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The hybrid fuel cell/battery technology is an attractive option for a sustainable mobility with zero emissions. In fact, this solution owns system scalability features and high efficiency and, compared to battery electric solutions, it offers advantages in terms of flexibility of use and fast charging times. However, the thermal management for the battery in this type of powertrain is a crucial issue, since operating temperatures can significantly affect safety and performance. In this study, an innovative system aimed at providing high storage energy density and improving the battery pack performance of hybrid fuel cell/battery vehicles is investigated for use on-board of a plug-in fuel cell electric bike. The proposed system, developed by the authors in previous studies, integrates the battery pack with a hydrogen storage based on metal hydrides. The idea behind this solution is to exploit the endothermic desorption processes of hydrogen in metal hydrides to cool down the battery pack during operation. An experimental analysis is conducted to assess the thermal management capabilities of this system: by considering a typical duty cycle designed on the base of road test measurements, battery pack temperature profiles are evaluated and compared against those from a control experiment where no battery thermal management is enabled (i.e. no hydrogen desorption from the metal hydride tank). The results show that, beside enhancing the on-board stored energy capacity, the proposed system represents an effective solution to provide an efficient thermal management for the battery pack, with significant advantages in terms of attainable riding range. • Plug-in fuel cell electric bicycle with greater riding range than e-bike. • On-board storage system integrating metal hydrides tank and battery pack. • Enhanced volumetric and gravimetric on-board energy storage density. • Optimal thermal management of battery pack and metal hydride tank. [ABSTRACT FROM AUTHOR]

Application of refrigerant-cooled multi-channel evaporators (MCEs) is a promising solution to cool electric vehicle batteries because the non-uniformly distributed heat from a battery can be efficiently dissipated by suitable arrangement of the multi-channels in an MCE. In order to provide a simulation tool for the design of an MCE, a distributed parameter model for quickly predicting the performance of an MCE at various channel arrangements and non-uniformly distributed heating conditions is useful, and thus it is developed in this study. In the model, heat and mass transfer in multiple flow paths in an MCE are separately described; the uneven mass flow distribution among these channels is predicted based on the pressure balance; each flow path is divided into multiple control volumes to reflect the non-uniformly distributed heating conditions; and the mass flow distribution among flow paths and the heat transfer in all the control volumes are jointly solved by a combined iteration algorithm of pressure drop and heat transfer. The proposed model is validated by experiments under the condition of battery heat flux ranging from 500 to 1500 W m−2. The results show that the prediction deviations of the average temperature and the highest temperature on the MCE surface from the experimental ones are 1.5 °C and 1.6 °C, respectively, which indicates that the proposed model can well predict the thermal performance of MCE under non-uniformly distributed battery heat. • A distributed parameter model of refrigerant-cooled MCE for power battery is developed. • Refrigerant flow among multi-channels is modeled as uneven flow with fix direction. • Arbitrary heat flux input can be calculated by the model. • The average deviation of temperature predictions is less than 3.0 °C. [ABSTRACT FROM AUTHOR]

The in-depth research on the heat exchanger for lithium-ion batteries is of significant importance due to its crucial role in ensuring the safe operation of electric vehicle (EV) power systems. To enhance the thermal and flow characteristic of the heat exchangers, the novel heat exchangers for 18650-cylinderical lithium-ion batteries have been proposed by topology optimization with the minimization of pressure drop and the lowest average temperature (∏ 1) and the minimization of pressure drop and the lowest temperature difference (∏ 2) as two different optimal goals. The topology optimization based on the variable density method is utilized to get two-dimensional (2D) optimal channels, and then the optimized results are extended to three-dimensional (3D) heat exchangers. The 3D heat exchangers are named TOHE-1 which is gotten by stretching the topology channels with ∏ 1 as optimal goal and TOHE-2 which is gotten by that with ∏ 2 as optimal goal. Subsequently, a detailed thermodynamic analysis is performed to assess the effect of the type of heat exchangers, channel heights, weight factor of topology optimization function, mass flow rates and discharge rates on the cooling effect of the batteries. The results show that compared with the traditional channel heat exchangers, the heat transfer coefficient of topological heat exchangers have increased by 49.92%, while reducing pressure drop by 27.81%. Meanwhile, compared to TOHE-1, heat transfer coefficient of TOHE-2 is increased by 9.70%, while pressure drop is saved by 4.70%. Other studies have indicated that for a 4 C discharge of the battery, a topological heat exchanger with a channel height of 1.5 mm, a thermal performance weight factor of 0.1, and a mass flow with 3.3 × 10−3 kg s−1 is the optimum heat dissipation scheme. Finally, the numerical studies are verified by conducting the convective heat transfer experimental tests. [Display omitted] • The topology optimization heat dissipation scheme for cylindrical lithium batteries is proposed. • The performance of topological heat exchangers is studied numerically and verified experimentally. • The performance of different functional types of topological heat exchangers is compared. • The ratio of heat dissipation scheme to battery weight is considered in cooling scheme design. [ABSTRACT FROM AUTHOR]

• Design for hybrid battery pack with high energy density and high safety. • Thermal Management Optimization Layout Design for Hybrid Battery Packs. • The P2D model is used to study electrochemical properties of single battery. • Multiphysics coupling analysis of electro-thermal behavior. • The SOC estimation method for hybrid battery pack. As traditional battery systems, lithium iron phosphate (LFP) batteries have better safety but lower energy density and nickel manganese cobalt oxide (NMC) batteries have higher energy density but poorer safety. In this work, we design a hybrid battery pack that has both higher energy density and higher battery safety. By analyzing the thermal properties of battery packs with aligned, staggered, and staggered arrangements, it can be concluded that the aligned arrangement has superior cooling efficiency and space-efficient optimization compared to the other arrangements, which have shorter flow paths to minimize air energy loss and reduce pressure drop. Notably, we design the optimal arrangement to avoid placing the NMC cells near the air outlet, to avoid NMC concentration, and to decentralize the LFP cells to reduce the relatively high maximum temperature and temperature difference. This hybrid battery pack is expected to give a boost to lithium-ion battery applications. [ABSTRACT FROM AUTHOR]

To maintain the optimal operating temperature range for the power batteries of new energy vehicles, this paper proposes a novel tree-structured channel cold plate. An orthogonal experimental approach was employed to investigate the effects of inlet flow rate m, inlet channel quantity n, channel width d, and hierarchy ratio α on battery temperatures T max , standard temperature difference T σ , and pressure drop Δ P. Non-dominated sorting genetic algorithm II (NSGA-II) was utilized to obtain an optimized solution set. The results reveal that the tree-like cold plate configuration including m = 15 g/s, n = 7 and 8, d = 3 mm, and α = 1:2:1 demonstrates superior performance. Thus, the developed cold plate was further compared with the conventional straight-through cold plate design. The results indicate that the proposed tree-like cold plate exhibits the maximum decreases of 13.94% in T max , 52.94% in T σ , and 61.5% in Δ P. The most significant improvement in the composite indicator PEC was 89%. In conclusion, the tree-like channel cold plate developed in this study provides excellent heat dissipation capability for power batteries, offering valuable insights for the thermal design of battery liquid cooling systems. [ABSTRACT FROM AUTHOR]

