Optimal Thermal Management Research Articles

Thermal management optimization strategy for lithium-ion battery based on phase change material and fractal fin

In order to solve the problem of temperature control of lithium-ion battery (LB) in electric vehicles, a new battery thermal management system (BTMS) based on phase change material (PCM) coupled fractal fin (FF) was proposed. The effects of latent heat, thickness, and thermal conductivity of PCM (paraffin) on the thermal properties of BTMS were investigated. Subsequently, the fin structure was added to the BTMS to improve the heat transfer capacity, and the number of fins, aspect ratio, material and structure morphology were explored. The results show that when the latent heat of PCM is 200 kJ/kg, the thickness is 2 cm, and the thermal conductivity is 0.8 W/(m·K), the temperature of LB is 34.9 K lower than that of LB without the BTMS at 4C. In addition, the BTMS has the best performance when FF-II with a fin count of 5, aspect ratio of 7:1, and material of carbon steel are used. The temperatures of LB are 301.8 K, 303.9 K, 305.4 K, and 307.3 K at 1 to 4C, respectively, and the temperature difference in BTMS can be controlled within 2.5 K. This study provides some guidance for the optimization of BTMS.

Adaptive optimization of thermal energy and information management in intelligent green manufacturing process based on neural network

The study of thermal energy adaptive optimization has important theoretical and practical significance. The deep learning neural network model is used to monitor and analyze the thermal energy data in the manufacturing process in real time. Through the construction of adaptive optimization algorithm, the heat input and output are systematically evaluated and adjusted, and the heat distribution scheme is dynamically optimized according to environmental changes and production needs. At the same time, information management system is introduced to realize data summary, feedback and decision support. The experimental results show that the proposed method can effectively reduce the heat energy loss, optimize the heat energy utilization, and significantly reduce the overall energy consumption compared with traditional management methods. With real-time data updates, the system improves the flexibility and responsiveness of the production process, significantly improving manufacturing efficiency. The thermal energy adaptive optimization method based on neural network provides an effective solution for intelligent green manufacturing, which can not only optimize thermal energy management, but also provide a reference for other resource conservation and environmental protection.

Heat Transfer Modeling and Optimal Thermal Management of Electric Vehicle Battery Systems

Heat Transfer Modeling and Optimal Thermal Management of Electric Vehicle Battery Systems

Thermal management optimization of natural convection in a triangular chamber: Role of heating positions and ternary hybrid nanofluid

In this paper, we used the multi-relaxation time lattice Boltzmann method to investigate natural convection in a triangular-shaped cavity filled with a tri-hybrid nanofluid. The cavity is partially heated by a chip of fixed size (l=L/2), the position of which varies on the left and bottom walls in order to find the optimal positions. The inclined side is maintained at a cool temperature, while the other parts are adiabatic. A detailed analysis is carried out on the impact of four essential parameters on the optimization of heat transfer: the Rayleigh number, ranging between Ra = 103 and Ra = 106; the partial heating position, showing the cavity in six different configurations; the fluid type, including pure water, nanofluid, hybrid nanofluid, and tri-hybrid nanofluid; and finally, the volume concentration of the nanoparticles for three values, ϕ = 0%, 3%, and 6%. Results are presented in the form of isotherms, streamlines, temperature and velocity profiles, and the mean Nusselt number values. As the results show, the position of the partial heater plays a crucial role, influencing natural convection heat transfer significantly in certain positions at all values of the Rayleigh number. The type of fluid has a remarkable impact on the amplification of natural convection at large values of the Rayleigh number, where the buoyancy force becomes strong. Notably, the use of tri-hybrid nanofluid shows a clear improvement in natural convection heat transfer. Furthermore, a substantial increase in thermal transmittance is observed with an increasing nanoparticle volume fraction. The validation results agree well with both numerical results and experimental data published in the literature.

Tree-Inspired Aerogel Comprising Nonoxidized Graphene Flakes and Cellulose as Solar Absorber for Efficient Water Generation.

