Advanced Battery Thermal Management Solution for Electric Vehicles

The transition to renewable energy sources from fossil fuels requires that the harvested energy be stored because of the intermittent nature of renewable sources. Thus, lithium-ion batteries have become a widely utilized power source in both daily life and industrial applications due to their high power output and long lifetime. In order to ensure the safe operation of these batteries at their desired power and capacities, it is crucial to implement a thermal management system (TMS) that effectively controls battery temperature. In this study, the thermal performance of a 1S14P lithium-ion battery module composed of cylindrical 18650 cells was compared for distinct cases of natural convection (no cooling), forced air convection, and phase change material (PCM) cooling. During the tests, the greatest temperatures were reached at a 2C discharge rate; the maximum module temperature reached was 55.4 °C under the natural convection condition, whereas forced air convection and PCM cooling reduced the maximum module temperature to 46.1 °C and 52.3 °C, respectively. In addition, contacting the battery module with an aluminum mass without using an active cooling element reduced the temperature to 53.4 °C. The polyamide battery housing (holder) used in the module limited the cooling performance. Thus, simulations on alternative materials document how the cooling efficiency can be increased. Full article

Accurately predicting lithium-ion batteries’ state of temperature (SOT) is crucial for effective battery safety and health management. This study introduces a novel approach to SOT prediction based on voltage and temperature profiles during the abusive discharging process, aiming for enhanced prediction accuracy and evaluating the safety range. The duration of equal voltage discharge and temperature variation during discharge are considered temperature indicators. Linear regression and R² analyses are employed to assess the relationship and variance over different discharge–charge cycles of varied duration between the complete life cycle and its temperature variance. In this study, a decision tree (DT) and an artificial neural network (ANN) are employed to estimate the SOT of a Li-ion battery. The effectiveness and accuracy of the proposed methods are validated using ageing data from eVTOL charge–discharge cycles through numerical simulations. The results demonstrate that for the short cruise range of 600 s, the DT algorithm with an R² regression value of 6.17% demonstrates better performance than ANN, whereas for the bigger cruise range of 1000 s, the ANN model with an R² regression value of 5.06 percent was better suited than DT. It is concluded that both DT and ANN outperform other methods in predicting the SOT of lithium-ion batteries. Full article

The battery systems of electric vehicles (EVs) are directly impacted by battery temperature in terms of thermal runaway and failure. However, uncertainty about thermal runaway, dynamic conditions, and a dearth of high-quality data sets make modeling and predicting nonlinear multiscale electrochemical systems challenging. In this work, a novel Mamba network architecture called BMPTtery (Bidirectional Mamba Predictive Battery Temperature Representation) is proposed to overcome these challenges. First, a two-step hybrid model of trajectory piecewise–polynomial regression and exponentially weighted moving average is created and used to an operational dataset of EVs in order to handle the problem of noisy and incomplete time-series data. Each time series is then individually labeled to learn the representation and adaptive correlation of the multivariate series to capture battery performance variations in complex dynamic operating environments. Next, a prediction method with multiple steps based on the bidirectional Mamba is suggested. When combined with a failure diagnosis approach, this scheme can accurately detect heat failures due to excessive temperature, rapid temperature rise, and significant temperature differences. The experimental results demonstrate that the technique can accurately detect battery failures on a dataset of real operational EVs and predict the battery temperature one minute ahead of time with an MRE of 0.273%. Full article

The power battery is a key component of electric vehicles and its performance is greatly affected by temperature. Battery thermal management systems based on phase change materials can effectively control the battery temperature and at the same time have the advantages of simple structures, energy savings, and good temperature uniformity, and has broad development prospects. In this paper, expanded graphite–paraffin composite phase change materials were prepared, phase change material cooling experiments were carried out, and a phase change material cooling simulation model was also established using the Fluent software to study the influence of phase change material thermophysical parameters on thermal management performance. The results show that the phase change material thermal management method has excellent cooling performance. The best thermal management performance is achieved at the 3C discharge rate, with a phase change material filling thickness of 4 mm, a melting point of 40 °C above ambient temperature, and a thermal conductivity of 3 W/(m·K). When the phase change latent heat was increased from 150 J/g to 250 J/g, the liquid phase ratio decreased from 0.84 to 0.51, and the subsequent cooling performance was greatly improved, so the phase change latent heat should be increased as much as possible. Full article

