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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]

The control of a battery thermal management system (BTMS) is essential for the thermal safety, energy efficiency, and durability of electric vehicles (EVs) in hot weather. To address the battery cooling optimization problem, this paper utilizes dynamic programming (DP) to develop an online rule-based control strategy. Firstly, an electrical–thermal-aging model of the LiFePO 4 battery pack is established. A control-oriented onboard BTMS model is proposed and verified under different speed profiles and temperatures. Then in the DP framework, a cost function consisting of battery aging cost and cooling-induced electricity cost is minimized to obtain the optimal compressor power. By exacting three rules "fast cooling, slow cooling, and temperature-maintaining" from the DP result, a near-optimal rule-based cooling strategy, which uses as much regenerative energy as possible to cool the battery pack, is proposed for online execution. Simulation results show that the proposed online strategy can dramatically improve the driving economy and reduce battery degradation under diverse operation conditions, achieving less than a 2.18% difference in battery loss compared to the offline DP. Recommendations regarding battery cooling under different real-world cases are finally provided. • A precise BTMS model for EV under diverse operation conditions is first proposed. • Battery capacity degradation and cooling energy is minimized by dynamic programming. • An online near-optimal battery cooling strategy is proposed from dynamic programming. • Using regenerative energy for cooling can dramatically reduce battery degradation. • Improved driving economy and battery life gained from the proposed cooling method. [ABSTRACT FROM AUTHOR]

A battery thermal management system (BTMS) using a composite phase change material (CPCM) is proposed for both heat dissipation under fast charging conditions and preheating in low temperature environments. Based on the validated battery thermal model and CPCM model, a parametric study was performed to determine the optimal conditions. As a result, in the proposed concept, the highest maximum temperature and maximum temperature difference are 39.3 °C and 3 °C under 3C charging conditions at room temperature. This is achieved by decreasing the total operating time of the liquid cooling system by 35.2% compared to that of the conventional BTMS, and after the cycle, the latent heat is fully recovered for use in a continuous cycle. Also, under low temperature conditions of −10 °C, the final maximum temperature is 29.2 °C after preheating in the proposed BTMS. The temperature difference is 2.5 °C, which is significantly lower than when applying the existing liquid heating method. Therefore, the proposed BTMS is advantageous in terms of both the cooling performance under fast charging conditions and preheating under low temperature conditions. • A compact BTMS with composite phase change material using copper foam is proposed. • Both the extreme conditions of fast charging and low temperature are covered. • The practical application of CPCM under charge-discharge cycle is considered. • Battery thermal model and CPCM model were validated well with experimental data. [ABSTRACT FROM AUTHOR]

The temperature has a significant effect on the lifespan and the safety of the batteries which are one of the core components of electric vehicles. A well-designed battery thermal management system is required to adjust the temperature of the batteries within an appropriate range for thermal safety, and further minimize the energy consumption for energy savings. However, these two goals form a tradeoff. Typically, increased energy consumption for cooling results in safer batteries thermally. To examine this tradeoff, firstly, a linear electro-thermal model is built to evaluate the thermal dynamics of the operating battery-cooling module. The linear model accounts for the heat generation based on internal resistance, and the heat transfer based on a resistance–capacitance model. Such linear model reduces the computation of the model simulation to dynamically catch up with the change of temperatures and to implement control strategies on the cooling system in a short time. Based on this model, a model predictive control (MPC) framework is proposed to design thermal control methods, which considers both thermal safety and energy saving. The weight of these two goals can be adjusted to explore the tradeoff between them. Finally, we investigate the performance of the MPC framework by applying the Urban Dynamometer Driving Schedule (UDDS) to the battery module. The simulation results show that the electro-thermal model is effective for battery thermal dynamics evaluation. Additionally, the tradeoff between the two goals is demonstrated by the simulation. • A fast temperature prediction and closed-loop thermal control framework is proposed. • An electro-thermal model of an active-liquid-cooling battery module is developed. • A thermal prevention control strategy is proposed. [ABSTRACT FROM AUTHOR]