As global freshwater shortages worsen, solar steam generation (SSG) emerges as a promising, eco-friendly, and cost-effective solution for water purification. However, widespread SSG implementation requires efficient photothermal materials and solar evaporators that integrate enhanced light-to-heat conversion, rapid water transportation, and optimal thermal management. This study investigates using nonoxidized graphene flakes (NOGF) with negligible defects as photothermal materials capable of absorbing over 98% of sunlight. By combining NOGF with cellulose nanofibers (CNF) through bidirectional freeze casting, we created a vertically and radially aligned solar evaporator. The hybrid aerogel exhibited exceptional solar absorption, efficient solar-to-thermal conversion, and improved surface wettability. Inspired by tree structures, our design ensures rapid water supply while minimizing heat loss. With low NOGF content (∼10.0%), the NOGF/CNF aerogel achieves a solar steam generation rate of 2.39 kg m-2 h-1 with an energy conversion efficiency of 93.7% under 1-sun illumination, promising applications in seawater desalination and wastewater purification.

Optimization of liquid cooling plate considering coupling effects of heat generation and aging characteristics in power batteries

The heat generation and aging characteristics of power batteries exhibit a strong coupling relationship, and thus designing liquid cooling plates (LCPs) requires considering both aspects to achieve optimal thermal management. In this study, an electric-thermal-aging model (ETAM) correlating internal resistance, capacity, and temperature was developed. Based on this model, the effects of a serpentine LCP on the heat generation and aging characteristics of battery pack under different operating conditions were investigated using a combined simulation of zero-dimensional numerical model and three-dimensional CFD methods. Furthermore, the LCP channel widths in the length and width directions and the number of channels were optimized using orthogonal tests, artificial neural networks, and genetic algorithms, aiming to minimize battery capacity degradation. Results showed that increasing the mass flow rate of the coolant reduced the maximum temperature, temperature difference, capacity loss, and aging inconsistency of the battery pack. Conversely, reducing the coolant inlet temperature could decrease the maximum temperature and capacity loss but increased the temperature difference and aging inconsistency of the battery pack. The orthogonal test results indicated that the number of channels had the greatest impact on the heat generation and aging characteristics of the battery pack, followed by the channel width in the length direction, and the channel width in the width direction had the least impact. After optimization, the maximum temperature of the battery pack decreased by 0.57 %, the maximum temperature difference increased by 1.41 %, and the average capacity degradation decreased by 0.20 %. Moreover, with the increasing mass flow rate, the pressure drop reduction improved from 27.90 % to 33.90 %. This study may provide guidance for the design of LCPs that take battery aging into account.

Deep reinforcement learning based fast charging and thermal management optimization of an electric vehicle battery pack

Existing optimal strategies for fast-charging electric vehicle batteries are predominantly at the cell level. The proposed high-fidelity methods for extending available cell models to pack level are associated with a large computational burden, making real-world implementation impossible. Further, fast charging optimization and thermal management problems are dependent. That is, the cooling system reduces battery temperature, allowing for higher charging current, while optimal current minimizes the need for cooling and, in turn, reduces thermal system power consumption. There is a lack of studies where fast charging optimization and battery thermal management problems are jointly solved. Therefore, this paper proposes a simulation study using a deep reinforcement learning (RL) approach that concurrently solves fast charging and thermal management problems for a battery pack with low computational complexity. In this regard, we formulate each cell using an electro-thermal-aging model, which accounts for the heat exchange between adjacent cells. The electro-thermal-aging model plays the role of the environment for RL and is not the focus of novelty in this work. The RL agent is then trained to output the optimal charging current and coolant mass flow rate. Moreover, the proposed methodology is examined through a numerical study where the outperformance of our model is showcased by comparing it with baseline algorithms of model predictive control (MPC) and CC–CV. Consequently, three battery packs comprising 20, 444, and 7104 cells are used, respectively. We demonstrate that RL requires less than a second to finish the simulation for 20 cells, while MPC requires more than 80 min. In addition, RL keeps the cells’ core temperature below 33 °C, but MPC results reach 40 °C. The RL performance in charging packs with 444 and 7104 cells is then compared with that of CC–CV. In terms of computation time, RL and CC–CV are nearly the same, while regarding the average core and surface temperature of the cells as well as the cell aging, RL attains better outcomes, extending the battery pack’s life by up to two years after 1000 fast charging cycles.