• The heat generation model for cylindrical Li-ion battery was built. • A liquid immersion cooling battery pack containing 60 batteries were established. • At 2C discharge rate, 0.5 L/min flow rate was recommended. • The battery pack can address localized high-rate discharge events (4.5C or 6.5C). • Liquid immersion cooling BTMSs have great heat dissipation performance. With the increasingly severe challenges of the thermal management of battery packs for electric vehicles, the liquid immersion cooling technology has gradually attracted more attention due to its superior characteristics such as high heat dissipation efficiency, well temperature uniformity and low risk of thermal runaway. To investigate the heat transfer characteristics of the liquid immersion cooling BTMSs, the 3D model of the 60-cell immersion cooling battery pack was established, and a well-established heat generation model that leveraged parameters derived from theoretical analysis and experiments was incorporated into the 3D simulation to analyze the thermal characteristics of battery pack. The simulation results showed that under the discharging rate of 2C, even with the lowest coolant flow rate in this work (0.2 L/min), no localized abnormal overheating within the battery pack was observed, and the highest temperature was 34.22 °C. The temperature uniformity within the battery pack improved with the increase of the coolant flow rate. It was recommended to maintain a flow rate above 0.5 L/min to ensure a temperature difference below 5 °C. The experimental apparatus of the immersion cooling battery pack was also developed to explore the heat dissipation and temperature uniformity at 2C discharge rate. The simulation results were in well agreement with the experimental results, with the deviation less than 0.43 °C when the flow rate exceeded 0.6 L/min. The effect of the localized high-rate discharge events (4.5C and 6.5C) at different battery pack locations on temperature distribution and uniformity was further discussed based on the verified 3D model. The results suggested that liquid immersion cooling systems offered promising potential for achieving both efficient heat dissipation and preventing thermal runaway in battery packs. [ABSTRACT FROM AUTHOR]

This study introduces a streamlined modeling framework that integrates a volume-averaged thermal (VAT) model with the Tank-in-Series battery model, a recently developed volume-averaged electrochemical model. The framework enables efficient simulations of electrochemical-thermal interactions in large-scale battery packs. This framework is used to investigate the effects of coolant flow rates and inlet temperature, initial and ambient temperatures, battery pack configurations, and cell-to-cell manufacturing related variations. Results showed a notable current distribution variation among modules connected in parallel at the end of discharge and beginning of charge. This is found to be directly related to the temperature variation in the battery pack governed by the coolant mass flow rate. Additionally, with the introduction of a 0.5% cell-to-cell to variation in the cell design parameters for the purpose of simulating manufacturing variation, a significant voltage variation of over 0.2 V across cells is found to be possible. Furthermore, rapidly changing the inlet temperatures to simulate a potential battery management system failure indicated the risk of some cells in the pack exceeding the desired cut-off voltage. The present framework can be used to design battery packs with effective thermal management strategies, enhancing the overall reliability and performance of battery systems. • Developed a multiphysics modeling framework to simulate electrochemical-thermal characteristics of Li-ion battery packs • Flexible, scalable, and efficient physics-based simulation of Li-ion battery packs • In-depth analysis of Li-ion battery pack at various operating conditions, including extreme thermal conditions • Effect of cell-to-cell manufacturing variation on cell-level and pack-level electrochemical and thermal characteristics [ABSTRACT FROM AUTHOR]

• The coupled BTMS with PCMs and cold plates is designed for performance improvement. • Aerogel is used to replace the unmelted PCMs for weight reduction. • A strategy is developed to optimize the distribution of PCMs/Aerogel. • T max and Δ T are reduced by 1 K and 49 % respectively after the optimization. • The weight of PCMs/Aerogel is reduced by 45 % after the optimization. The thermal management system is critical for battery packs in electrical vehicles. Coupling the battery thermal management system (BTMS) with phase change materials (PCMs) and cold plates (CPs) has demonstrated good cooling performance. However, part of the PCMs inside the existing systems doesn't experience phase change, which contribute less to the cooling performance as the weight load increases. In this study, aerogel as the typical lightweight flame retardant materials (FRMs) is adopted to replace the un-melted PCMs to reduce the weight of the system. An optimization strategy for the distribution of PCMs/FRMs in the coupled BTMS is proposed to improve the cooling performance with the system's volume fixed. By locating PCMs on the high-temperature area, an optimized system can be obtained by taking just a few adjusting steps using the developed strategy. After the optimization, the maximum temperature and temperature difference inside the battery pack are reduced by1.0 K and 49% respectively, with the weight of the filling materials among battery cells decreasing by 45%. The proposed strategy shows great potential for efficient optimization of coupled BTMSs with phase change materials and cold plates, which can improve the cooling and lightweight performance of the system simultaneously. [ABSTRACT FROM AUTHOR]

The era of electric mobility has started, and petrol/diesel vehicles are being replaced by electric vehicles (EVs). The phase change material (PCM) is a trending field of research in its application of energy storage and thermal management. PCM-based thermal management method is found to be quite simple and effective for battery packs. However, its commercialization is difficult due to its low thermal conductivity and extra weight addition to the battery pack. Hence, the present research focuses on the battery performance with PCM. The experimental setup for a 48V, 25Ah battery pack is developed, and its performance is explored with and without PCM. The numerical model for same sized battery pack is developed, and validated with experimental results. The major objective of the present research is to find the optimal gap between two battery cells so that a sufficient amount of PCM can be filled inside the battery pack. Initially, inline and staggered cell arrangements are examined, and no significant difference in thermal performance is found. Further, cell spacing of 5 mm, 3 mm, and 1 mm are examined, and maximum temperature and temperature difference are compared along with the weight and volume of the battery pack. For a single charging process, 1 mm cell spacing is found sufficient, considering the weight of the battery pack and thermal performance. However, with 1 mm cell spacing, temperature increases significantly after each charging and discharging. At the same time, 3 mm and 5 mm are found as feasible solutions considering single and double charging-discharging cycles, respectively. 3 mm cell spacing is better option when weight is a critical issue, while 5 mm cell spacing is better when thermal performance is a critical issue. The current study offers guidance in the advancement of battery packs, particularly in cases where space constraints are a concern. • The research focuses on utilization of optimal amount of PCM. • The battery charging experiments are carried out on 48V, 25Ah battery pack. • PCM OM42 reduced battery temperature by 18 %. • The inline and staggered arrangements are found equally effective. • 3 mm cell spacing is found sufficient with limited weight increment. [ABSTRACT FROM AUTHOR]

