Thermal Management Control Research Articles

Temperature management of liquid-cooled fuel cells based on active disturbance rejection control

In the proton exchange membrane fuel cell (PEMFC) systems, the operating temperature affects the gas transport, reaction rate and water balance inside the PEMFC stack, thus affecting the output performance and lifetime of the stack. Therefore, it is necessary to study the thermal management methods and control strategies to maintain the stack temperature at the expected value. A thermal management system model of the PEMFC based on the electrochemical reaction and thermodynamics is established. This study proposes a novel active disturbance rejection controller (ADRC) to solve the problem of excessive temperature fluctuation of liquid-cooled stack with the dynamic load current changes. The simulation data show that compared with the PID, Fuzzy-PID and PSO-PID controllers for the cooling fan, the overshoot amount of the coolant inlet temperature with the ADRC is significantly reduced from 1.02 %, 0.77 % and 0.26 % to 0.07 %, and the integral of time absolute error (ITAE) is decreased from 5.299 × 104, 5.206 × 104 and 1.255 × 104 to 3.930 × 103, respectively. The degree of temperature fluctuation is reduced and the parasitic power does not significantly increase. Therefore, the ADRC proposed in this study improves the temperature control effect of the PEMFC stack, which is conducive to enhancing the stack performance.

Thermal management and power generation characteristics in a bifurcating channel by using a piezo-embedded inclined elastic fin assembly during turbulent forced convection of ternary nanofluid

Numerous engineering systems use piezoelectric energy harvesters (PE-EHs), which have several benefits including low cost, simplicity, better power density, and ease of installation. They can be used in different applications for energy harvesting and different external sources such as wind and vortex induced vibrations due to fluid–structure interaction can be utilized. This study uses a unique elastic fin PE/EH assembly for power generation, thermal management, and flow control in a bifurcating channel. Performance of the system is improved by using ternary nanofluid in the channel cooling system. Galerkin weighted residual FEM with ALE is used as the solution method. The convective heat transfer performance and power generation by the EH device are investigated in relation to the varying following parameters: Reynolds number (Re between 10000 and 30000), PE-EH inclination (γ between 0 and 60), fin horizontal location (xf between −H and H), and nanoparticle loading in the base fluid (ϕ between 0 and 0.03). The vortex size and distribution near the junction are significantly influenced by the fin inclination and horizontal location of the fin assembly within the bifurcating channel. When varying other parameters of interest, using nanofluid at the highest loading results in significant deflection of the fin assembly and power generation within the PE-EH. Enhancement factors (EFs) for power generation becomes 15.6 and 39.8 when cases of lowest and highest Re are compared with pure fluid and nanofluid while they are 2.93 and 3.38 for thermal performance improvements. Fin inclination of γ=30 is found as the optimum inclination for achieving the highest power from the assembly. Higher inclination of elastic fin/PE-EH assembly results in cooling performance deterioration while average Nu reduces by a factor of 2.94 by varying inclination from γ=30 to γ=60 with nanofluid. For power generation, effects of using nanofluid with varying inclination is significant and EF becomes 252 from γ=0 to γ=30. There are opposing tendencies for the device’s power generation and cooling performance enhancement when the fin’s horizontal placement is changed. EF for average Nu is 7.25 for varying fin location. As the loading of nanoparticle inside the base fluid increases, the average Nu and generated power exhibit non-linear rising characteristics. Polynomial type correlations are provided for the average Nu and power from the device by varying elastic fin assembly inclination and nanoparticle solid volume fraction. Potential of using hybrid nanofluid in PE-EH embedded thermo-fluid system is shown. The design, development, and optimization of self-sufficient power production systems that may be used to various thermo-fluid systems, such as electronic cooling and thermal control in a range of heat transfer devices, may benefit from the findings.