Advanced Design and Manufacturing Approaches for Structures with Enhanced Thermal Management Performance: A Review

AbstractAdvanced design methods and manufacturing techniques are crucial for developing thermal management structures, essential for the efficient operation of complex equipment. This study provides a thorough review of design methodologies and advanced manufacturing technologies for thermal management materials and structures. It identifies key challenges and critically evaluates the integration of innovative design principles, such as biomimicry and topology optimization, into thermal management solutions. The analysis delves into the evolution of design theories and preparation techniques, with a specific focus on modern needs and research directions, particularly highlighting components fabricated using additive manufacturing and their effectiveness in meeting advanced thermal management requirements. Current research focuses on designing structures tailored to various cooling methods, including air‐cooling, liquid‐cooling, heat exchanger cooling, and heat pipe cooling. These designs utilize phase change materials, electrocaloric cooling, and thermoelectric cooling materials to achieve optimal thermal management performance. Additionally, emerging innovations like solid‐liquid mixed heat transfer and the elastocaloric effect are garnering increased interest. Enhancing the design of thermal management structures through rigorous numerical simulations is critical for improving engineering applicability. However, overcoming challenges related to the commercialization and practical utilization of these advanced structures remains a pressing need.

Multi-Layer NMPC for Battery Thermal Management Optimization Strategy of Connected Electric Vehicle Integrated With Waste Heat Recovery

Multi-Layer NMPC for Battery Thermal Management Optimization Strategy of Connected Electric Vehicle Integrated With Waste Heat Recovery

Application of ternary nanofluid and rotating cylinders in the cooling system of photovoltaic/thermoelectric generator coupled module and computational cost reduction

Innovative cooling systems and solar panel modeling approaches have become critical for effective photovoltaic module performance and higher energy efficiency. In the present study, a novel cooling system for thermoelectric generator integrated photovoltaic module is proposed. Three dimensional coupled photovoltaic module/thermoelectric generator/cooling channel system is numerically analyzed by using Galerkin weighted residual finite element method. The cooling channels include rotating circular cylinders, with ternary nanofluid serving as the cooling medium. Three dimensional coupled numerical simulations are carried out for various values of cylinder’s rotational speed (rotational Reynolds number, Rew between 0 and 5000), number of channels with rotating cylinders (N between 2 and 8), size of the cylinders in the cooling channel (RC between 0.006H and 0.433H) and nanoparticle amount in water (ϕ between 0 and 3%). Higher rotational speed of the cylinders, higher nanoparticle loading and higher channel number with cylinder contribute positively to the performance enhancement of the photovoltaic-thermoelectric generator coupled system. In the case of motionless cylinder in cooling channels, larger cylinder sizes have negative impact on the performance. By using cylinders that rotate at the fastest possible rate together with the usage of ternary nanofluid and only water, photovoltaic-cell temperature drops of 61.6 °C and 61 °C in comparison to un-cooled photovoltaic are achieved. When compared to motionless cylinder arrangements, cell temperature reductions of 4.3 °C and 3 °C are achieved by using the fastest rotation speeds for the base fluid and nanofluid. The temperature of the photovoltaic cells decreases and the thermoelectric power increases as the number of rotating cylinders in the cooling channels increases while temperature of the cell drops by 2 °C from N=2 to N=8 and becomes 4.3 °C as compared to motionless cylinder configuration. An efficient computational method by using proper orthogonal decomposition is proposed. While the computational time is reduced by a factor of 1/50, the approach is effective in properly predicting the variation in photovoltaic-cell temperature. The proposed cooling system and practical computational method are useful for further development and optimization of efficient thermal management of photovoltaic panels and integrated systems.