A powerful thermal management scheme is the key to realizing the extremely fast charging of battery electric vehicles. In this scheme, a water-cooled plate is set at the bottom of the battery modules, which has a remarkable heat dissipation ability but increases the temperature difference between the top and bottom of the battery. This temperature difference problem is more obvious during the high-rate charge/discharge process; in particular, in the area of battery tabs, which are usually located far from the cooling plate, heat accumulates, risking thermal runaway. To address this problem, a thermal management method based on an ultrathin vapour chamber (UTVC) is proposed in this paper to improve temperature uniformity and reduce the highest temperature of batteries. According to the number of applied UTVCs, a unilateral UTVC (U-UTVC) and a bilateral UTVC (B-UTVC) cooling approach were presented, the effectiveness of which was verified by a set of thermal performance experiments. The test data show that the temperature differences in the batteries under the U-UTVC and B-UTVC schemes are 39.77% and 73.54% lower than those under the traditional method at a 25 °C ambient temperature and a 1.39C charge rate, respectively. The temperature difference on the battery surface with the B-UTVC scheme is approximately 3 °C at 25 °C and 40 °C ambient temperature. • An ultra-thin vapour chamber-based power battery thermal management is proposed to improve the temperature uniformity. • The methods have limited effect on battery volumetric specific energy, and the volumetric specific energy of battery is only reduced by 1.2% which is far less than reported investigations. • Temperature difference and maximum temperature of battery module of the presented scheme are reduced by 15.49% and 73.54%, respectively. [ABSTRACT FROM AUTHOR]

For cylindrical Li-ion battery packs, the battery thermal management system can be properly designed and analyzed from an energy-exergy viewpoint during charging and discharging to ensure the proper functionality of batteries; however, not been explored yet. Hence, cylindrical Li-ion battery pack with novel-designed serpentine microchannel-cooled thermal management system are analyzed. Applying the Multi-Scale Multi-Domain Newman, Tiedemann, Gu, and Kim model, an electrochemical model is used for the 3D battery thermal modeling. Effects of circular and rectangular cross-sectional shaped microchannels and using ternary hybrid nanofluids [THNF1 (Al 2 O 3 (0.5%) + Cu (0.5%) + MWCNT (1%)/water) and THNF2 (Al 2 O 3 (0.5%) + Cu (0.5%) + Graphene (1%)/water] are investigated at a 3C-discharge rate. Results indicate that the use of ternary hybrid nanofluid and microchannel cross-sectional shape has a strong influence. Maximum temperature, temperature uniformity, pumping power, heat transfer coefficient to pressure drop ratio, and entropy generation are the key factors. The present simulation can predict individual battery thermal behavior during charging and discharging. The suggested design successfully lowers the cell temperature to 305.24 K by using THNF2 and the temperature difference to 5.23 K of the 26,650-type cylindrical cell. Rectangular cross-sectioned microchannel is found to be more effective. The thermal control of batteries is greatly enhanced by using ternary hybrid nanofluid. The suggested technique will improve the battery life. • Novel serpentine microchannel-cooled system is proposed for cylindrical battery pack. • Multi-Scale Multi-Domain Newman, Tiedemann, Gu and Kim model is used for battery. • Different microchannel cross-sections and ternary hybrid nanofluids are investigated. • Thermal performance parameters, pressure drop and entropy generation are evaluated. • Suggested design and fluid successfully keep cell temperature within desired range. [ABSTRACT FROM AUTHOR]

• An improved FRN model is developed for variable cross-section air-cooled BTMSs. • An efficient method based on FRN model is proposed for design of deflector shape. • The optimized BTMS outperformed those using the previous optimization methods. • Experiments are carried out to verify the effectiveness of the optimization method. Air-cooled systems are widely used for cooling of battery packs in electric vehicles. Optimization method combined with the flow resistance network (FRN) model is effective for system design. However, the local pressure loss of divergence and convergence ducts in the traditional FRN model is ignored, leading to large error when applying the model in systems with variable cross-section channels. In this study, the local loss coefficients of the contractive and diffusive channels are derived and the improved FRN model is developed for velocity calculation of variable cross-section air-cooled systems. The improved model is verified using computational fluid dynamics method. Based on the improved FRN model, the cross-section width distribution of the divergence duct is calculated from the given flow rate distribution. The shape of the divergence deflector is optimized by adjusting the flow rate distribution and using the improved model. The results indicate that the temperature difference of the battery cells decreases by more than 84% after the optimization, with the maximum temperature decreasing by more than 3.8 K. Furthermore, the optimized system performs better than those in the previous studies. Also, experiments are carried out to verify the effectiveness of the developed optimization method based on the improved FRN model. [ABSTRACT FROM AUTHOR]

The current study proposed a heat pipe (HP)-assisted hybrid fin (HF) for inter-cell cooling in a battery thermal management system (BTMS). Its thermal performance was comprehensively investigated under extreme thermal conditions of up to 50 W along with critical variables. A numerical model for the proposed HF-BTMS was developed using the finite difference method and integrated with a performance prediction model based on an artificial neural network. After successfully validating with experimental results, the developed numerical model was intensely used for module-level thermal analysis and multivariate optimization. The proposed HF-BTMS exhibited a better thermal performance, which was experimentally verified by the reduction in the maximum temperature and deviation by 5.4 and 3.8 °C, respectively, than the BTMS with conventional plain fin (PF). The multivariate optimization indicated that the optimized performances of the HF-BTMS were all within the desired temperature ranges. The condensation lengths are known to be most influential rather than other variables related to coolant operating conditions. Finally, under the most thermally harsh condition, compared to PF-BTMS, the HF-BTMS was found out to dramatically reduce the maximum temperature and temperature deviation of the BTMS by over 17.95 °C and 16.37 °C, successfully maintaining within the safety range. [ABSTRACT FROM AUTHOR]

The heat dissipation performance of batteries is crucial for electric vehicles, and unreasonable thermal management strategies may lead to reduced battery efficiency and safety issues. Therefore, this paper proposed an optimization strategy for battery thermal management systems (BTMS) based on linear time-varying model predictive control (LTMPC). To begin, based on the results of three-dimensional thermal flow analysis, a reduced order substitution model for the battery cooling system was established. Next, to address the issue of high computational complexity caused by the nonlinear model in the controller, a linearization method based on staged control was designed. Furthermore, the control parameters were optimized using the particle swarm optimization algorithm. Finally, a BTMS physical model based on SIMSCAPE was established for performance simulation. The performance of the logic threshold controller (LTC), linear model predictive controller (LMPC), and nonlinear model predictive controller (NMPC) was compared and analyzed. LTMPC was found to reduce the average temperature of the battery by up to 2.33 °C and 1.90 °C, and the cumulative temperature difference is reduced by 13.9% and 16.6% compared to LTC and NMPC, respectively. Compared to LMPC, LTMPC reduces thermal management energy consumption by 21.2%. • A complete mathematical model of the liquid cooling cycle circuit was derived through the order reduction method. • Reasonably incorporate future information into the controller to improve robustness of system. • Adopting a staged control strategy to segment the model, establishing a linear time-varying control model, greatly improving computational efficiency. • The upper controller uses the heat exchange between the coolant and the air conditioning system as the control variable, improving control efficiency. • The combination of particle swarm optimization algorithm and pareto curve fully exploits the optimization potential of parameters. [ABSTRACT FROM AUTHOR]

