC) method is proposed. Specifically, through first-principles analysis, the influencing factors of temperature fluctuation are determined, and then the feed fluctuation is divided into two parts: the batch difference (BD) caused by changes in production objectives or process conditions, and the random fluctuation (RF) caused by uncertain factors of component content or ore source mixing process. For the problem of BD, a first-principles model of the roasting process is established by integrating multisource data in the cloud. Through timely response to the batch differences, the appropriate feed rate is sent to the edge controller to address the temperature unstable problem induced by the sudden component batch changes. For the problem of RF, a fuzzy controller based on trend analysis is adopted at the edge to fine-tune the feed rate to further reduce the negative impact of component fluctuation on the temperature. Accordingly, the proposed CECC method can realize stable control of the roaster furnace temperature synergistically. Both the numerical simulation experiment and hardware-in-the-loop platform experiment results verify the effectiveness of the proposed method.

Coordination control strategy for PEM fuel cell system considering vehicle velocity prediction information

Accurate air supply and stable temperature control are important factors to ensure fuel cell safety and high efficiency. In automotive applications, frequent load changes challenge the air supply and thermal management systems of fuel cells. In this paper, a coordination model predictive control strategy based on velocity prediction is proposed to regulate the oxygen excess ratio and stack temperature to improve the fuel cell system efficiency. First, the impact of load current, temperature and oxygen excess ratio on the efficiency is analyzed to obtain the optimal control reference. Then, the future velocity information is predicted by the long short term memory algorithm and integrated into the disturbance sequences. Optimal control trajectory obtained by collaborative optimization of the global objective function for sub-controllers. Finally, the impact of parameters on control performance is analyzed, and the effectiveness of the coordination control strategy is verified under the combined driving condition. The results show that the proposed method can reduce the oxygen excess ratio and temperature control errors by 13.8% and 4.5% compared to the control algorithm without velocity prediction. In addition, the system efficiency is increased by 1.15% due to the introduction of the optimal control reference.

Design of Water Heater Temperature Control System using PID Control

This research delves into advanced control methodologies by investigating the intricate applications of Proportional-Integral-Derivative (PID) control for achieving precise and dependable temperature regulation within electric water heaters. The study delves into various control strategies, namely Proportional, Proportional-Integral, and Proportional-Integral-Derivative methodologies, to realize the pinnacle of stable and exacting temperature control. The Proportional Controller, operating with a Kp value of 10, stands out with its relentless performance, characterized by minimal overshoot and an inconsequential steady-state error. Implementing the Proportional-Integral Controller, synergizing Kp at 10 and Ki at 5, elevates system stability while deftly curbing any hint of overshoot. The dynamic interplay between the Kp, Ki, and Kd parameters in the Proportional-Integral-Derivative (PID) Controller unveils an intricate dance of precision and control. Notably, configurations involving Kp 10, Ki 5, and Kd 2 emerge as beacons of rapid stabilization, heightened precision, and masterful overshoot management, exemplified by a rise time of 119.3543 seconds, settling time of 162.6116 seconds, overshoot of 1.0299%, peak time of 216 seconds, and a commendably low steady-state error of 0.31. This extensive exploration bears testament to its instrumental role in optimizing PID control strategies, ushering in augmented efficacy and pinpoint accuracy in water temperature regulation across an expansive spectrum of applications. As a result, these findings pave the way for the evolution of control methodologies that transcend theoretical confines and manifest within practical scenarios with profound impact.

P-286 Clinical pregnancy after blastocyst culture at a stable temperature of 36.6 °C or 37.1 °C : a prospective randomized controlled trial

