Temperature Control Strategy Research Articles

The Influence of Temperature Disturbance on Space Inertial Sensors

The TianQin program is an independently proposed space-borne detection initiative from China. The inertial sensor, as a crucial component, is susceptible to disturbances from temperature fluctuations, the impact of which on acceleration measurements remains elusive. Therefore, a comprehensive analysis on the influence of temperature disturbance is necessary to avoid errors in acceleration measurement. In this study, we proposed a complete scheme for calculating the level of acceleration noise. Based on the traditional temperature control scheme of using a heat pipe, we developed a systematic heat transfer simulation model to obtain the temperature signals. These signals can then be converted into the frequency domain and used to calculate the acceleration noise level within the target bandwidth. Our results indicate that, with a temperature control of 0.13 K/Hz1/2@1 mHz, the largest contributions to acceleration noise come from the outgassing effect, radiometer effect, and radiative pressure effect, in descending order. The total noise peak is 3.6×10−12 m/(s2⋅Hz1/2) at 1 mHz, which is more than three orders of magnitude higher than the TianQin target of 10−15 m/(s2⋅Hz1/2). This study provides new avenues for evaluating measurement errors and solutions for the TianQin program.

Internal temperature prediction and control strategy design of anode-supported solid oxide fuel cell for hot start-up process

Anode-supported solid oxide fuel cell (SOFC) has a high energy efficiency while suffering from a poor transient performance such as start-up. In this study, a model-based design method is proposed to develop a suitable strategy for the rapid hot start-up of anode-supported SOFC (AS-SOFC). First, a mathematical model is established for a 25-kW SOFC system and the internal temperature is predicted. Subsequently, three different strategies are compared during hot start-up process. The results indicate that the positive-electrolyte-negative (PEN) temperature variation magnitude is 50 K and the response time is 1300 s when the hydrogen and the air flow rates are fixed for the afterburner and the cathode. If a PID controller is employed to regulate the flow rate of H2 to the afterburner, the PEN temperature variation magnitude decreases to 16 K with a shorter response time of 158 s. When increasing the air flow rate synchronously, the PEN temperature variation magnitude is merely 8 K, reduced by 84 % and 50 % compared with the previous strategies. Additionally, the gas temperature exiting from the afterburner declines significantly for the third control strategy. Thus, the lifetime and reliability of AS-SOFC is enhanced. The results provide a reference for the SOFC systems control such as domestic combined heat and power (CHP) and mobile applications.

Experimental investigation on heat transfer characteristics and thermal optimization methods of the storage-type downhole visual tool

The storage-type downhole visual tool is a crucial device for monitoring the technical condition of the downhole tubing string. However, prolonged exposure to the high-temperature downhole environment leads to an increase in the internal temperature of the tool, causing instability in the operation of electronic devices. To address this issue, a thermal optimization scheme for the tool’s internal cavity has been proposed, combining a distributed lens structure with vacuum phase-change composite materials. An environmental-tool heat transfer model has been established to study the temperature rise characteristics during the entry stage (ES) and the operation stage (OS). Comparative analysis shows that this optimization scheme can effectively reduce the internal cavity temperature by 32.5 °C, a decrease of 41.7 %, during the entry stage. During the operation stage, the heat absorption by the composite phase-change material results in a 6.3 °C drop in the internal cavity temperature and a 30.1 °C reduction in the circuit board temperature. The model was validated through the high-temperature oil bath experiment, with the calculation results showing errors below 8 % compared to experimental results. Implementing this thermal optimization scheme in case wells ensures the tool’s continuous and stable operation for 6 h, with the internal cavity temperature maintained below 100 °C and the circuit board temperature kept within 140 °C. This significantly enhances the safety and stability of downhole electronic devices and provides guidance for the selection of temperature control strategies for downhole tools in high-temperature environments.

Research on Temperature Control of Mass Concrete for Multi-Tower Cable-Stayed Bridge Cap during Construction

In the construction process of mass concrete structures, the large temperature gradient due to exothermic hydration makes the mass concrete highly susceptible to cracking. This paper carried out research on temperature control methods of mass concrete for the purpose of ensuring construction quality based on the construction of Fengyi cable-stayed bridge caps. Firstly, the temperature and stress change rule in the concrete pouring process of the caps was analyzed though the finite element method (FEM). Then, targeted-oriented comprehensive temperature control schemes were formulated according to the structural characteristics and construction environment of the cap, including the optimization of the material ratio, the arrangement of crack-resistant reinforcing steel, the design of a water pipe cooling scheme and reasonable maintenance. Finally, the whole bridge cap construction process using the optimized water pipe cooling solution was monitored, and the temperature gap between inside and outside the concrete satisfied the specification requirements rigorously. In the concrete demolding session, the concrete surface was smooth and no cracks were found, which indicates the temperature control scheme is reasonable and effective. The research results have reference significance for the pouring and temperature control of mass concrete for bridge caps.