• A computationally efficient model for large-scale battery packs is developed. • Parameters are devised to evaluate the structural designs for the battery pack. • Pros and cons of the alternative structural designs are analyzed. • Interspersed battery pack design is suggested to enhance the thermal performance. In this paper, a comparative study for structural design of battery thermal management system is presented for electric vehicles. A thermal model for the pouch battery pack with liquid cooling is developed for thermal analysis of various pack designs. Typical battery pack with fin-cooling structure is set as a reference design, and thermal behavior of the battery pack is examined in the aspect of cooling performance and temperature uniformity. Numerical results indicate that poor heat conductivity from the bottom of the cell stack to the cooling plate is one of the major barriers to the efficient heat dissipation and asymmetric design of fin-cell arrangement have negative effect on the temperature uniformity of the battery pack. To improve the performance of the thermal management system, various structural designs are suggested and evaluated based on plural criteria. A new structural design for the large-scale battery pack is suggested to enhance the cooling performance and temperature uniformity of the battery pack minimizing the increase in system volume, weight, and pressure drop. [ABSTRACT FROM AUTHOR]

The objective of this study is numerically to investigate the heat transfer characteristics of the integrated heating system considering the temperature of cabin and battery of an electric vehicle under the cold weather conditions. The integrated heating system consists of a burner to combust fuel, an integrated heat exchanger for CHE (coolant heat exchanger) and AHE (air heat exchanger). The heat transfer characteristics like the overall heat exchanger effectiveness, the heat transfer rate, the temperature distribution and the fluid flow characteristics like the pressure drop, velocity distribution of the investigated integrated heating system were considered and analyzed by varying the inlet mass flow rates and the inlet temperatures of the cold air and water, respectively. The average Nusselt numbers for the cold air side and the water side were increased 28.4% and 9.5%, respectively, with the increase of the cold air side Reynolds numbers from 15,677 to 72,664 and the water side Reynolds numbers from 4330 to 11,912. The numerical results showed good agreement within ±9.0% of the existed data and thus confirmed that the present model was valid. In addition, the proposed integrated heating system could be used as the thermal management of the cabin and the battery system of the electric vehicle under the cold weather conditions. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are commonly used in hybrid electric and full electric vehicles (HEV and EV). In HEV, thermal management is a strict requirement to control the batteries temperature within an optimal range in order to enhance performance, safety, reduce cost, and prolong the batteries lifetime. The optimum design of a thermal management system depends on the thermo-electrochemical behavior of the batteries, operating conditions, and weight and volume constraints. The aim of this study is to investigate the effects of various operating and design parameters on the thermal performance of a battery module consisted of six building block cells. An electrochemical-thermal model coupled to conjugate heat transfer and fluid dynamics simulations is used to assess the effectiveness of two indirect liquid thermal management approaches under the FUDC driving cycle. In this study, a novel pseudo 3D electrochemical-thermal model of the battery is used. It is found that the cooling plate thickness has a significant effect on the maximum and gradient of temperature in the module. Increasing the Reynolds number decreases the average temperature but at the expense of temperature uniformity. The results show that double channel cooling system has a lower maximum temperature and more uniform temperature distribution compared to a single channel cooling system. [ABSTRACT FROM AUTHOR]

While the air conditioning system provides a comfortable thermal environment for vehicle occupants, it is also one of the most energy-intensive auxiliary devices in modern vehicles. Meanwhile, the operating characteristic of the battery system significantly impacts the economic and safety performance of the vehicle. To improve the energy efficiency of plug-in fuel cell electric vehicles, this paper proposes a collaborative energy management strategy based on the soft actor-critic algorithm, considering battery thermal management and cabin thermal comfort management. First, the soft actor-critic algorithm is implemented in energy management research for fuel cell electric vehicles. Second, by establishing a control-oriented vehicle-integrated thermal management model and adopting a novel air conditioning system design, the coordinated optimization of the battery thermal management and cabin thermal comfort management is achieved. Finally, the collaborative energy management strategy based on the soft actor-critic algorithm is presented to minimize the total operating cost, while maintaining the optimal battery temperature range and cabin thermal comfort. The online testing results demonstrate that the implemented energy management strategy based on the soft actor-critic algorithm can achieve 96.06% fuel economy of the dynamic programming benchmark methodology, while significantly improving computational efficiency. Moreover, the proposed collaborative energy management strategy can effectively improve the overall vehicle fuel economy, manage the battery temperature within the optimal operating range, and maintain cabin thermal comfort. However, with the prolonged operation of the air conditioning system, the total operating cost of the vehicle increases considerably, up to 28.12% or even more, indicating that it is a highly energy-consuming component. • The control-oriented vehicle-integrated thermal management model is established. • A novel air conditioning system design is adopted in the control framework. • A collaborative energy management strategy is developed based on soft actor-critic. • The optimization performance of the proposed scheme is comprehensively analyzed. [ABSTRACT FROM AUTHOR]

Conventional cooling approaches that target either a singular tab or outer surface of common format cylindrical lithium-ion battery cells suffer from a high cell thermal resistance. Under an aggressive duty cycle, this resistance can result in the formation of large in-cell temperature gradients and high hot spot temperatures, which are known to accelerate ageing and further reduce performance. In this paper, a novel approach to internal thermal management of cylindrical battery cells to lower the thermal resistance for heat transport through the inside of the cell is investigated. The effectiveness of the proposed method is analysed for two common cylindrical formats when subject to highly aggressive electrical loading conditions representative of a high performance electric vehicle (EV) and hybrid electric vehicle (HEV). A mathematical model that captures the dominant thermal properties of the cylindrical cell is created and validated using experimental data. Results from the extensive simulation study indicate that the internal cooling strategy can reduce the cell thermal resistance by up to 67.8 ± 1.4% relative to single tab cooling, and can emulate the performance of a more complex pack-level double tab cooling approach whilst targeting cooling at a single tab. [ABSTRACT FROM AUTHOR]

Thermal management of electric vehicles, especially battery thermal management, is critical to driving range and operational safety. To find a vehicle thermal management system with higher energy efficiency and environmental protection, an environmentally-friendly and efficient battery and cabin parallel cooling thermal management system was evaluated with CO 2 as the working fluid. First, different control strategies of the evaporation temperature were compared regarding the battery cooling performance. Then, the effect of the battery cooling evaporation temperature on the coefficient of performance (COP) was explored. It was found that the maximum COP increased by 8.38% as the evaporation temperature decreased from 17 to 5.8 °C. Besides, it was found that the optimal battery cooling evaporation temperature range is 10.2–11 °C when the battery heating power is 0.4 kW. The vapor quality at the cold plate outlet should be lower than 0.95. Finally, the battery cooling performance under variable operating conditions was investigated. The influence of operating parameters on the battery cooling evaporation temperature and CO 2 outlet vapor quality was also analyzed. Simulation results showed that the optimum evaporation temperature range varied significantly under different working conditions. The vapor quality at the cold plate outlet decreased slightly with the evaporation temperature. • A transcritical CO 2 battery direct cooling thermal management cycle is studied. • The temperature distribution characteristics of the battery surface are revealed. • The effects of CO 2 temperature and vapor quality on performance are researched. • Suggestions on optimal CO 2 temperature and vapor quality in BTM control are given. [ABSTRACT FROM AUTHOR]