High thermal conductivity composite phase change material with Zn2+ metal organic gel and expanded graphite for battery thermal management

Phase change materials (PCMs) with promising potential thermal energy is stored and released much thermal energy during phase change process, which has greatly prospect in building energy conservation, waste heat recovery, energy storage, electrical vehicles (EVs) and other fields. Nevertheless, the low thermal conductivity and easy leakage of PCM is still a challenge to restrict its fasting development. Traditional supporting material is hard to reconcile antileakage and thermal conductivity of composite PCM (CPCM). Herein, the polyethylene glycol (PEG) with three-dimensional Zn2+ metal–organic gel (ZnHGL) as high-thermal conductivity support framework, styrene–butadiene–styrene block copolymer (SBS) and expanded graphite (EG) has been designed and prepared PZSE with high thermal conductivity, accompany with double transferring heat and supporting network structure. In contrast with pure PEG, the thermal conductivity of PZSE2 is increased by obvious 8.7 times when Zn2+ metal–organic gel and SBS with the proportion of 1:1, the mass maintenance rate and latent heat storage capacity are increased to 99.5 % and 103.64 J/g, respectively. Further, the thermal imaging camera indicate that PZSE2 exhibit a stable temperature-regulation property, which is benefited to extend the time to adjust the temperature. Additionally, the maximum temperature and temperature differential of the battery module with PZSE2 can be maintained within 60 °C and 6 °C, respectively, even at 1.5C discharge rate after ten cycling process. It indicates that the battery module with PZSE2 has optimum thermal management effect. Therefore, PZSE with metal–organic gel and EG can provide a promising candidate utilization in thermal regulation of EVs and energy storage.

Optimization of thermal management system architecture in hydrogen engine employing improved genetic algorithm

Decarbonization in the aeronautical industry is a daunting challenge due to the lack of sustainable aviation fuel. Hydrogen offers a potential option for this problem, given that it is an energy-dense fuel capable of reducing climate impact. Along with it, the liquid hydrogen preheating and thermal protection bring inevitable safety issues. Currently, how to construct the optimal thermal management system (TMS) architecture and further clarify its principles is still unclear. Thus, this study compares different TMS architectures through optimized genetic algorithms (GA), and firstly points out the excellent architecture as well as its operating parameters. Strikingly, our results reveal the optimized algorithm can significantly improve efficiency and precision of the optimizing processes. Benefiting from adaptive population strategy and elite preservation strategy, optimized GA saves half the time compared to conventional GA, and the variance is 60 % smaller than that of conventional GA. Using optimized GA, the series-parallel scheme is determined as the best solution and it exhibits better advantages on lightweight. In addition, results also show the leading factor is air/helium heat exchanger area. In conclusion, we hope this work can provide guidance for the optimal GA, contribute to decarbonization, and provide more ideas for the optimization of hydrogen TMS in the future.

Multiphysics-informed thermal runaway model for estimating the pressure evolution induced by the gas formation in a lithium-ion battery

This study proposes a multiphysics-informed thermal runaway (TR) model for a lithium-ion battery to replicate TR phenomena by considering the evolution of the SOC and SOH, thermodynamics, chemical reactions, pressure evolution, vent, and ejection phenomena. This versatile model contributes to estimate both temperature and pressure evolutions, and thereby understand the underlying multiphysics of TR better by deploying three key features. First, the proposed model accounts for TR dependency on the SOC and SOH of a cell by controlling kinetic parameters of positive and negative active materials. Second, simple yet accurate governing equations of vent and ejection phenomena are coupled to complex and nonlinear thermodynamics, elaborating the TR characteristics predicted by the proposed model. Third, the proposed model directly couples the chemical reactions of the five main components to predict gas formation (CO, C2H4, CO2, H2, and CH4) and evolution because the pressure evolution is initiated by different reaction ratios of these components. Quantitative experimental validation with both nickel-manganese-cobalt and lithium–iron-phosphate cells shows that the maximum error for prediction of temperature and pressure evolution is 2.2 and 14.5 % respectively, confirming the accuracy and robustness of the proposed model. This study also includes in-depth discussions for the applications of the proposed model, including the early detection of TR and gas monitoring. These insightful discussions not only reveal the effectiveness of the proposed model but also provide guidelines for optimal battery thermal management strategies.