• The LiFePO 4 overcharge process is divided into four stages. • ICA and DVA are used to reveal the internal mechanism when different gases are detected. • A Three-Level warning strategy is proposed based on the voltage, temperature, and gases. The thermal runaway (TR) of lithium-ion batteries (LIBs) is difficult to control when it reaches the late stage, which results in disastrous accidents, while the current means of early warning are biased late or inaccurate. Therefore, an early monitoring and warning strategy is necessary for LIB to mitigate TR. In this study, overcharge tests on LiFeO 4 batteries were conducted at various current rates (C-rates). The evolutions of voltage, gas, and temperature during overcharge were analyzed, and the TR process could be divided into four stages: Stage I (initial stage), Stage II (gas detected stage), Stage III (reaction accelerating stage), Stage IV (post-TR stage). The maximum surface temperature difference (Δ T max) exceeded 5 °C in Stage II. Incremental capacity analysis (ICA) and differential voltage analysis (DVA) were used to reveal the internal mechanism when different gases were detected in Stage II, and the safety performance of the LIB was affected severely. To avoid TR of LIB, it was necessary to start early warning in Stage II. A Three-Level warning strategy was proposed based on the voltage turning point (V TP), temperature, and the appearance of various gases in Stage II. A reliable warning before the TR was achieved by setting the threshold effectively, and the TR event was mitigated successfully. These findings provide a critical basis to enhance the monitoring and warning capability of the battery management system as well as battery safety. [ABSTRACT FROM AUTHOR]

• Hybrid cooling using PCM plates and MCPs is numerically studied. • Using 3 PCM plates reduces the maximum battery temperature by 16.2 K. • Hybrid cooling system considerably improves temperature uniformity. • Adding PCM plates, the required water pumping power is decreased by up to 68%. • Using 3 PCM plates increased the time to battery overheating by up to 105%. Battery thermal management systems play a significant role in the safety, performance, and maintenance of electric vehicles. This paper proposes a new hybrid cooling system incorporated with phase change material (PCM) and liquid cooling to achieve high performance and safety for the pack of prismatic batteries. Each four battery cells are grouped as a module and placed between vertically orientated mini-channel cold plates. PCM plates are also placed horizontally between the battery cells. This new design is simple enough to be implemented easily in common cooling systems and could provide parallel cooling of the active and passive methods with subsequent improvement in thermal performance and system safety. Three-dimensional numerical simulations are validated against previous empirical and numerical works. The thermal performance, power consumption, and safety of the hybrid cooling systems are investigated in a variety of battery discharge rates and mini-channel inlet velocities using different numbers of PCM plates. Also, the system performance is tested in a real driving cycle. This new design could notably improve the battery thermal management characteristics. The maximum battery temperatures in the hybrid system with three PCM plates at 2C and 3C discharge rates were 5.6 K and 16.2 K lower than those without PCM plates. Besides, adding three PCM plates reduced the temperature difference by up to 33 % at 3C discharge rate. Another key finding was that at 3C discharge rate, by simultaneously utilizing three PCM plates and decreasing the fluid inlet velocity, the power consumption per battery cell is reduced by 68 % (from 1.187 mW to 0.0375 mW). Furthermore, considering the PCM plates as the emergency backup, the time to reach the critical temperature increased by 38 % and 105 % in the systems with 1 and 3 PCM plates, respectively. Testing in a real driving cycle reveals the superiority of the hybrid system over the active cooling method by peak shaving of the thermal loads and reducing thermal fluctuations and maximum temperature. This novel design for battery thermal management could provide high performance for batteries and reduce fabrication and maintenance costs. [ABSTRACT FROM AUTHOR]