Integrated battery thermal management and CO2 control in electric buses using recirculated air and waste heat recovery

In recent years, electric vehicles (EVs) have significantly progressed due to their environmental protection and energy-saving advantages. However, maintaining indoor thermal comfort and effective battery thermal management are critical considerations for EVs. Unlike conventional vehicles, EVs cannot use waste heat and depend on heat pump systems for winter heating and summer cooling. This research proposes a novel system to reduce the energy consumption of heat pump systems by using recirculated air while addressing the challenges of battery temperature management and maintaining safe CO2 concentrations in the cabin. The primary objectives of this research are threefold: first, to ensure passenger comfort through an integrated approach that includes cabin CO2 concentration safety; second, to recover heat from recirculated cabin air to save energy and control battery temperature; and third, to comprehensively analyze the performance of the Electric Vehicle Thermal Management System (EVTMS) using precise Computational Fluid Dynamics (CFD) analysis and mathematical modeling. This study will significantly enhance the understanding of energy consumption related to CO2 concentration control; an aspect previously overlooked in the literature. It will develop a battery temperature management strategy that leverages bus exhaust heat. These contributions will aid in achieving both passenger comfort and battery stability in electric buses, providing practical insights for the design and optimization of thermal management systems for future electric buses.

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.

A Predictive Model for the Growth Diameter of Mold under Different Temperatures and Relative Humidities in Indoor Environments

A substantial body of evidence suggests that indoor mold exposure is a cause of allergic and respiratory diseases in humans. While models exist for assessing the risk of mold growth on building materials, few study the characteristics of mold growth after germination. This study conducted mold growth experiments in a constant temperature chamber, using four temperature settings of 15, 20, 25 and 30 °C, and three relative humidities of 56 to 61%, 75 to 76% and 83 to 86%. A mold growth prediction model was established using temperature and relative humidity. The accuracy of the model was verified by comparing the sampling and the predicted values in a laboratory environment. The results indicated that reducing the environmental temperature and relative humidity could significantly inhibit the growth of mold, although the inhibitory effects varied. Temperature might play a more critical role. At higher temperatures (25 °C and 30 °C), the growth rate and lag time of mold tended to be consistent and there were differences in the maximum diameter. In the predictive model, the polynomial secondary model for the maximum growth rate and lag time and the Arrhenius–Davey secondary model for the maximum diameter (A) had good predictive effects (Adj.R2 > 0.850). It is speculated that temperature is the key factor affecting the maximum growth diameter of mold. The mold growth prediction model could better predict the growth of mold in actual environments without wind Adj.R2 > 0.800), but the accuracy of the model decreased under windy conditions (wind velocity < 1 m/s). The mold growth predictive model we established could be used to predict the growth characteristics of mold in windless environments. It also provides control suggestions for the regulation of temperature and relative humidity in indoor environments, supporting indoor thermal environment management and pollutant control, and ensuring indoor human health.

A thermal management control using particle swarm optimization for hybrid electric energy system of electric vehicles

A metaheuristic algorithm, Particle Swarm Optimization (PSO), was employed for developing the optimal control strategies for an innovative hybrid thermal management system (IHTMS) in a proton exchange membrane fuel cell (PEMFC)/battery electric vehicles (EVs). The goals were to shorten the period of low-efficiency temperatures during the initial startup of EVs, and to maintain temperatures of PEMFCs and batteries at their optimal-efficiency zones, where significantly enhances the traveling range and power output of EVs. Prior to simulation for benefit analysis, eight IHTMS subsystems were mathematically constructed. For the multi-input-multi-output PSO control strategy, two inputs were the fuel cell and battery coolant temperatures; while two outputs were the coolant mass flow rate and the flow rate ratio between two energy sources. A rule-based (RB) control strategy for four actuators was designed as the baseline case. Another RB using the PSO to derive the initial conditions (PSOi) was developed as well. In this research, the IHTMS was tested under two driving patterns, WLTP and NEDC, where outstanding thermal management performance was exhibited. The results demonstrate that: in WLTP driving cycle, to compare PSO and PSOi-RB with the RB strategies, the rise time of optimal temperature decreased 13.655 % and 9.505 % for the PEMFC; while 8.77 % and 4.385 % for the battery. For the NEDC driving cycle, the rise time of optimal temperature decreased 8.908 % and 7.318 % for the PEMFC, while 5.226 % and 3.136 % for the battery. The improvements of average temperature errors of the PEMFC were 19.759 % and 11.023 %; the improvements of the average temperature errors of the battery were 57.027 % and 3.67 %. For NEDC driving cycle, the improvements of average temperature errors of the PEMFC were 18.879 % and 9.551 %; the improvements of the average temperature errors of the battery were 29.144 % and 20.221 %. In the future work, the IHTMS will be integrated to a hybrid-energy EV for experimental verification.