The primary objective pursued in this research is the creation and thorough evaluation of an inventive cooling system designed to uphold optimal temperatures within the batteries employed in electric vehicles. Nowadays, the prevailing equipment underpinning electrical motion hinges on Lithium-Ion cells. These cells frequently necessitate the expeditious delivery of substantial power, thereby giving rise to a consequential generation of heat. Consequently, there is an emergence of elevated operational temperatures, potentially causing noteworthy declines in battery performance, or, in extreme cases, operational failures. Furthermore, deviating from the recommended temperature range (20–40 °C) significantly expedites the aging process of the battery and elevates the probability of premature malfunction. In response to these crucial challenges, the implementation of a battery thermal management system assumes a pivotal role in maximizing battery efficiency. Within the framework of this investigation, we propose the adoption of a cooling system founded on a three-dimensional pulsating heat pipe as the designated thermal management technology for a battery pack. The preliminary phase of our study involved the assessment of the suggested pulsating heat pipe’s performance. Following this, the efficacy of the pulsating heat pipe is subjected to rigorous scrutiny through practical experimentation on an authentic electric battery. The empirical findings conclusively highlight the substantial cooling capacity of the proposed system, thereby presenting a robust and efficacious solution for the thermal management challenges faced by electric vehicle batteries. Full article

This study proposes an anti-gravity 3D pulsating heat pipe (PHP) for cooling pouch batteries in electric vehicles. The 3D PHP envelops the battery cells and rapidly transfers heat generated from the batteries to the bottom cold plate. While the batteries generate heat on their frontal surface during charging and discharging, structural characteristics lead to localized heat accumulation at the electrode lead tabs. Therefore, to address frontal heating, Pattern A with a consistent height for the 3D PHP and Pattern B with varying heights to enhance heat transfer in the localized heating area were designed. The target application involved creating a battery simulator for 340 × 100 mm pouch battery cells, considering the battery’s heat generation characteristics. The experiments for the thermal characteristics were conducted, considering factors such as the working fluid (methanol, Novec7100), filling ratio, supplied heat, and orientation. Additionally, to observe internal flow mechanisms, a special experimental apparatus was used, employing transparent fluorine rubber tubes to observe the flow mechanism of the 3D PHP. In the results of the thermal characteristics, the optimal filling ratio was 15% when heat generation levels of 50 W and 100 W were supplied and 20% when 150 W was supplied. The impact of orientation yielded varied results depending on the pattern and working fluid, attributed to the complex interplay of flow momentum due to orientation changes and the influence of the working fluid’s buoyancy under anti-gravity conditions. Pattern B, designed with the goal of applying a localized heat model, exhibited relatively decreased heat transfer performance in areas with varying heights. As the distance from the varying height portion increased, temperature oscillations and heat transfer became more active. These results suggest that variations in the shape of the 3D PHP could be a primary design variable for crafting localized heat models. Observations of internal flow revealed that the 3D PHP, with its unique shape and operation under anti-gravity conditions, exhibits longer and more irregular cycles compared to gravity-assist PHPs, transferring heat through rapid oscillations of internal working fluid liquid/vapor slug/plug. The potential of 3D PHPs for cooling electric vehicle batteries is suggested by these findings, and further experimentation is planned to evaluate the optimal design and applicability. Full article

Electric vehicles (EVs) are experiencing explosive developments due to their advantages in energy conservation and environmental protection. As a pivotal component of EVs, the safety performance of lithium-ion batteries directly affects driving miles and even safety; hence, a battery thermal management system (BTMS) is especially important. To improve the thermal safety performance of power battery modules, first, a new leak-proof phase change material (PCM)-coupled liquid-cooled composite BTMS for large-scale battery modules is proposed in this research. Second, the numerical simulation analysis method was utilized to analyze the influences of the fluid flow channel shape, working fluid inlet temperature, inlet velocity, and reverse flow conditions on the BTMS. Eventually, the abovementioned performances were compared with the traditional PCM-coupled liquid-cooling strategy. The relative data indicated that the T_max was reduced by 17.5% and the ΔT_max was decreased by 19.5% compared to the liquid-cooling approach. Further, compared with conventionally designed PCM composite liquid cooling, the ΔT_max was reduced by 34.9%. The corresponding data showed that, when using the e-type flow channel, reverse flow II, the inlet flow velocity was 0.001–0.005 m/s, and the inlet temperature was the ambient temperature of the working condition. The thermal performance of the anti-leakage system with a thermal conduction slot PCM-coupled liquid-cooling composite BTMS reached optimal thermal performance. The outcome proved the superiority of the proposed BTMS regarding temperature control and temperature equalization capabilities. It also further reduced the demand for liquid-cooling components, avoided the problem of the easy leakage of the PCM, and decreased energy consumption. Full article