The exposure of electric vehicle batteries to rapid charging and discharging profiles, particularly under uncertainty in the drive schedules, requires effective strategies to forecast and avoid thermal excursions during operation. In this work, we present a light gradient boosting-based machine learning model to create probabilistic forecasts of the discharge current over a forecast horizon in real time. A surrogate of a physics-based computational model provides the functional relationship for the battery temperature, using which a stochastic model-predictive control strategy is developed to derive the optimal cooling schedule based on the probabilistic forecast. The effectiveness of the stochastic model-predictive control approach is assessed on the US06 driving cycle, in comparison to a constant coolant flow and persistence forecast-based control. It is shown that the total number of temperature excursion instances using the stochastic model-predictive control is reduced by about 69% compared to the constant coolant flow case and by over 51% compared to persistence-forecast-based control. Further, the total coolant usage is reduced by about 73% compared to persistence forecast-based control. The stochastic model-predictive control approach provides more flexibility by allowing a wider range of control and battery pack design parameters to obtain optimal performance with minimum coolant use. • Presents model-predictive thermal control of LIBs under drive cycle uncertainty. • Probabilistic forecast of discharge current obtained using machine learning model. • Uses physics-based computational model to derive optimal cooling schedule. • Stochastic model-predictive control approach is assessed on US06 drive cycle. • Reduces temperature excursion instances by ∼ 69% and coolant usage by ∼ 73%. [ABSTRACT FROM AUTHOR]

• Thermal performance of refrigerant-based battery thermal management system for a real HEV battery pack is analyzed. • Effect of battery discharging C-rate, refrigerant mass flow rate, inlet temperature, vapor quality, and heating power on thermal performance of battery pack is studied. • Thermal performance of battery pack at real driving cycle operational conditions for refrigerant cooling is discussed. • Heat flow distribution on the battery pack at different discharging C-rates is analyzed. The thermal performance of refrigerant-based battery thermal management system (BTMS) for a real HEV battery pack in both the cooling and heating conditions is numerically and experimentally investigated in this paper. The heat generation model of battery cells and the numerical methodology for predicting the cooling performance of refrigerant-based cooling system are validated by experiments and the predicted results are consistent with experimental data. The effects of discharging C-rate, mass flow rate, initial temperature and vapor quality of refrigerant on thermal performance of battery pack are analyzed in detail. The thermal performance of refrigerant-based BTMS at a real driving cycle is also examined. The results indicate that the discharging C-rate has a significant impact on thermal performance of battery pack due to the distinctive heat transfer behaviors of battery pack at different discharging C-rates. Increasing mass flow rate of refrigerant is contributed to descend the maximum temperature and improve temperature uniformity of battery pack. Decreasing initial temperature of refrigerant is beneficial to reducing the maximum temperature of battery pack but is disadvantageous to temperature uniformity. The effect of vapor quality on thermal performance of battery pack is limited. The cooling performance of refrigerant satisfies the requirement of BTMS at the real driving cycle. The optimum heating power of the battery pack at heating condition ranges from 400 W to 460 W. [ABSTRACT FROM AUTHOR]

This paper provides a methodology to assess the average surface temperature of battery cells under realistic transient scenarios. Computational fluid dynamics modelling of battery cooling is conducted for the cases exposed to the ramps of internal heat generation inferred from the standard driving cycles. The results are then post-processed to determine the effectiveness of air and water as the coolant fluids. A quantitative measure of the maximum overshoot, dimensionless settling (DST), heating (DHT), and cooling (DCT) time is subsequently presented. It is shown that, compared to water, air produces a considerably delayed response to temporal changes in the internal heat generation and is slower at reaching the new steady state condition. Cooling battery cells by using water almost always ensures remaining within the safe operating range. Nonetheless, regardless of the coolant type, the long period ramps tend to produce smaller values of DST. The primary origin of the delay is the slow heat conduction within the battery cells. In addition, it is shown that water responds to changes in the internal heat generation far quicker during the heating and the cooling phases. The study highlights the importance of transient analyses for characterising the thermal behaviour of battery packs. • A novel measure of battery heat release due to internal heat generation is presented. • Transient cases with sharp gradients cause large delays in system response. • Air cases always produce an overshoot and are far slower at reaching steady state. • Battery cells remain within the safe operating range in almost all water cases. • Water cases react far quicker to changes in the internal heat generation. [ABSTRACT FROM AUTHOR]

• A novel design for BTMS is proposed to separate the propagation of thermal runaway. • Th BTMS unites phase change cooling, liquid cooling and thermal insulation material. • The electrochemical-thermal and heat transfer-laminar flow coupling model is built. • The influence of coolant flow rate on the novel BTMS in the extreme case is analyzed. Nowadays, electric vehicles attract much attention due to the advantages of low energy consumption and zero emission. As the power source of electric vehicles, the safe and stable operation of lithium ion battery is very important. However, owing to overcharge, mechanical collision, overheating or other conditions, the battery may occur thermal runaway, which can cause serious accidents such as fire or explosion. To solve this problem, an efficient and energy-saving battery thermal management system becomes a necessary choice. In this paper, a novel integrated battery thermal management system with multi-measure prevention strategy is designed and analyzed, which is mainly composed of the composite phase change material, aerogel and cooling-channel. Firstly, the electrochemical-thermal coupling mathematical model is established, and then the reliabilities of thermal runaway model, phase change cooling model and liquid cooling model are verified, respectively. Next the numerical simulation including the effect of different operating modes, extreme case and coolant flow rate on the battery thermal management system is carried out, and finally the results are discussed in detail. The results show that the battery thermal management system can not only quickly take away the accumulated heat and separate the propagation of thermal runaway, but also maintain the temperature uniformity of battery. [Display omitted] [ABSTRACT FROM AUTHOR]

Mini channeled cold plates (MCCP) are an impressive choice for electric vehicles with a liquid-based thermal management system to keep the battery temperature within the desired range and to achieve a homogeneous temperature distribution. This paper came up with an optimum solution for maximum battery temperature (MBT), maximum temperature difference on the battery surface (MTD) and pressure drops in the channels (ΔP), which are vital parameters. Multi-objective optimization of geometric parameters and coolant flow rate of a designed MCCP which is experimentally investigated is carried out using the Desirability Function Approach. Firstly, the design of experiments (DoE) is generated using response surface method after determining the input variables and their levels. Then, each sample of DoE are modeled and analyzed numerically. Furthermore, the regression equations of the objective functions (MBT, MTD and ΔP) depending on the design parameters are developed and their variance analyzes are performed. Prediction accuracies of model equations developed for MBT, MTD and ΔP are 97.75%, 95.49% and 97.15%, respectively. As a result, optimum values of design variables, namely channel width (mm), distance between branches (mm), channel depth (mm), number of crossovers in branches and coolant flow rate (l/min) are 5, 5, 10, 13 and 0.7061, respectively. • Multi-objective optimization of a mini channeled cold plate. • Simulation of temperature distribution on the battery surface for different cases. • Deriving regression equations for the optimization output variables. • Achieving a minimum prediction accuracy rate of 95.49% for the response parameters. [ABSTRACT FROM AUTHOR]