Numerical study on the impact of geometrical parameters and employing ternary hybrid nanofluid on the hydrothermal performance of mini-channel heat sink

Thermal management and temperature control of the electrical, electronic, and electrochemical devices during their operation have always been a challenge for proper performance and further development of them. In this regard, the utilization of liquid-cooled mini-channel heat sinks (MCHSs) and improving their capability for heat dissipation have been considered an effective method in past decades. The current study aims to improve the hydrothermal performance and temperature uniformity of MCHS. To this end, several channel configurations with novel geometrical cross sections, namely basic case and cases 1–4, are designed to investigate the influence of geometrical parameters on the mini-channel performance and temperature distribution inside the heat sink. Moreover, the hydrothermal improvement of each model in comparison to the basic case is computed through a parameter, namely performance evaluation criteria (PEC). Additionally, the impact of employing water-based ternary hybrid nanofluid (THNF) containing TiO2-MgO-GO ternary hybrid nanoparticles (THNPs) with various volume fractions and shape factors (SFs) instead of distilled water in the mini-channel with optimized hydrothermal behavior is thoroughly scrutinized. the outcomes endorse that in case 3 with trapezoidal geometry and PEC parameter equal to 1.2, the Nusselt number improves by 3.2 and 1.3 times, in comparison to case 2 (lowest values of Nusselt number) and base case, at Reynolds number of 831. Also, this is observed that hydraulic diameter directly impacts the pressure drop, and by decrement of that, the pressure drop heightens. However, case 2 with a rhombus geometry results in better temperature uniformity due to its larger effective heat transfer area. Furthermore, it is observed that the volume fraction and SF of THNP significantly affect the hydrothermal behavior of THNF inside the MCHS. For instance, by employing THNF with volume fractions of 0.03 % and 0.05 %, the average heat transfer coefficient (HTC) improves by 9 % and 17 %, pressure drop increases by 220 Pa and 370 Pa, and thermal resistance reduces by 9 % and 25 %, respectively, at Reynolds number of 1496, compared to distilled water. Further, THNF with a volume fraction of 0.05 %, reduces the maximum temperature of the heat sink by 3 K in comparison to distilled water, at a Reynolds number of 831. In addition, the utilization of disparate types of THNP with various SF, including spherical (sf = 3), platelets (sf = 5.7), blades (sf = 8.6), and lamina (sf = 16.1576) is examined and disclosed with volume fraction of 0.05 % and SF of 16.1576 instead of 3, HTC roughly elevates by 67 % and thermal resistance decreases by 47 %, at a Reynolds number of 831.

Intelligent Codesign Strategy for Thermal Management and Cost Control of 3-D Integrated System With TTSV

Intelligent Codesign Strategy for Thermal Management and Cost Control of 3-D Integrated System With TTSV

Thermal rectification through the topological states of asymmetrical length armchair graphene nanoribbons heterostructures with vacancies

We present a theoretical investigation of electron heat current in asymmetrical length armchair graphene nanoribbon (AGNR) heterostructures with vacancies, focusing on the topological states (TSs). In particular, we examine the 9-7-9 AGNR heterostructures where the TSs are well-isolated from the conduction and valence subbands. This isolation effectively mitigates thermal noise of subbands arising from temperature fluctuations during charge transport. Moreover, when the TSs exhibit an orbital off-set, intriguing electron heat rectification phenomena are observed, primarily attributed to inter-TS electron Coulomb interactions. To enhance the heat rectification ratio (η Q ), we manipulate the coupling strengths between the heat sources and the TSs by introducing asymmetrical lengths in the 9-AGNRs. This approach offers control over the rectification properties, enabling significant enhancements. Additionally, we introduce vacancies strategically positioned between the heat sources and the TSs to suppress phonon heat current. This arrangement effectively reduces the overall phonon heat current, while leaving the TSs unaffected. Our findings provide valuable insights into the behavior of electron heat current in AGNR heterostructures, highlighting the role of topological states, inter-TS electron Coulomb interactions, and the impact of structural modifications such as asymmetrical lengths and vacancy positioning. These results pave the way for the design and optimization of graphene-based devices with improved thermal management and efficient control of electron heat transport.