With an increase in global warming, battery electric vehicles (BEVs), which are environmentally friendly, have been rapidly commercialized to replace conventional vehicles with internal combustion engines. Unlike traditional internal combustion engine vehicles, the powertrain system of BEVs operates with high efficiency, resulting in lower heat generation. This poses a challenge for cabin heating under low-temperature conditions. Conversely, under high-temperature conditions, the operating temperature of a high-voltage battery (HVB) is lower than the ambient air temperature, which makes cooling through ambient air challenging. To overcome these challenges, in this study, we proposed an integrated thermal management system (ITMS) based on a heat pump system capable of stable thermal management under diverse climatic conditions. Furthermore, to assess the ability of the proposed ITMS to perform thermal management under various climatic conditions, we integrated a detailed powertrain system model incorporating BEV specifications and the proposed ITMS model based on the heat pump system. The ITMS model was evaluated under high-load-driving conditions, specifically the HWFET scenario, demonstrating its capability to perform stable thermal management not only under high-temperature conditions, such as at 36 °C, but also under low-temperature conditions, such as at −10 °C, through the designated thermal management modes. Full article

This study proposes a simulation technique for investigating a battery thermal management system based on direct refrigerant cooling (BTMS-DRC). The main focus is to investigate the temperature uniformity and working temperature of the module housing. The simulation technique employs a finite element method for a combined conduction–convection heat transfer to predict the module housing temperature. The refrigerant side is based on two-phase flow evaporation, which is represented by the convection heat transfer under a certain refrigerant saturation temperature. The real BTMS-DRC, which is based on the dual-evaporator vapor compression refrigeration system, is constructed for experimentation with the test bench. The simulated result is validated with the experimental results to ensure correction of the modelling. Error rates of approximately 2.9–7.2% are noted throughout the specified working conditions. The BTMS can produce temperatures of less than 35 °C under conditions where 80–320 W heat is generated. The difference in the temperature of the module is around 1.7–4.2 °C. This study also investigates the impact of heat generation, the convection heat transfer coefficient (h_ref), the refrigerant saturation temperature, and thermal conductivity on the module’s temperature. The thermal conductivity ranges from 25 to 430 W/m·K, while the h_ref ranges from 80 to 400 W/m²·K. Full article

The electric vehicle thermal management system (EVTMS) plays a crucial role in ensuring battery efficiency, driving range, and passenger comfort. However, EVTMSs still face unresolved challenges, such as accurate modeling, compensating for temperature variations, and achieving efficient control strategies. Addressing these issues is crucial for enhancing the performance, reliability, and energy efficiency of electric vehicles. Therefore, this study presents a cooling EVTMS model, considering both the battery pack temperature and the cabin comfort, and utilizes the prediction of neural network as a feedforward in a fuzzy PI controller to compensate for the model temperature variations. The simulation results reveal that, compared with PI controller and MPC, the neural network fuzzy PI (NN-Fuzzy PI) controller can well predict and compensate for the system’s nonlinear characteristics as well as the time-delay caused by heat transfer, achieving superior control performance and reducing energy consumption. The battery pack temperature and $\mathrm{PMV}$ fluctuations are effectively constrained within [−0.5, 0.5] and [−0.1, 0.1], reducing up to 150% and 164%, and the energy consumption of the pump and compressor are reduced by up to 0.23 and 100.1 $\mathrm{KJ}$, with ranges of 18% and 2.68%. Meanwhile, the neural network feedforward also works effectively in different controllers. The findings of this research can provide valuable insights for TMS engineers to select advanced control strategies. Full article

The thermal performance of a lithium-ion battery module comprising three cells contained within a casing was investigated at discharge rates of 3C and 5C with three different cooling strategies: forced air, phase-change material (PCM), and a hybrid system using a combination of forced air and the PCM. Three levels of fan speed (5000 rpm; 7000 rpm; and 9000 rpm) for cooling air flow were considered. A numerical simulation of heat transfer was performed using the ANSYS Fluent software. The electrochemical modelling of a battery was developed based on the NTGK approach, and the phase-change phenomenon was treated as an enthesis–porosity problem. The composite PCM, aluminum metal foam embedded in n-octadecane, had better heat dissipation performance than forced air convection. The PCM is significantly more effective at heat dissipation than forced air. Interestingly, when using a hybrid cooling system that combines forced air and a PCM, although it meets the operational requirements for Li-ion batteries in regard to maximum temperature and temperature uniformity at a 3C discharge rate, the airflow appears to have a negligible effect on thermal management and yields an indiscernible change in temperature. This can be attributed to a complex flow pattern that developed in a casing as a result of the suboptimal design of the inlet and outlet. Further studies will be required for the optimal positioning of the inlet and outlet, as well as the effectiveness of combining liquid cooling methods. Full article