Battery thermal management is essential to achieve good performance and a long battery system lifespan in electric vehicles and stationary applications. Such a thermal management system is dependent on temperature monitoring, which is frequently hampered by the limited sensor measurements. The virtual sensor is brought forward to overcome this physical restriction and provide broader access to the battery's temperature distribution. Through leveraging the combined convolutional neural network (CNN) and long short-term memory (LSTM) networks to extract both spatial and temporal information from the data, this paper proposes a novel virtual sensing platform. A PID compensator is included to offer auxiliary correction to the inputs and drive the prediction error to zero over time in a feedback loop. Off-line and online modes of this CNN-LSTM virtual sensor are considered. The network, which is trained off-line, will work with the PID compensator in the online mode with real-time sensor data. With the PID-based accuracy-boosted virtual sensor, the performance of the trained CNN-LSTM prediction on real-time data inputs is improved. Besides, this PID compensator reduces the number of hyper-parameters to be tuned. Based on control theory, the design of PID and its analysis are presented as well. With generated battery thermal data, numerical simulations show that the CNN-LSTM-PID virtual sensing framework can achieve the real-time prediction error reduction rate to 35.52% on average with 18.78% less online calculation time. • Novel virtual sensing platform with CNN-LSTM for comprehensive cell level temperature monitoring. • PID-based accuracy boosting algorithm enhancing trained CNN-LSTM performance on real-time sensor data. • Analysis of CNN-LSTM dynamics based on heat equations of batteries and PID parameters search space characterization based on control theory. • Computationally efficient PID tuning in offline mode and boosted prediction accuracy in the online mode of CNN-LSTM virtual sensor. [ABSTRACT FROM AUTHOR]

• A battery thermal management system that uses fins to enhance the combination of thermoelectric cooler and phase change material was established. • Compared the effects of four thicknesses of fins on the thermal management performance. • It was proved that adding fins is beneficial to improve the thermal management performance under three working conditions. • The influence of the input current on the cooling power and COP of TEC was analyzed. In this study, a hybrid active & passive BTMS(Battery Thermal Management System) that uses fins to enhance the combination of TEC(Thermoelectric Cooler) and PCM(Phase Change Material) is shown. The cold side of the TECs produces a cooling effect, which is used to cool the PCM and prevent it from melting completely in a short time, thereby extending the temperature control time. Fins are used to transfer the heat of the PCM to the cold side of the TECs, and effectively cool the batteries at high temperatures. The effects of different fin thicknesses (2 mm-8 mm) and different TEC input currents (1A-6A) on thermal management performance were analyzed by numerical simulation. The results show that the temperature control time was prolonged by 12% when the fins were increased from 2 mm to 8 mm, but the temperature difference increased by 13.7%. When the current changed from 1A to 6A, the temperature control time increased by 87.42%, but the temperature difference and COP became worse. Comprehensive analysis of temperature control time, temperature difference, COP, 4 mm fin thickness, and TEC input current of 3A were optimal for the model in this paper. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-Objectives Optimization is used to improve cooling performance of hybrid PCM-Air BTMS. • All dimensions, air velocity, and PCM type are optimized by design of experiment methodology. • Sensitivity analyses are performed for all independent variables. • Cooling efficiency of BTMS is improved remarkably after the optimization. • Results are cross-validated between simulations and the experimentally fabricated optimized pack. Studies have confirmed that using phase change materials (PCM) as a battery thermal management system (BTMS) in the battery pack controls the battery's temperature and improves its performance; however, it undeniably imposes a significant weight on EV. Therefore, a pivotal issue remains, the best economic battery pack design and required PCM to guarantee the pack's performance. This paper optimizes the arrangement of the hybrid PCM-Air BTMS by the multi-objective Response Surface Method (RSM) to enhance the system's cooling achievement under the New European Driving Cycle (NEDC). The influence of four factors, including; 1) PCM thickness (A), 2) air gap (B), 3) air velocity (C), and 4) PCM type (D), are investigated. The objective of the optimization is to minimize the highest and mean battery temperature and the temperature difference among cells, as well as maximize the total liquid fraction and the power density per cost ((W / m 3) / $) (PDC). polyethylene glycol-1000 (PEG-1000) is applicable for high-speed inlet air and short distances (up to 2hr driving time), and PEG (1500) for low-velocity inlet air and longer distances. Increasing the C does not always reduce the cell temperature. Also, C up to 1 m/s cannot reliably keep the cell temperature in a safe range. Increasing A at low Cs improves cell temperature and at higher Cs warms the cell. Increasing A, B, and C can significantly control the temperature difference. One of the best optimal conditions is: A = 1.7, B = 2.37, C = 0.93, D = PEG(1000). This pack is almost 91% cheaper than conventional BTMSs in today's EVs; In fact, by investing 1$ per each unit volume ( 1 m 3) in a similar EV, almost 20% more cells (power) can be mounted in this pack. Finally, this pack was fabricated under optimum point specifications, and experimental results were well consistent with the simulation results. [ABSTRACT FROM AUTHOR]