Research on Structural Design and Optimization of Battery Thermal Management System

The quality of the thermal management control strategy of the power battery is directly related to the energy consumption and the use state of the battery. The lithium battery will generate heat in the process of charging and discharging, which will lead to its own temperature rise, and the temperature rise will affect the performance of the lithium battery. In this paper, the simulation analysis from the cell to the battery pack is carried out, and the thermal simulation analysis of the air-cooled and liquid-cooled battery pack is carried out by using different control strategies. This paper mainly analyzes the thermal simulation of three discharge rates of single lithium battery under normal temperature environment, and designs the type I liquid cooled battery pack and type S liquid cooled battery pack. By setting the same liquid cooling control strategy, the inlet temperature is 20℃, the flow rate is 1m/s, the initial temperature of the battery in normal temperature environment is 25℃, and the cooling medium is ethylene glycol (50% water and ethylene glycol mixture). Through simulation analysis and comparison of the heat dissipation effect under the three discharge ratios, the research results show that the maximum temperature of the type I liquid cooled battery pack is lower than that of the type S liquid cooled battery pack, and the effect is more significant.

Numerical Simulation on Thermoelectric Cooling of Core Power Devices in Air Conditioning

Air conditioning has become a necessity in people’s daily life. The performance of the compressor determines the energy efficiency ratio of this electrical equipment, but the heat generated during the operation of its internal core power components will greatly limit its performance release, so it is urgent to carry out research on the heat dissipation of power devices. In this work, we explore the application of thermoelectric coolers (TECs) in the field of power device heat dissipation through finite element simulation. First, we geometrically modeled the structure and typical operating conditions of core power devices in air conditioners. We compared the temperature fields in air-cooling and TEC active cooling modes for high-power-consumption power devices in a 319 K operating environment. The simulation results show that in the single air-cooling mode, the maximum temperature of the 173.8 W power device reached 394.4 K, and the average temperature reached 373.9 K, which exceeds its rated operating temperature of 368.1 K. However, the maximum and average temperature of the power device dropped to 331.8 K and 326.5 K, respectively, at an operating current of 7.5 A after adding TECs, which indicates that TEC active cooling has a significant effect on the temperature control of the power device. Furthermore, we studied the effect of the TEC working current on the temperature control effect of power devices to better understand the reliability of the TECs. The results show that TECs have a minimum working current of 5 A, which means it has no significant cooling effect when the working current is less than 5 A, and when increasing the current to 10 A, the average temperature of the power device can be reduced to 292.9 K. This study provides a meaningful exploration of the application of TECs in chip temperature control and heat dissipation, providing a new solution for chip thermal management and accurate temperature control.

Reversible Ionic Liquid Intercalation for Electrically Controlled Thermal Radiation from Graphene Devices.

Using graphene as a tunable optical material enables a series of optical devices such as switchable radar absorbers, variable infrared emissivity surfaces, or visible electrochromic devices. These devices rely on controlling the charge density on graphene with electrostatic gating or intercalation. In this paper, we studied the effect of ionic liquid intercalation on the long-term performance of optoelectronic devices operating within a broad infrared wavelength range. Our spectroscopic and thermal characterization results reveal the key limiting factors for the intercalation process and the performance of the infrared devices, such as the electrolyte ion-size asymmetry and charge distribution scheme and the effects of oxygen. Our results provide insight for the limiting mechanism for graphene applications in infrared thermal management and tunable heat signature control.