Abstract Study question Is there a difference in clinical pregnancy rate after single blastocyst transfer (SET) on day 5, in case of stable culture at 36.6 °C or 37.1 °C? Summary answer Clinical pregnancy rates (CPR, heartbeat at 7 weeks) do not differ between blastocyst culture at 36.6 °C and 37.1 °C for five/six consecutive days. What is known already Since the beginning of IVF, embryo culture has been performed at 37.0 °C; however, the optimal temperature remains unknown. Changes in incubator types have led to significant improvements in temperature control. Stable temperature control, with temperature gradients of 0.1 °C among chambers, is possible in G210 incubators (K-Systems, Coopersurgical). A previous prospective trial at our centre showed that embryo development on day 5/6 was not affected when embryos were cultured at a stable temperature of 36.6 °C or 37.1 °C. Though not powered for clinical pregnancy, culture at 37.1 °C resulted in an increased CPR when compared to culture at 36.6 °C (46.4% vs. 74.2%). Study design, size, duration A prospective randomized controlled trial was performed in a tertiary fertility centre between February 2017 and December 2022. Sample size of 89/89 patients with fresh SET was required achieving 80% power to detect a difference of 0.22 between group proportions (0.43-0.65) at a significance level of 0.05 using a two-sided z-test with continuity correction. Participants/materials, setting, methods Patients were recruited the day before oocyte retrieval based on inclusion criteria (SET on day 5, fresh or frozen ejaculated sperm, female age&amp;lt;40 years, BMI&amp;lt;35m2/kg, &amp;lt;3 cycles for the current child) with final randomization after denudation once six mature oocytes were present. Primary endpoint was clinical pregnancy rate (CPR defined as heartbeat at 7 weeks); secondary endpoints were fertilization, blastocyst development, pregnancy (positive hCG), live birth rate (LBR) and cumulative live birth rate (CLBR). Main results and the role of chance A total of 304 patients were eligible for the study of whom 268 signed the consent, 234 were randomized and 181 received SET on day 5: 90 cultured at 36.6 °C and 91 at 37.1 °C. Patients were on average 32.4 ± 3.5 vs. 32.5 ± 4.2 years old, respectively. No differences were observed in embryological outcomes per cycle between both temperatures: 12.0 ± 3.8 vs. 12.1 ± 3.8 COCs retrieved (p = 0.88), 10.0 ± 3.1 vs. 9.7 ± 2.9 mature oocytes inseminated (p = 0.68) with a maturation rate of 83.2% (901/1083) vs. 81.3% (898/1104) (p = 0.87); 8.0 ± 3.1 vs. 7.9 ± 2.7 normally fertilized oocytes with a fertilization rate of 79.9% (720/901) vs. 80.0% (718/898) (p = 0.96), respectively. On average 1.5 ± 1.7 vs. 1.4 ± 1.9 (p = 0.25) and 1.1 ± 1.1 vs. 0.9 ± 1.0 (p = 0.45) blastocysts were vitrified on day 5 and day 6, respectively. Utilization rate per fertilized oocyte was 44.3% (319/720) vs. 42.1% (302/718) (p = 0.14). A single blastocyst transfer was performed for 181 patients, leading to a pregnancy rate of 72.2% (65/90) vs. 62.7% (57/91) (p = 0.17), respectively. CPR of the fresh cycle was 51.1% (46/90) vs. 48.4% (44/91) [OR (95%CI) 1.05 (0.55-1.96), p = 0.71]. To date, a CLBR of 71.1% (64/90) vs. 65.9% (60/91) (p = 0.64), was achieved respectively; with seven patients in each group with remaining blastocysts and no live birth yet. Limitations, reasons for caution Only a selected patient population with expected good prognosis was eligible for the study. Wider implications of the findings Embryos are capable to tolerate small changes in temperature deviations, demonstrated by their similar implantation potential. Trial registration number NCT03548532

Intelligent Temperature Control of a Stretch Blow Molding Machine Using Deep Reinforcement Learning

Stretch blow molding serves as the primary technique employed in the production of polyethylene terephthalate (PET) bottles. Typically, a stretch blow molding machine consists of various components, including a preform infeed system, transfer system, heating system, molding system, bottle discharge system, etc. Of particular significance is the temperature control within the heating system, which significantly influences the quality of PET bottles, especially when confronted with environmental temperature changes between morning and evening during certain seasons. The on-site operators of the stretch blow molding machine often need to adjust the infrared heating lamps in the heating system several times. The adjustment process heavily relies on the personnel’s experience, causing a production challenge for bottle manufacturers. Therefore, this paper takes the heating system of the stretch blow molding machine as the object and uses the deep reinforcement learning method to develop an intelligent approach for adjusting temperature control parameters. The proposed approach aims to address issues such as the interference of environmental temperature changes and the aging variation of infrared heating lamps. Experimental results demonstrate that the proposed approach achieves automatic adjustment of temperature control parameters during the heating process, effectively mitigating the influence of environmental temperature changes and ensuring stable control of preform surface temperature within ±2 ℃ of the target temperature.