Liquid-cooled battery thermal management system with cold plate shows great potential for cooling battery packs in electric vehicles due to its merits of large heat transfer coefficient and good sealing performance. However, current design of cold plate leads to large temperature difference in battery packs, especially in the case with large battery packs. Besides, the pump energy consumption is usually high, which shortens the endurance of electric vehicles. In this paper, a parallel mini-channel cold plate (PMCP) for large battery packs is designed to reduce the temperature difference of the system. Numerical method is adopted to evaluate the performance of the PMCP, which is further demonstrated by experiment. Then a bidirectional symmetrical cold plate is designed to reduce both temperature difference and energy consumption. Positions of the outlets of the bidirectional symmetrical cold plates are adjusted to further improve the system performance. Finally, the designed cold plates are used for cooling large battery packs. Compared with systems equipped with traditional PMCP, the temperature difference in battery pack and the energy consumption of the system with designed PMCP are reduced by 77% and 82%, which shows that the designed PMCP significantly improves the system cooling and energy saving performance. • PMCP is used to cool large-scale battery packs at a high discharge rate. • Experiments are done to study the PMCP performance and verify the numerical method. • Performance of PMCP is improved by constructing bidirectional symmetrical system. • Influence of the outlet position on the performance of designed PMCP is studied. • Δ T avg-b and W P of designed BTMS are reduced by at least 76% and 81%, respectively. [ABSTRACT FROM AUTHOR]

• Lithium-ion battery module and thermal management interactions were simulated. • The system was thermally managed using fuel. • A comparative analysis was performed for verification and assessment. • N-heptane fuel was found as a feasible coolant in hybrid electric vehicle batteries. Battery thermal management system (BTMS) design is crucial for its performance, which can be associated with extra costs and system complexity. Most of the current studies are focused on the BTMS design but with a little focus on the improvement of coolants. In this work, the feasibility of using combustion engine fuel for the LIB thermal management of hybrid electric vehicles is investigated. N-heptane is used as a dielectric hydrocarbon coolant in the introduced system. The thermal performance of the proposed system is investigated numerically using the CFD software ANSYS-Fluent. To benchmark and validate the system performance, a comparative study is made among other common approaches, including the use of air and 3M-Novec 7200. A variety of input parameters are accounted for, including inlet velocities and discharge rates. The results show that air cooling is the least effective method to control the battery module temperature uniformity and the Li-ion battery safety limit. At the same time, n-heptane and 3M-Novec 7200 have shown good control of the module temperature range (20 °C–40 °C) at various discharge rates and different inlet velocities. However, using n-heptane is a considerable improvement to the cost of the system and reduction in its weight and maximum temperature, compared to that using 3M-Novec 7200 coolant. For instance, at 0.1 m · s - 1 , n-heptane has reduced the Li-ion battery maximum temperature at 1 C and 2 C discharge rates by more than 7.9 °C (2.6%) and 17.9 °C (5.65%), respectively, compared to those predicted using the same battery module without cooling. [ABSTRACT FROM AUTHOR]

• Design of a liquid cooling system for EV batteries based on the constructal law • Canopy-to-canopy architectures prove to have high thermal efficiency • They allow to maintain the battery cell below the critical temperature level With the growing interest on electric vehicles comes the question of the thermal management of their battery pack. In this work, we propose a thermally efficient solution consisting in inserting between the cells a liquid cooling system based on constructal canopy-to-canopy architectures. In such systems, the cooling fluid is driven from a trunk channel to perpendicular branches that make the tree canopy. An opposite tree collects the liquid in such a way that the two trees match canopy-to-canopy. The configuration of the cooling solution is predicted following the constructal methodology, leading to the choice of the hydraulic diameter ratios. We show that such configurations allow extracting most of the non-uniformly generated heat by the battery cell during the discharging phase, while using a small mass flow rate. [ABSTRACT FROM AUTHOR]

As the temperature has a great effect on the cycle life and capacity of power battery on electric vehicles (EVs), a practical battery thermal management (BTM) strategy is required to adjust the battery temperature within an appropriate range and reduce the temperature inconsistency in the battery module. To achieve the multiple objectives, a nonlinear model predictive control (NMPC) method is proposed to optimize the cooling process of battery module. Firstly, a lumped thermal model of single lithium-ion battery under air cooling is presented, which considers the change of internal resistance with temperature and the change of heat transfer coefficient with coolant velocity. Considering the temperature inconsistency in the battery module, a thermal model of the battery module is derived based on the law of conservation of energy and verified. Due to the nonlinearity, time-varying parameters and multiple constraints of the thermal management system, the NMPC method is designed. Particle swarm optimization is used to solve the nonlinear programming problem in NMPC method. The simulation results show that the NMPC method ensures that the battery works near the target temperature under different working conditions, the deviation is less than 0.5 K, and the temperature inconsistency in the battery module is less than 1.2 K. In addition, compared with the PID method, the air flow consumption is effectively reduced. • A lumped thermal model considering inconsistency of battery module is established. • Nonlinear model predictive control is used for battery cooling and energy reduction. • Particle Swarm Optimization is used as NMPC solver to reduce the calculation burden. [ABSTRACT FROM AUTHOR]

The battery thermal management system (BTMS) is important to ensure the lithium-ion battery life, performance, and safety. A novel inclined U-shaped flat microheat pipe array (FMHPA) is used for BTMS to achieve high efficiency and space-saving in this study. The thermal control performance is experimentally studied and compared with the module without FMHPAs. Results show that the equivalent thermal conductivity of the inclined U-shaped FMHPA is approximately 4350 W m−1 K−1, and plays the role of core heat transfer element. The maximum temperature and temperature difference of the module with FMHPAs are reduced by 16% and 60%, respectively, compared with those of the module without FMHPAs; FMHPAs keep the module in a suitable temperature range for most of the time in the ambient temperature of 25 °C during the 1C charge–2C discharge cycle. Moreover, the temperature difference at cell and module level are maintained within 5 °C in ambient temperature of 25 °C and 40 °C. The heating rate of the module with FMHPAs reaches 0.61 °C/min under the temperature difference of less than 5 °C; variable power heating (from large to small) will increase the temperature rise rate of the battery by 0.19 °C/min. • Inclined U-shaped flat microheat pipe array is used in battery module. • The module with inclined U-shaped FMHPAs is compact in structure and saves space. • The separation of the coolant and batteries improves safety. • Module is kept in suitable temperature in 1C charge–2 C discharge cycle. • Temperature difference at cell and module level are maintained within 5 °C. [ABSTRACT FROM AUTHOR]

• Liquid cooling of pouch type li-ion batteries with multi-stage Tesla valve proposed • Channel geometry, coolant properties optimized numerically from COMSOL simulation • Forward and reverse flow configuration across the multi-stage Tesla valve explored • An enhanced heat transfer in the reverse flow observed at the cost of pressure drop • Maximum cold plate temperature noted within 40°C for Re varying from 2500 to 4750 The operating temperature can significantly influence the performance, cycle life, and safety of Li-ion batteries used in electric vehicles. One of the critical factors is to assess the temperature distribution within the battery pack when operated under extreme conditions and choosing an appropriate cooling method. Concerning this, a liquid cooling plate comprising Tesla valve configuration with high recognition in microfluidic applications is proposed to provide a safer temperature range for pouch type Li-ion batteries. A multi-stage Tesla valve with forward and reverse flow configuration is designed and analysed to improve a conventional rectangular channel's intrinsic temperature gradient issues for turbulent flow conditions. Moreover, the influence of various parameters such as channel number, the distance between two consecutive valves, coolant temperature, and heat flux applied on the cold plate's top and bottom surfaces are numerically investigated for varying Reynold's number using COMSOL Multiphysics software. An enhancement in heat transfer with the reverse flow in multi-stage Tesla valve is seen, mainly caused by flow bifurcation and mixing mechanisms, at the cost of pressure drop. A cold plate with 4 channels and valve to valve distance of 8.82 mm exhibits the most effective cooling performance. [ABSTRACT FROM AUTHOR]