A Comprehensive Flow–Mass–Thermal–Electrochemical Coupling Model for a VRFB Stack and Its Application in a Stack Temperature Control Strategy

In this work, a comprehensive multi-physics electrochemical hybrid stack model is developed for a vanadium redox flow battery (VRFB) stack considering electrolyte flow, mass transport, electrochemical reactions, shunt currents, and as heat generation and transfer simultaneously. Compared with other VRFB stack models, this model is more comprehensive in considering the influence of multiple factors. Based on the established model, the electrolyte flow rate distribution across cells in the stack is investigated. The distribution and variation in shunt currents, single-cell current and single-cell voltage are analyzed. The distribution and variation in temperature and heat generation and heat transfer are also researched. It can be found that the VRFB stack temperature will exceed 40 °C when operating at 60 A and 100 mA cm−2 at an ambient temperature of 30 °C, which will lead to electrolyte ion precipitation, affecting the performance and safety of the battery. To control the stack temperature below 40 °C, a new tank cooling control strategy is proposed, and the suitable starting cooling point and the controlled temperature are specified. Compared with the common room cooling strategy, the new tank cooling strategy reduces energy consumption by 27.18% during 20 charge–discharge cycles.

Design of Oil Mist and Volatile-Organic-Compound Treatment Equipment in the Manufacturing Plant

To effectively confront the acute challenge of global warming, at the present stage, the Chinese government has designated carbon reduction as the core objective to accomplish the coordinated control of greenhouse gas and pollutant emissions. As China is a major manufacturing country, with the continuous improvement of air emission standards, it is particularly necessary to carry out the design of more efficient volatile organic pollutant emission devices. This study takes a treatment system with a waste gas ventilation volume of 6 × 104 m3·h−1 as an example, adopts the end treatment approach of adsorption and catalytic combustion coupling, and designs a purification device composed of multistage oil-mist recovery, electrostatic adsorption, dry filtration, activated-carbon adsorption and desorption, catalytic combustion, etc. It also employs the fuzzy proportional-integral-derivative fine temperature control algorithm, and the temperature overshoot was decreased by 85%. The average emission concentration of volatile organic compounds at the equipment outlet is 6.56 mg·m−3, and the average removal rate is 93.99%, far surpassing the national emission standards. The device operates efficiently and stably, confirming that the end-coupled treatment system based on the adaptive fuzzy proportional-integral-derivative temperature control strategy can effectively handle volatile organic compounds with oil mist and holds significant promotion and research value.

Modeling the Effects of Temperature in Enzymatic Biodiesel Synthesis of Jatropha Oil: An Optimal Control Approach.

Biodiesel, an alternative to diesel, is produced through the enzymatic transesterification of vegetable oil or animal fats. Enzymatic transesterification of oil is gaining more importance, as this method possesses no such disadvantages that are associated with the chemical process. Temperature is the most important factor in enzymatic transesterification for biodiesel synthesis. In this study, a mathematical model is developed to understand the effects of temperature on the enzymatic transesterification of Jatropha curcas oil. Reaction rates are expressed as a function of temperature using an appropriate function, and the effects of temperature on the overall enzymatic system are investigated using the mathematical model. A suitable temperature is determined using the mathematical model, keeping the other reaction conditions unchanged that gives maximum yield. Furthermore, an optimal control problem (OCP) is formulated to identify the temperature control strategy that maximizes the biodiesel yield while minimizing production costs. Simulated outcomes obtained from the mathematical model are analogized with the experimental results to make them acceptable. The optimal profile of temperature is determined from the developed OCP, which maximizes the biodiesel yield.