A portable, high-throughput real-time quantitative PCR device for point-of-care testing

Nucleic acids detection has become essential in the identification of many infectious diseases and tumors. Conventional qPCR instruments are not suitable for point-of-care Moreover, current miniaturized nucleic acid detection equipment has limited throughput and multiplex detection capabilities, typically allowing the detection of a limited number of samples. Here, we present an affordable, portable, and high-throughput nucleic acid detection device for point-of-care detection. This portable device is approximately 220 × 165 × 140 mm in size and about 3 kg in weight. It can provide stable and accurate temperature control and analyze two fluorescent signals (FAM and VIC) and run 16 samples simultaneously. As a proof of concept, we used the two purified DNA samples from Bordetella pertussis and Canine parvovirus and the results showed good linearity and coefficient of variation. Moreover, this portable device can detect as low as 10 copies and has good specificity. Therefore, our device can provide advantages in real-time diagnosis of high-throughput nucleic acid detection in the field, especially for resource-limited conditions.

Experimental study on pressure-enhanced close contact melting with PCMs for stable temperature control of high heat flux electronic devices

Phase change material (PCM) demonstrates great potential for the thermal management of electronic devices. However, stable temperature control is hardly achieved because of the moving melt front during the phase change process. This study presents the pressure-enhanced close contact melting method for PCM, from the application aspect via visualization study. The overheated liquid PCM can be rapidly removed from the heat source, thus achieving stable temperature control for electronic device when operating under high heat flux. The transient performances of paraffin and low melting point alloy are evaluated, respectively, under various heat loads and pressures. It is recognized from the visualization test that the conventional PCM-based and metal foam-enhanced heat sinks fail to achieve stable temperature control since the continuously elevated liquid thickness between melt front and heat source results in increasing thermal resistance. However, the pressure-enhanced close contact melting method might continuously squeeze melted liquid, thus promoting the contact of melt front with the heat source. The effects of applied pressures and heat loads on the transient thermal management performance over time are virtually investigated. As the result, the surface temperature of heat source can be stabilized around the melting point of PCM. When applying the pressure of 2250 Pa, the thermal resistance can be minimized to lower than 10−4 K·m2·W−1. It is also noted that the thermal management performance remains unchanged when the pressure exceeds 1250 Pa.

Real-time X-ray analytical micro-furnace technique for in situ phase formation analysis during material synthesis

The monitoring of real-time reaction mechanisms can provide authentic structural information related to the prepared materials. This study reports the development of a novel real-time X-ray analytical micro-furnace (RT-XAMF) technique, which is applied during the synthesis of LiNi0.8Co0.15Al0.05O2 to monitor the phases present between 30 and 850 °C. To ensure stable temperature control during heating and ensure the practicality of the RT-XAMF technology, an insulating block was developed that allowed a small temperature tolerance of ±0.5 °C up to 1000 °C. Detailed information was gathered regarding the optimal heat treatment conditions for layered structure formation, and in the Li-excess LiNi0.8Co0.15Al0.05O2 electrode material, high charge and discharge capacities were obtained. The formation of a layered structure was monitored upon mixing various lithium salts (LiOH·H2O, Li2CO3, LiNO3, and LiF) with the Ni0.8Co0.15Al0.05(OH)2 precursor. Our results indicate that this RT-XAMF technology can be applied in the development of metal oxides and ceramic materials.

Design of the PID temperature controller for an alkaline electrolysis system with time delays

Electrolysis systems use proportional–integral–derivative (PID) temperature controllers to maintain stack temperatures around set points. However, because of heat transfer delays in electrolysis systems, the manual tuning of PID temperature controllers is time-consuming, and temperature oscillations often occur. This paper focuses on the design of the PID temperature controller for an alkaline electrolysis system to achieve fast and stable temperature control. A thermal dynamic model of an electrolysis system is established in the frequency domain for controller designs. Based on this model, the temperature stability is analysed by the root distribution, and the PID parameters are optimized considering the temperature overshoot and the settling time. The performance of the optimal PID controllers is experimentally verified. Furthermore, the simulation results show that the before-stack temperature should be used as the feedback variable for small lab-scale systems to suppress stack temperature fluctuations, and the after-stack temperature should be used for larger systems to improve the economy. This study helps ensure the temperature stability and control of electrolysis systems.