In this paper, the coupling system of liquid-cooled battery thermal management system (BTMS) and heat pump air conditioning system (HPACS) for battery electric vehicles (BEV) is designed and analyzed. The performances of liquid-cooled BTMS are concerned and analyzed from the perspective of air conditioning based experimental data. Besides, an automatic calibration model of the liquid-cooled BTMS based HPACS is established to predict cooling capacity and system coefficient of performance (COP) of the BTMS by support vector regression (SVR). To better obtain three hyper parameters (the penalty coefficient C , the RBF kernel function parameter γ , and the insensitive loss coefficient ε) of SVR model, particle swarm optimization (PSO) algorithm is introduced to optimize above three parameters. It is found that compared to SVR model, the correlation coefficient (R) of cooling capacity and system COP for the proposed PSO-SVR model in this paper is improved 2.1% and 2.8% respectively, the mean squared error (MSE) of and cooling capacity and system COP is reduced 87.8% and 82.9% respectively, which indicated that PSO-SVR model can be used as a new method to fit the complex nonlinear relationship among the system COP, cooling capacity and other influencing factors of the liquid-cooled BTMS based HPACS. • Comprehensive analysis from the perspective of air conditioning system. • Automatic calibration model for battery thermal management system. • The battery thermal performance estimation based on the SVR model. • SVR model with RBF kernel exhibits better generalization ability. [ABSTRACT FROM AUTHOR]

Air-cooled battery thermal management system (BTMS) is universally adopted in electric vehicles for temperature control of battery packs. In the present study, we develop an efficient transient model for accurately predicting the battery cell temperature in different types of parallel air-cooled BTMSs. A flow resistance network model for BTMS with I-type flow is established according to law of momentum conservation. Based on energy equations, a transient heat transfer model is derived to calculate the temperature distribution of battery pack in the BTMSs. The model results are in good agreement with experimental data, verifying the effectiveness and efficiency of this model. The deviations of T max and Δ T max between the models and experiment are less than 1.5 K. Furthermore, by using the developed transient models, the deviations of T max and Δ T max respectively decrease by 70% and 26%, in comparison with previous study. Finally, based on the developed models, the widths of parallel channels and divergence/convergence ducts in the BTMSs are designed, leading to remarkably enhanced cooling performance. The present study provides an efficient transient heat transfer model for parallel cooling systems, which can provide a deeper insight into the system performance and be applied to structural optimization of the systems. • A flow resistance network model for BTMS with I-type flow is developed.. • A transient heat transfer model for parallel BTMSs is derived mathematically. • Experiments are conducted to verify the developed transient heat transfer model. • The optimized BTMSs based on the developed models achieve good performance. [ABSTRACT FROM AUTHOR]

• A novel liquid cooling plate embedded with PCM for battery thermal management. • The cooling plate provides a modular solution for battery cooling with PCM. • The cooling plate is 36% lighter than an aluminum cooling plate of the same size. • Up to 30% reduction in pump energy consumption is achieved by the new cooling plate. • The cooling plate provides a heating solution for batteries in cold temperatures. In this paper, an innovative liquid cooling plate (LCP) embedded with phase change material (PCM) is designed for electric vehicle (EV) battery thermal management. The proposed cooling plate is named "hybrid cooling plate" as it takes advantage of both active (liquid) and passive (PCM) cooling methods. The hybrid LCP is 36% lighter than a volumetrically equivalent traditional aluminum LCP, and in addition to the cooling capability, it provides a heating solution to slow the temperature loss of the batteries during the cold stop. The thermal behavior of the hybrid LCP for two different scenarios including the cooling performance under a real driving cycle, and the cold stop temperature performance are investigated and compared with a traditional aluminum LCP using a computational fluid dynamics (CFD) model. An experimental test bench is developed to test a prototype of the hybrid LCP and verify the CFD model. The cooling performance results indicate that the use of hybrid LCP could reduce the energy consumption of the pump required for circulating the coolant up to 30% in comparison with an aluminum LCP. Moreover, the novel designed LCP improves the temperature uniformity effectively. It was also found that the hybrid LCP could significantly delay the temperature drop at the cold stop situation of the EV and therefore, reduce the energy needed for the active heating of the batteries after short-term parking. These imply that the hybrid liquid cooling plate concept could be a promising thermal management solution for EVs. [ABSTRACT FROM AUTHOR]

• The heat generation and transfer modeling approaches of LIB are introduced. • The advantages and disadvantages on various multi-physical BTMS are summarized. • The emerging techniques in emergency battery thermal barrier are examined. • A novel BTMS framework is proposed based on CHAIN. New energy vehicles have significant prospects in reducing greenhouse gas emission and environmental pollution. Lithium-ion batteries are the favored power source in electric vehicles because of their high energy density and long service life. The battery performance depends noticeably on the temperature. Battery thermal management system, which can keep the battery pack working in a proper temperature range, not only affects significantly the battery pack system performance but is also vital for the safety and stability. This article mainly summarizes the thermal management models in the literature which can predict heat generation, heat transfer and the temperature distribution within the battery cell, module and pack. The multi-physical battery thermal management systems are divided into three categories based on different methods of cooling the phase change materials such as air-cooled system, liquid-cooled system, and heat-pipe-cooled system. The emergency battery thermal battier methods are also summarized in multi-scale included material scale, battery management system and supplementary system. Finally, we propose a novel digital solution for full-lifespan thermal management control of EV power system based on CHAIN framework that helps improve the power battery temperature control strategy applying multiple working conditions. Image, graphical abstract [ABSTRACT FROM AUTHOR]

• 3D-printed polymer-based battery thermal management system is proposed • Coolant flow architecture reduces the effect of polymer low thermal conductivity • Low coolant temperature raise leads to lower BTMS energy consumption The thermal performance of a novel battery thermal management system produced by additive manufacturing is investigated through simulations. The performance of 3D-printed polymer-based battery thermal management systems is investigated for heat-managing high power density Li-ion batteries for electric vehicles and stationary applications. The manufacturing of the battery packs through 3D-printing allows for greater complexity and novelty in the design of the coolant flow domains, in order to achieve a high heat transfer coefficient by the coolant. Having a high heat transfer coefficient at the coolant side allows the use of lower conductive materials in the body of the battery pack. The proposed system takes advantage of 3D-printing technology to embedded heat fins in the cooling channel. The simulations consider various discharging rates from 2C to a high of 3C to take the battery from a 100% to 20% state of charge in the discharging process. For the charging rates 2C and 3C, the maximum battery temperature within the pack reached 22.8°C and 24.5°C, respectively. However, the maximum temperature difference across a six-battery pack reached no more than 1.5°C and 4.5°C, respectively. A maximum temperature difference achieved by the proposed system shows the ability of the 3D-printed polymer-based system to achieve the required performance and demonstrates the potential of such systems that are equipped with the advantage of additive manufacturing. [ABSTRACT FROM AUTHOR]