Optimization for the temperature range of radiator for preventing draught risk of cold window

High surface temperature of radiator can provide thermal plume with enough momentum intensity and thus counteracts the downdraft caused by window. Meanwhile, it is necessary to avoid causing indoor temperature to exceed upper limit of thermal comfort zone. In this paper, influence of heat transfer coefficients of window and exterior wall, outdoor temperature, and average surface temperature of radiator on operative temperature (Top) and temperature difference between indoor air and window (Td) was investigated. Based on response surface method, single factor and interaction effects for the four influencing factors on Top and Td were analyzed. A framework optimizing average surface temperature of radiator for preventing draught risk of window was established. When the heat transfer coefficient of window was around 1.4 W/m2·°C and satisfied related energy-conservation standard, cold draught could be eliminated without causing indoor environment overheating. Based on the optimized temperature range, the supply water temperature was controlled, and seasonal performance using the variable temperature strategy was investigated based on TRNSYS simulation. With the variable water temperature control strategy, the output hourly indoor air temperature was within the comfortable range. In the whole heating season, hours that did not meet cold draught requirement occupied 77.22 %, as the heat transfer coefficients of window dis-satisfied the energy-saving design standard. As meeting the design standard, the proportion decreased to 12.97 %. Utilizing the optimized temperature interval can prevent discomfort caused by cold draught to the greatest extent. This study is conducive to improving thermal environment with the convective–heating system and may lead to the reduction of energy consumption for heating.

The impact of induction heating time on the temperature distribution of high-temperature alloy discs

Abstract The induction heating time is directly related to the temperature uniformity of high-temperature alloy disc components. Therefore, investigating the influence of induction heating time on the temperature field distribution of disc components provides guidance for temperature control strategies in the forming process. In this study, the finite element analysis software COMSOL Multiphysics was employed to examine the impact of induction heating time on the radial and thickness-wise temperature fields of GH4169 discs. The results indicate that the heating time affects the thickness of the heating layer, and appropriately extending the heating time can improve the temperature uniformity in the thickness direction, achieving a temperature difference of ±5 °C in the disc component thickness direction under certain conditions. When the heating time ranges from 1229 s to 1239 s, the temperature in the R=30 mm to R=100 mm range reaches the suitable forging temperature.

Distributed Cooperative Dispatch Method of Distribution Network with District Heat Network and Battery Energy Storage System Considering Flexible Regulation Capability

Flexible resources, including district heat networks (DHN) and battery energy storage systems (BESS), can provide flexible regulation capability for distribution networks (DN), thereby increasing the absorption capacity for renewable energy. In order to improve the operation economy of DN and ensure the information privacy of different operators, a distributed cooperative dispatch method of DN with DHN and BESS considering flexible regulation capability is proposed. First, a distributed cooperative dispatch framework of DN-DHN-BESS is constructed. Then, an optimal dispatch model of DHN under constant flow-variable temperature control strategy is established in order to utilize the heat storage capacity to provide flexible regulation capability for DN. Next, the optimal dispatch models of BESS and DN are established with the objective of minimizing the operation cost, respectively. Finally, a solution method based on the alternating direction multiplier method of distributed cooperative dispatch for DN-DHN-BESS is proposed. Case studies are performed on a system consisting of a 33-node DN and a 44-node DHN, and simulation results demonstrate that the proposed method differs from the centralized dispatch method by only 0.52% in the total system cost, and the proposed method reduces the total system cost by 34.5% compared to that of the independent dispatch method.

Efficient 3D temperature field prediction and visualization for AFP process analysis in composite structures

AbstractProcess modeling is an indispensable tool for establishing a foundation for process optimization and enhancing the quality of products. Analyzing the thermoforming process of polymer matrix composites presupposes the acquisition of accurate thermal histories. This paper introduces a numerical solution based on the finite difference (FD) model to predict the temperature field of angle‐ply composite structures during automated fiber placement (AFP) process along the machining trajectory. The proposed method incorporates three‐dimensional hybrid boundary conditions and considers temperature‐dependent material properties, significantly improving efficiency compared to the finite element (FE) model and overcoming challenges related to complex boundary conditions and anisotropic heat transfer in analytical solutions. Real‐time temperature measurement experiments were conducted to validate predictions, and further a specific temperature control strategy that meets process requirements was explored. In summary, the paper introduces a novel approach to address the temperature field in complex composite structure manufacturing processes.Highlights A novel 3D finite difference model predicts the temperature field in automated fiber placement. Improved prediction accuracy by managing complex boundary conditions. Effectively handled anisotropic heat transfer in complex composite structures. Superior efficiency over existing numerical methods. Developed a model‐based strategy for optimal temperature control within ±5°C.