• A multifunction flexible composite phase change material (CPCM) has been proposed. • Ethylene-Propylene-Diene Monomer (EPDM) based CPCM has excellent anti-leakage property. • Thermal contact resistances of rigid and flexible CPCMs under vibration are compared. • Flexible CPCM with EPDM for battery module has prominent anti-vibration performance. From the assembly and application perspective, battery thermal management system with phase change material has been highly desirable but remains significant challenges, including phase change material leakage, high rigidity and low thermal conductivity. In this study, a novel anti-leakage and anti-vibration thermally induced flexible composite phase change material has proposed which is utilized Ethylene-Propylene-Diene Monomer to increase the crosslinking of styrene-butadienestyrene block copolymer, so as to improve the adsorption of paraffin. The results revealed that the mass retention rate of thermally induced flexible composite phase change material with 3 wt% Ethylene-Propylene-Diene Monomer and 5 wt% expanded graphite was still more than 99% after heating (60 °C, 10 h) condition. Besides, the maximum temperature of battery module with the flexible composite phase change materials can be still controlled below 50 °C at 1C discharge rate, the corresponding temperature difference was effectively maintained within 2 °C. With these prominent performances, the battery module with designed thermally induced flexible composite phase change material can provide insights into the passive thermal management and other energy storage fields. [ABSTRACT FROM AUTHOR]

• The battery thermal model accuracy is improved by considering the radiation effect. • The sensor bias is treated as an augmented state to be estimated with temperatures. • The online experimental tests demonstrate the efficacy of the proposed method. Lithium-ion battery is now considered as an enabling technology for modern civilization and sustainability, initiating wireless revolution and efficient energy storage. In spite of the significant progress made in materials and manufacturing, the growing awareness on the operational safety and reliability requires more efficient battery management systems. Core temperature, an underlying variable for battery management, is unfortunately unmeasurable and has to be online estimated via other measurable variables. The core temperature monitoring becomes even more challenging when the measurable variables encounter sensor bias as well as model inaccuracy and sensor noise. To this end, this paper improves the thermal model accuracy by introducing a radiation term into the conventional linear lumped model. The unknown parameters of the new nonlinear model are identified based on multi-objective optimization, of which the results confirm the superiority of the proposed nonlinear model. The sensor bias is treated as an extended state to be estimated together with other states. An extended unscented Kalman filter is accordingly developed to handle the nonlinearity, measurement noise and sensor bias. Both simulation and experimental results are given to demonstrate the efficacy of the proposed method, showing that the core temperature can be accurately estimated in spite of the sensor biases in the surface temperature or electric current measurements. [ABSTRACT FROM AUTHOR]

• A dynamic J-type battery thermal control system is established. • The mode switching control succeeds to maintain the battery thermal performance. • The energy efficiency is improved by 15.8% by employing model predictive control. Battery thermal control plays an indispensable role in terms of the safety and performance for electric vehicles. For air-based cooling technologies, one of the most pressing challenges is to balance the temperature uniformity and constrain the maximum temperature simultaneously under varying driving conditions. This paper proposes a self-adaptive intelligent neural network-based model predictive control strategy for a J -type air-based battery thermal management system. The J -type structure is first optimized through surrogate-based optimization to improve the temperature uniformity before control. Based on the optimized J -type configuration, an operation mode switching module is developed to mitigate the temperature unbalance. The thermal control approach is tested using an integrated driving cycle, and its evaluations are threefold: (i) the neural network-based control without mode switching fails to meet the thermal requirements; (ii) the control with mode switching succeeds in constraining the maximum temperature and maintaining the temperature uniformity within 1.33 K; (iii) the added model predictive control approach slightly enhances the thermal performance but improves the energy efficiency significantly by 15.8%. The results show that the J -type structure with its appropriate control strategy is a promising solution for light-duty electric vehicles using an air-cooling technology. [ABSTRACT FROM AUTHOR]