The heat dissipation from the battery surface significantly affects battery performance and lifetime. This study proposes a new and an alternative method to predict the thermal performance of the battery operation according to the surface temperature gradients and heat & exergy losses by using a data-driven dynamic mode decomposition method, which is new for thermal flows. To predict the thermal gradients, a 10 min long experiment is performed via an infrared thermographic camera for a commercial Li-polymer battery of a smartphone. The camera collects the thermal images on the battery surface along 1 min as the data training period at first; then, the proposed method predicts the surface temperature gradients for the rest of the experimental period, 5 min. The temperature gradients on the battery surface are well predicted with less than 1% error whereas the heat dissipation and the exergy loss are predicted with the maximum error values of 2.75% and 5.30%, respectively. According to the error probability distribution plots, the vast majority of the occurred error is less than ±5%. The results prove the fast prediction ability of the proposed technique and show promising outcomes for further improvement studies. Image 1 • A novel data-driven technique is developed for heat loss from batteries. • Training periods of 30 and 60 s-periods achieve well-prediction. • The method is verified via experimental results with less than 5% errors. • Data visualization is shown for 5 min-long battery charging. [ABSTRACT FROM AUTHOR]

• R134a AMFHP with 50% FR achieves the best performance among the three FRs. • The performance order of AMFHPs with 50% FR are ammonia > R134a > acetone. • Analysis is conducted about the liquid pool heat transfer of 3 fluids in AMFHPs. • The effect of air velocity on t e ¯ is obvious, however, its influence on λ eff is marginal. • Optimum air velocities for each AMFHP with different working fluids are presented. An experimental investigation is conducted to study the effect of the type of working fluid, liquid filling ratio (FR) and the cooling and heating conditions on the performance of air-cooled multi-port flat heat pipes (AMFHPs) designed for the thermal management of power battery. The results show that, under the same FR of 50%,the ammonia AMFHP owns the highest thermal performance, whose equivalent thermal conductivity is 2.21–3.30 times that of one filled with acetone and 1.05–1.31 times that of one using R134a as working substance. Evaporation thermal resistance of acetone AMFHP is significantly larger than those of the AMFHPs filled with ammonia and R134a, whereas their condensation thermal resistance values are comparative. Secondly, it is found that the equivalent thermal conductivity of the R134a AMFHP with 50% FR is 1.63–2.22 times that of one with 30% FR and 1.14–1.63 times that of one with 70% FR, respectively. Thirdly, result indicates that the effect of cooling air velocity on the equivalent thermal conductivity of AMFHP is insignificant, but the temperature of evaporation section is tightly connected to the cooling air velocity. There exists an economic air velocity for each AMFHP, the appropriate air velocities of the AMFHPs filled with R134a, acetone and ammonia at FR=50% are 3.5 m/s, 2.5 m/s and 3.5 m/s, respectively. In addition, analysis of heat transfer reveals that, the intensity of heat transfer mode of the AMFHPs in liquid pool ranges from R134a, ammonia and acetone, under the same working condition and filling ratio. The most direct conclusion is that the R134a AMFHP with appropriate FR is suitable to meet the thermal management requirements of lithium ion batteries for electric vehicles. [ABSTRACT FROM AUTHOR]

Battery modeling and state estimation are critical to the battery safety and vehicle driving range. Currently, electrochemical mechanism based models require huge computation effort for solving partial differential equations, equivalent circuit models do not consider actual battery mechanism, while machine learning models are lack of generalization ability due to their data-driven nature. All these problems bring the challenges to guarantee the model effectiveness in wide temperature and large current conditions. To estimate the battery state of charge (SOC) and state of temperature (SOT) under these conditions, an electrochemical-thermal-neural-network (ETNN) model is formulated in this paper. Specifically, a simplified single particle model and a lumped thermal model are served as the sub-models of ETNN to predict core temperature and provide approximate terminal voltage. Then a neural network is incorporated to enhance the performance of sub-models. According to the extensive experiments, ETNN model is able to accurately estimate battery voltage and core temperature under the ambient temperatures of -10–40 °C and the discharge rate of 10-C. After that, an unscented Kalman filter (UKF) is integrated with ETNN to achieve reliable co-estimation of SOC-SOT. Experimental results illustrate that proposed ETNN-UKF can rapidly eliminate initial errors and provide satisfactory co-estimation performance. • Formulation of a hybrid battery electrochemical-thermal-neural-network model. • High model accuracy under large currents and wide range of ambient temperatures. • Accurate co-estimation of SOC and SOT by integrating the unscented Kalman filter. [ABSTRACT FROM AUTHOR]

• A compact and lightweight liquid-cooled BTM solution is proposed. • The influences of the parameters on the performance of the TCS are investigated. • The structure of the TCS is designed for better performance and weight reduction. • Δ P , Δ T and m TCS after designing are reduced by 80%, 14% and 46%, respectively. • The system with parallel TCSs is designed to improve the cooling performance. Battery thermal management (BTM) is indispensable to the battery pack of electric vehicles (EVs) for safety. Among different types of BTM technologies, liquid cooling shows its superiority with high heat transfer coefficient and low power consumption. However, the previous works paid little attention to the compactness and weight ratio of liquid-cooled BTM system, which is vital to the specific energy of battery pack. In this study, a compact and lightweight liquid-cooled BTM system is presented to control the maximum temperature (T max) and the temperature difference (Δ T) of lithium-ion power battery pack. In this liquid-cooled solution, one thermal conductive structure (TCS) with three curved contact surfaces is developed to cool cylindrical battery. The influences of mass flow rate (m f), inner diameter (d), contact surface height (h) and contact surface angle (α) of the TCS are investigated through numerical study. It is found that for the 5C discharge rate process of battery, T max can be maintained within 313 K when m f is larger than 1 × 10−4 kg/s. A weight sensitive factor is defined to evaluate the influences of d , h and α on Δ T and the weight of TCS. It is found that d is the most important parameter that influences the weight. h is the secondary parameter, and α is the parameter with the minimal impact on the weight. Then the values of d , h , and α are designed to reduce the weight of TCS while maintaining its cooling performance. The designed TCS can control T max under 313 K with Δ T as 4.137 K. Compared to the original TCS, Δ P , Δ T and the weight are respectively reduced by 80%, 14% and 46% for the designed TCS. Furthermore, the performance of liquid-cooled system with parallel TCSs is discussed. The flow distribution among parallel TCSs is improved through designing the positions of the inlet and the outlet, which enables that T max and Δ T of battery pack is similar to the ones of a single battery. The present study facilitates the guideline for compact and lightweight design of liquid-cooled battery thermal management system. [ABSTRACT FROM AUTHOR]