Design and test of a compact capacitor-based energy storage pulsed power module with high repetitive discharge frequency

Advance in electromagnetic launch have put forward higher requirements for the pulsed power supply(PPS). A capacitive PPS for electromagnetic launcher has been constructed in NJUST recently with a basic cell of 220kJ energy storage, which has a good scalability. Design of integrated 220kJ pulsed power unit (PFU) was demonstrated in the paper. To meet the requirement of compact structure of PPS, the device design and system layout are considered and combined with simulation to optimize the magnetic field distribution in the constrained space. In order to achieve the function of continuous discharge, the reliability of thermal management system, control system and safety protection system are focused on. System description was presented in the paper. A series of experiments were conducted to verify the performance of the module. The results show that the PFU shows good reliability in 10 consecutive burst-shot tests. Due to the modular setup of this pulse formation network, it can be extended to a larger-scale pulse forming network. Flexible current pulse shapes can be formed by controlling the charging voltage and the trigger time of the PFU.

Experimental analysis of heat and mass transfer in non-isothermal sloshing using a model-based inverse method

Nonisothermal liquid sloshing in partially filled reservoirs can significantly enhance heat and mass transfer between liquid and ullage gasses. This can result in large temperature and pressure fluctuations, producing thrust oscillations in spacecraft and challenging thermal management control systems. This work presents an experimental characterization of the thermodynamic evolution of a cylindrical reservoir undergoing sloshing-induced thermal de-stratification. We use a 0D model-based inverse method to retrieve the heat and mass transfer coefficients in planar and swirl sloshing conditions from the temperature and pressure measurements in the liquid and the ullage gas. The experiments were carried out in the SHAKESPEARE shaking table of the von Karman Institute in a cuboid quartz cell with a cylindrical cut-out of 80 mm diameter in the center, filled up to 60 mm with the cryogenic replacement fluid HFE-7200. A thermal stratification with ΔT=25 K difference between the ullage gas and liquid was set as the initial conditions. A pressure drop of 90% in the ullage gas was documented in swirling conditions. Despite its simplicity, the model could predict the system’s thermodynamic evolution once the proper transfer coefficients were derived.

Thermal management optimization strategy of electric vehicle based on dynamic programming

In order to further tap the energy saving potential of the thermal management system of pure electric vehicles and to improve the driving range under low temperature environment, a vehicle thermal management control strategy based on dynamic programming was designed. Firstly, based on the AmeSim and Simulink co-simulation platform, a refined simulation model of the vehicle thermal management system was built, including the battery system, drive system and heat pump system models. Then, a vehicle thermal management control strategy based on forward dynamic programming algorithm was proposed. By optimizing the control trajectory of compressor speed, PTC ( Positive Temperature Coefficient) power and waste heat mode, both economy and cabin comfort were improved. Finally, the simulation based on CLTC (China Light Vehicle Test Cycle) working condition verifies the effectiveness of the control strategy.

Thermal Management in Neuromorphic Materials, Devices, and Networks.

Machine learning has experienced unprecedented growth in recent years, often referred to as an "artificial intelligence revolution." Biological systems inspire the fundamental approach for this new computing paradigm: using neural networks to classify large amounts of data into sorting categories. Current machine-learning schemes implement simulated neurons and synapses on standard computers based on a von Neumann architecture. This approach is inefficient in energy consumption, and thermal management, motivating the search for hardware-based systems that imitate the brain. Here, the present state of thermal management of neuromorphic computing technology and the challenges and opportunities of the energy-efficient implementation of neuromorphic devices are considered. The main features of brain-inspired computing and quantum materials for implementing neuromorphic devices are briefly described, the brain criticality and resistive switching-based neuromorphic devices are discussed, the energy and electrical considerations for spiking-based computation are presented, the fundamental features of the brain's thermal regulation are addressed, the physical mechanisms for thermal management and thermoelectric control of materials and neuromorphic devices are analyzed, and challenges and new avenues for implementing energy-efficient computing are described.