The transportation sector is a significant contributor to greenhouse gas (GHG) emissions due to large energy consumption, which is why there is a need to promote the use of electric vehicles (EVs) to mitigate overall GHG emissions. To ensure market confidence towards EVs, battery packs’ energy storage capacity and thermal management system (TMS) must be optimized. Designing a battery pack that can withstand changes in temperature is essential to the TMS. In this study, we proposed two battery pack designs with cell arrangement angles of $\theta =\pi /3$ and $\theta =\pi$, respectively, to investigate TMS. The CAD models were drawn, and simulations were performed using ANSYS Fluent with a mesh size of 0.005m. The computational fluid dynamics (CFD) analysis was conducted to obtain the maximum and average temperature and fluid flow velocity. Our results show that the 3 parallel and 8 series (3p8s) battery pack design with a cell arrangement angle of $\theta =\pi /3$ is the most feasible and can consistently perform in thermal management. This design also has 15% less volume than the cell arrangement of $\theta =\pi$, allowing for more battery packs to be incorporated in the EV for a longer range of travel. Furthermore, this design can maintain the battery pack at its optimal operating temperature of 25 °C, reducing the incidence of battery runaway and ultimately lowering the EVs maintenance costs. The proposed design approach can serve as a basis for designing battery packs with optimized thermal management systems for EVs, contributing to the global effort to reduce GHG emissions. Full article

The development of hybrid technology can effectively solve the problems of the high pollution and energy consumption levels of automobiles. Therefore, an energy consumption prediction and control algorithm for hybrid vehicles based on a minimum equivalent fuel consumption model is proposed. The model’s battery power consumption is equivalent to the fuel consumption, and the sum of the engine fuel consumption and the battery equivalent fuel consumption is established as the objective function. By utilizing these factors, an innovative minimum equivalent fuel consumption model was constructed that could be used to measure the energy efficiency of hybrid vehicles. The longitudinal force result of braking force distribution control was obtained, as well as the energy consumption prediction structure of a hybrid electric vehicle. The rolling resistance, air resistance, and climbing resistance of the hybrid electric vehicles were calculated, and the energy consumption control algorithm for hybrid electric vehicles was constructed according to the calculation results. The experimental results indicated that under this research algorithm, the driving energy consumption of hybrid electric vehicles was relatively low and the energy consumption and energy efficiency measurements effectively met the actual demand, and the energy consumption prediction and control results were good. Full article

Electric vehicles (EVs) have become a viable solution to the emerging global climate crisis. Rechargeable battery packs are the basic unit of the energy storage system of these vehicles. The battery thermal management system (BTMS) is the primary control unit of the energy source of the vehicles. EV performance is governed by specific power, charging/discharging rate, specific energy, and cycle life of the battery packs. Nevertheless, these parameters are affected by temperature, making thermal management the most significant factor for the performance of a battery pack in an EV. Although the BTMS has acquired plenty of attention, research on the efficiency of the liquid cooling-based BTMS for actual drive cycles has been minimal. Liquid cooling, with appropriate configuration, can provide up to 3500 times more efficient cooling than air cooling. Direct/immersive and indirect liquid cooling are the main types of liquid cooling systems. Immersive/direct cooling utilizes the technique of direct contact between coolant and battery surface, which could provide larger heat transfer across the pack; however, parameters such as leakage, configuration, efficiency, etc., are needed to be considered. Indirect cooling techniques include cold plates, liquid jackets, discrete tubes, etc. It could result in complex configuration or thermal non-uniformity inside the pack. The paper intends to contribute to the alleviation of these gaps by studying various techniques, including different configurations, coolant flow, nanoparticles, varying discharging rates, different coolants, etc. This paper provides a comprehensive perspective of various techniques employed in liquid cooling battery packs, identifying the shortcomings in direct/immersive and indirect liquid cooling systems and discussing their mitigation strategies. Full article