High flame retardant composite phase change materials with triphenyl phosphate for thermal safety system of power battery module

The thermal safety of battery pack has attracted much attention accompany with the growth in electric vehicles (EVs) in recent years. Although various battery thermal management systems (BTMS) are investigated by many research, the thermal runaway propagation (TRP) of battery packs under extremely abused conditions is just at the level of structural design and theoretical model. How to explore an innovative technology to improve the integrated thermal safety including the BTMS and TRP is still a great challenge. In this study, a multifunctional flame-retardant paraffin (PA)/styrene-butadiene-styrene (SBS)/expanded graphite (EG)/methylphenyl silicone resin (MPS)/triphenyl phosphate (TPP) composite phase change material (PSEMT) has successfully prepared. Besides, it has applied in 26650 ternary power battery modules. When the proportion of MPS and TPP is 1:2, the experimental results reveal that PSEMT possesses high thermal stability, and excellent flame-retardant properties owing to synergistic flame-retardant effect with phosphorus and silicon. Further, the cylindrical 26650 battery module with PSEMT exhibits optimum thermal management performance. Even at 2C discharge rate after ten cycles, the maximum operating temperature of battery module can still be maintained below 50 °C, and the maximum temperature difference is controlled within 4.6 °C. Additionally, it displays an excellent thermal runaway suppression through triggering by multiple heat sources. What's more, the battery with PSEMT can suppress the peak temperature and delay the occurrence time of thermal runaway. Therefore, it can be induced that the battery module with PSEMT can effectively avoid heat accumulation and significantly reduce its thermal safety risk. This study offers a new solution with promising prospects from the perspectives of energy storage and EVs, for balancing the temperature inconsistencies in batteries and suppressing thermal runaway in the battery packs.

CONTEXTUALIZATION OF HISTORY AND DEVELOPMENT

The field of optical materials research stands at a pivotal juncture, driven by the relentless pursuit of advancements in laser technology. This study delves into the development and characterization of novel optical materials designed to enhance the performance and reliability of laser systems. Through a comprehensive investigation combining theoretical modeling, material synthesis, and empirical analysis, we identify key material properties that significantly influence laser efficiency and stability. Our research focuses on the exploration of new dopants, host materials, and fabrication techniques to achieve optimal thermal management, higher damage thresholds, and improved lasing efficiencies.

TECHNOLOGICAL ADVANCEMENTS IN SOLID-STATE LASERS AND FIBER LASERS

In this article through a comprehensive investigation combining theoretical modeling, material synthesis, and empirical analysis, we identify key material properties that significantly influence laser efficiency and stability. Our research focuses on the exploration of new dopants, host materials, and fabrication techniques to achieve optimal thermal management, higher damage thresholds, and improved lasing efficiencies.

Experimental CIGS technology performance under low concentration photovoltaic conditions

This research study assesses the influence of the concentration factor on two different PV technologies: c-Si and CIGS, to analyze the feasibility of utilizing CIGS thin-film technology in Low Concentration Photovoltaic conditions. Additionally, the importance of the encapsulation design is explored to determine the optimum thermal management strategy. The initial phase involves an analysis of the thermal performance of two types of commercial photovoltaic module and explores the enhancement of temperature management in CIGS photovoltaics modules by substituting the rear glass backsheet with an aluminum sheet to reduce the operating temperature of the prototype. Subsequently, various prototypes are fabricated, incorporating CIGS and silicon technologies, and different encapsulation designs: tedlar, glass and aluminum backsheets. The analysis reveals that comparing performance under 2.2× and 1× concentration conditions, CIGS technology exhibits the higher performance at 2.2×, making it a more promising choice for LCPV systems. While CIGS technology boasts an intrinsic advantage because of its open circuit voltage temperature coefficient, its performance enhancement under LCPV conditions is further amplified through the optimization of the backsheet to improve the thermal management.