Co-regulation of integrated thermal management based on refrigerant cooling for electric vehicles

As an essential part of an electric vehicle thermal management system, collaborative regulation of power battery thermal management and AC temperature is imperative to maximize the vehicle's driving range and energy utilization effectiveness. This work proposes a joint control pattern for the compressor (Com) and variable opening valves (VOVs) with a dual-evaporator system. Specifically, the compressor rotation speed is the dominant control variable, and the battery's thermal behavior and system COP are investigated. The analytic results demonstrate that when the system is under moderate and high thermal loads, the Com-VOVB-VOVC strategy can regulate the temperature of both the battery and AC temperature. Meanwhile, the goal of low energy consumption is optimized. Nevertheless, when the thermal load is low, the Com-VOVB strategy can attain steady temperature regulation for the dual-evaporator and decrease the complexity of the system control. In addition, a Map approach to the temperature regulation is presented, enhancing the effectiveness and dynamism of thermal management control. The common control method for an integrated thermal management system can effectively confront system thermal load changes and decrease energy consumption.

Electric Vehicle Enhanced Fast Charging Enabled by Battery Thermal Management and Model Predictive Control

This paper explores the synergy between battery thermal management (BTM) in an electric vehicle (EV) and battery charging. A model predictive control (MPC) based approach is proposed to minimize the energy used for BTM during the drive and fast charging stages and the estimated charging time while enforcing constraints imposed on state-of-charge (SOC), power, and thermal conditions of the battery. An adaptive strategy is developed to adjust the weight of the two competing objectives in the MPC cost function to manage the trade-off between BTM energy consumption and charging time. The sensitivity of the proposed MPC-based BTM strategy to uncertainties in the fast charging station availability is also investigated. Our results show that a 12.3% of decrease in the charging time could be achieved by optimally performing BTM at the cost of negligibly higher BTM energy usage in the case study conducted.

A review of thermal management of proton exchange membrane fuel cell systems

Proton exchange membrane fuel cells (PEMFCs) have the advantages of long operation cycles, high energy efficiency, and no pollution of reaction products. Temperature is an important factor to ensure the operation of fuel cell systems. Too high temperature will cause irreversible damage to the proton exchange membrane, and too low temperature will greatly reduce the power generation efficiency of fuel cells. Therefore, the effective thermal management temperature control can ensure the stable operation of the system under steady state and dynamic variable load. It can also improve the reaction efficiency of the fuel cell system and prolong the life of the fuel cell. This paper mainly summarized the cooling mode and control strategy of PEMFCs based on thermal management system. The application of different cooling methods is further discussed. The characteristics of traditional proportional-integral-derivative (PID) control, fuzzy PID control, predictive control, adaptive control, and other common thermal management control strategies were described in detail. The research status of scholars in various countries were analyzed, respectively, and the cooling effects of different strategies are compared. Through the review and research on the temperature control of PEMFCs, it is found that the stable operation of the stack is inseparable from the coordination of reasonable cooling mode and control strategy.

Thermal Management of Fuel Cells Based on Diploid Genetic Algorithm and Fuzzy PID

The operation of a proton exchange membrane fuel cell (PEMFC) is greatly affected by temperature. Reliable thermal management of fuel cells can improve the life, efficiency, and power output of fuel cells. The model established in this paper is based on the inner layer of the fuel cell, and through the analysis of the heat change and material flow between layers, the simulink model can reflect the temperature change of the end plate, the bipolar plate, and the membrane electrode assembly (MEA) plate. In terms of the thermal management control strategy, the deviation and deviation rate between the MEA plate’s temperature and the target temperature are taken as input, and the fuzzy PID (proportional integral differential) controller is used to control the cooling water flow, to achieve a cooling effect. Due to the low efficiency and instability of a haploid genetic algorithm (GA) in solving dynamic optimization problems, a diploid genetic algorithm to optimize the membership function of the controller, and improve the adaptability of the control system, was designed. The simulation results show that compared with the haploid genetic algorithm, the optimal results of 100 iterations of the fuzzy PID control strategy reduce by 27.9%. Compared with the haploid genetic algorithm and fuzzy PID control, the MEA layer temperature, under the control of a diploid genetic algorithm, is reduced by 18% and 28%, respectively, and the minimum temperature difference of the reactor is 2.28 K.