Large-scale energy cost optimization and performance analysis for dedicated outdoor air system: simulation results from ASHRAE RP-1865

This is the first journal article from the ASHRAE research project RP 1865, “Optimizing Supply Air Temperature Control for Dedicated Outdoor Air Systems,” focusing on the large-scale energy performance evaluation of the optimal control of dedicated outdoor air systems (DOAS). DOAS is a type of air handling system that is installed in buildings to ensure proper ventilation for the built environment. It is acknowledged that DOAS with proper operation strategies can provide sufficient ventilation and dehumidification while achieving energy efficiency. In this regard, there have been efforts to develop advanced control sequences (e.g., optimal control) for DOAS. Still, limited studies have demonstrated the effectiveness of such DOAS controls on a larger scale under varying climate zones with different DOAS configurations. To fill the research gap, this study aims to quantify the energy-saving potentials of applying an optimal supply air temperature (SAT) control strategy for DOAS considering diverse configurations of HVAC systems in various climate conditions across the United States. For this study, we first developed a total of 180 EnergyPlus models accommodating different types of buildings (i.e., detailed medium-sized office and primary school) and HVAC systems (i.e., DOAS types, DOAS sizes, and terminal units) under varying ASHRAE climate zones (i.e., 2A, 3B, 4A, 4C, 6A, and 6B). Next, genetic algorithm (GA)-based optimizations were conducted to determine the optimal DOAS SAT control that would minimize the energy cost of the entire HVAC system operation. Our study of comparing the optimal control to a typical rule-based control (i.e., outdoor air temperature-based reset control) revealed approximately 4–34% of energy cost saving potential by optimizing the DOAS SAT control sequence.

Influence of cooling bed temperature on microstructural, mechanical properties and surface quality of high-strength seismic-resistant rebar

High-strength seismic-resistant rebar is essential in construction engineering, yet balancing its strength, plasticity, seismic resistance, and surface quality poses challenges. This research explores niobium-vanadium-nitrogen composite reinforced steel, examining how cooling bed temperature affects its microstructure, mechanical properties, and surface quality using advanced microscopy techniques. The research reveals that the steel's microstructure primarily consists of ferrite and pearlite. As cooling bed temperatures decrease, both the proportion and colony size of pearlite, along with ferrite size, show a declining trend. Specifically, reducing the cooling bed temperature from 1100 °C to 900 °C results in a decrease in yield strength, tensile strength, and tensile-to-yield strength ratio by 6 MPa, 27 MPa, and 0.03, respectively. Meanwhile, elongation after fracture, total elongation at maximum force, and strength-ductility balance improve by 3.8%, 1.5%, and 1.93%, respectively. At a cooling bed temperature of 1100 °C, significant blistering occurs on the steel surface. Significant blistering at 1100 °C vanishes at 1000 °C and 900 °C, with diminished silicon enrichment in the surface oxide scale. A cooling bed temperature of 1000 °C ± 20 °C is recommended for optimal performance. This study provides a temperature control strategy for the properties of high-strength seismic-resistant rebar rated at 650 MPa and above, contributing valuable insights to the field of advanced construction materials.

Temperature Control and Crack Prevention of High RCC Dam in Cold and Drought Area

A development process is introduced for a computation program to calculate the temperature and stress field of mass concrete based on the ANSYS® platform. The temperature control scheme of a high roller compacted concrete (RCC) dam in northern Xinjiang is optimized by using the simulation program. It is suggested that the concrete pouring temperature of the dam should not exceed 16°C and that water-pipe cooling should be adopted. The dam should be permanently heat preserved by 10 cm thick extruded polystyrene (XPS) extruded panels, and the top surface of the overwintering layer should be covered with an at least 14 cm thick thermal insulation quilt. During construction, the warehouse surface should be temporarily insulated with a 2 cm thick thermal insulation quilt. The causes of cracks in a particular dam section are simulated and analysed, and it is concluded that the cracks are mainly caused by the lack of thermal insulation of the warehouse surface during cold spells.

Lipid production from corn straw by cellobiohydrolase and delta-6 desaturase engineered Mucor circinelloides strains under solid state fermentation

Previously, we constructed engineered M. circinelloides strains that can not only utilize cellulose, but also increase the yield of γ-linolenic acid (GLA). In the present study, an in-depth analysis of lipid accumulation by engineered M. circinelloides strains using corn straw was to be explored. When a two-stage temperature control strategy was adopted with adding 1.5% cellulase and 15% inoculum, the engineered strains led to increases in the lipid yield (up to 1.56 g per 100 g dry medium) and GLA yield (up to 274 mg per 100 g dry medium) of 1.8- and 2.3-fold, respectively, compared with the control strain. This study proved the engineered M. circinelloides strains, especially for Mc-C2PD6, possess advantages in using corn straw to produce GLA. This work provided a reference for transformation from agricultural cellulosic waste to functional lipid in one step, which might play a positive role in promoting the sustainable development of biological industry.