Review of Thermal Management Strategies for Cylindrical Lithium-Ion Battery Packs

This paper presents a comprehensive review of the thermal management strategies employed in cylindrical lithium-ion battery packs, with a focus on enhancing performance, safety, and lifespan. Effective thermal management is critical to retain battery cycle life and mitigate safety issues such as thermal runaway. This review covers four major thermal management techniques: air cooling, liquid cooling, phase-change materials (PCM), and hybrid methods. Air-cooling strategies are analyzed for their simplicity and cost-effectiveness, while liquid-cooling systems are explored for their superior heat dissipation capabilities. Phase-change materials, with their latent heat absorption and release properties, are evaluated as potential passive cooling solutions. Additionally, hybrid methods, such as combining two or more strategies, are discussed for their synergistic effects in achieving optimal thermal management. Each strategy is assessed in terms of its thermal performance, energy efficiency, cost implications, and applicability to cylindrical lithium-ion battery packs. The paper provides valuable insights into the strengths and limitations of each technique, offering a comprehensive guide for researchers, engineers, and policymakers in the field of energy storage. The findings contribute to the ongoing efforts to develop efficient and sustainable thermal management solutions for cylindrical lithium-ion battery packs in various applications.

Research on performance test and evaluation of thermal management system of power battery module under harsh conditions

Under harsh conditions, the battery module (BM) used for Ev’s power system has issues of local overheating, continuous high temperature, and spontaneous combustion causing thermal accidents. This problem is directly related to the safety of life and property of drivers and passengers. What’s more, it also seriously restricts the high-quality development and promotion of Evs. To solve the limitations and drawbacks of the BM. this paper designs the thermal management structure with TiO2 nanofluids closed loop pulsating heat pipe (TiO2-CLPHP) as the key component and constructs the thermal management system with TiO2-CLPHP (TiO2-CLPHP TMS). On the basis, the temperature optimal thermal management strategy (TOS) and energy consumption optimal thermal management strategy (ECOS) is proposed. To investigate the performance response of TiO2-CLPHP TMS, the performance test of TiO2-CLPHP TMS is carried out. The results show that in terms of thermal management performance, the TiO2-CLPHP TMS with TOS and ECOS (TOS-TiO2-CLPHP TMS, ECOS-TiO2-CLPHP TMS) can effectively suppress the highest temperature, temperature rise and improve temperature uniformity of the PM. Of these, the minimum improvement rates of TOS-TiO2-CLPHP TMS can reach 29.41%, 78.37%, 65.88%, 58.82%, and 64.95%. The minimum improvement rates of ECOS-TiO2-CLPHP TMS can reach 27.24%, 72.65%, 64.71%, 55.88%, and 68.04%, respectively. In terms of the thermal management economy, compared with TOS-TiO2-CLPHP TMS, ECOS-TiO2-CLPHP TMS has lower energy consumption. The efficiency values of the ECOS-TiO2-CLPHP TMS are not less than 87.72%. It can be concluded that the proposed TiO2-CLPHP TMS has excellent thermal management performance. The ECOS-TiO2-CLPHP TMS can maximize the dual requirements of the thermal management performance and thermal management economy. This study innovatively proposed a thermal management method for nanofluids PHP used in BM. Compared with previous studies, the proposed TiO2-CLPHP TMS reduced the temperature difference from the traditional 5.00 °C to less than 3.40 °C, greatly improving the temperature uniformity of the BM. The completion of this research provides a new idea of battery thermal management based on metal oxide nanofluids PHP, and the constructed performance evaluation method provides a referral scheme for the performance test and evaluation of thermal management technology.

Janus polysulfone gradient hollow fiber membranes with interfacial photothermal evaporation by optimization of water transport and thermal management

Interfacial solar evaporation is a promising technology to get fresh water from seawater, because it is free of fossil fuel consumption and carbon dioxide emission. Here, a Janus gradient polysulfone hollow fiber membrane (PSF HFM) with capillary force-driven water transport and 3D evaporation performance was constructed. Different from the traditional 3D evaporation architecture, internal water transport and external water vapor are generated simultaneously. Especially, the outer surface of the membrane can also effectively absorb heat from the environment for cold evaporation because its temperature is lower than the ambient temperature. The obtained 3D PSF HFMs showed a light absorption rate of 93.7 % under simulated sunlight, and an evaporation rate of 2.51 kg·m−2·h−1 under one sun at an ambient temperature of 25 ℃. The evaporation rate of 1.6 kg·m−2·h−1 could be obtained in simulated seawater. The effect of MWCNTs on the evaporation rate was evaluated, showing that the MWCNTs with special water transport pathways were conductive to evaporation process. Overall, this work demonstrates a new direction for the future development of solar-driven evaporation.