Optimization of methanol yield and carbon dioxide utilization in methanol synthesis process

The method of CO2 hydrogenation to methanol can effectively reduce carbon emission and has wide application prospects in chemical industry and environment. Therefore, methanol synthesis is an important way to save energy, reduce emission and transform energy utilization. In this paper, the mathematical model of methanol synthesis reactor is established. Under the condition of controllable cooling temperature, the optimization is carried out with maximum methanol yield and CO2 utilization rate. The results show that the methanol yield can be increased by 6.57% and CO2 utilization rate can be increased to 39.1% by adjusting the cooling temperature control strategy. The comparative study found that the optimal cooling temperatures all show up and down variations, with local minima and maxima. In addition, an industrial application method of methanol yield maximization cooling strategy is proposed. When the stage cooling at different temperatures is adopted, the methanol yield could be increased by 5.38%.

Application of an improved simulated annealing algorithm in satellite network routing

Abstract Satellite communication is integral to modern communication systems, yet navigating the intricacies of routing in networks characterized by high loads and dynamic evolution poses a significant challenge. This research is dedicated to enhancing satellite communication routing algorithms, with the goal of bolstering network efficiency and amplifying the success rate of business transmissions. Our approach introduces an improved simulated annealing algorithm incorporating adaptive temperature control and innovative path neighborhood exploration strategies. This novel algorithm is adept at adjusting to ever-shifting network topologies and meeting various business requirements. Our simulation results reveal that this refined algorithm outperforms traditional annealing methods in several critical aspects. It elevates the success rate of business transmissions, reduces the average number of forwardings by 6.546% across various load scenarios, and diminishes system response time by 15.05%, thereby marking a substantial improvement in network performance.

Energy Saving Research on Temperature Control in Data Center Server Rooms

Abstract To tackle the challenge of inefficient traditional control methods and energy wastage caused by temperature disparities within the data center’s server room cooling system, this research initiative initially installed temperature and humidity sensors in each cabinet to gather comprehensive data. Subsequently, a detailed mathematical model of the room’s temperature system was formulated to assess the influence of air supply airflow distribution on the temperature distribution. Following this, through the integration of fuzzy theory with the PID control strategy, a sophisticated fuzzy PID controller was developed. Utilizing Simulink, an in-depth simulation analysis of both PID and fuzzy PID temperature control strategies was executed. The outcomes of the simulations underscored that fuzzy PID control effectively addresses the time delay and stability concerns present in conventional PID temperature control systems. Lastly, empirical validation confirmed that the fuzzy PID control algorithm can proficiently manage the server room’s temperature while concurrently decreasing the intake of cold air, thus promoting energy conservation. This control approach showcases commendable adaptability and robust performance characteristics.

A Precise Temperature Control Method for Lithium-ion Battery Pack based on the Nonlinear Model Predictive Control Algorithm

Abstract To utilize the maximum performance of the battery while ensuring its thermal safety, a battery thermal management system is used to control the battery maximum temperature within a safe range. This paper centres on the establishment of a temperature prediction model and the development of the nonlinear-based model predictive control (MPC) strategy. First, to address the need of predicting battery temperature, this paper develops a distributed parameter thermal resistance model to predict battery temperature quickly and accurately. Secondly, the open-loop formulation of the nonlinear-based MPC is derived based on the established state space equations. Then the soft and hard constraints of the model are established based on the actual current conditions, pump conditions, temperature difference and temperature rise indexes, so as to establish the objective function of the MPC algorithm. Finally, the established temperature nonlinear MPC algorithm is embedded on the board and the hardware platform of battery liquid cooling system is established. The experiment test result shows that the maximum error of temperature control is less than 0.1°C, and the effectiveness of the temperature control strategy of lithium-ion battery is verified through experiments.

Fuzzy-based thermal management control analysis of vehicle air conditioning system

Automotive air conditioning (ACC) system designers faced unique challenges in satisfying customer demands for efficient and comfortable operation across a broad temperature range. The AAC system's effective or fixed temperature setting makes this possible. Many climate control models, like the state flow switching controller in MATLAB control, must handle heating and cooling due to a single Simulink/environment software and frequently contain steady-state error (SSE). The present research proposes to design an automatic temperature control scheme and fuzzy logic control (FLC) for an automotive air-conditioned (AAC) system. In addition, it employs MATLAB Simulink/environment software to model the fuzzy control technique to analyze the AAC system's response. A simulation has been set up to evaluate the suggested system performance to match a selection of user-specified reference temperatures and compressor speeds. Compared with a PID-controlled AAC system, the proposed FLC-based system reduced the undershoot to only 2.30% from 33.30% respectively, and was robust, quicker, and better at controlling temperature.