Search

In the present study, the thermal and electrical performances of automotive waste heat recovery thermoelectric generator system are investigated for different internal fin structures in hot heat exchanger. A coupled numerical model integrated with heat transfer and thermoelectric effects is developed to simulate the Multiphysics behavior of thermoelectric generator system. The coupled numerical model is validated with experimental results for both thermal and electrical performances within maximum error of ± 8%. The temperature difference, pressure drop, power, conversion efficiency, exergy efficiency, and net efficiency of thermoelectric generator system are compared for hot heat exchanger without internal fin structure and that with 12 different internal fin structures. The 12 different internal fin structures comprise of straight fins, perpendicular fins, fishbone fins, triangular guide fins, and combination of fins. The results reveal that, an Internal structure11 depicts superior thermal and electrical performances of thermoelectric generator system among all internal fin structures. Despite of higher pressure drop of 0.04571 bar, the Internal structure11 shows superior power, conversion efficiency, exergy efficiency, and net efficiency of 70.79 W, 7.76%, 14.10%, and 0.996%, respectively. The hot heat exchanger with Internal structure11 is proposed as the best configuration for the optimum performance of thermoelectric generator system. [ABSTRACT FROM AUTHOR]

The limitations of existing commercial indirect liquid cooling have drawn attention to direct liquid cooling for battery thermal management in next-generation electric vehicles. To commercialize direct liquid cooling for battery thermal management, an extensive database reflecting performance and operating parameters needs to be established. The development of prediction models could generate this reference database to design an effective cooling system with the least experimental effort. In the present work, artificial neural network (ANN) modeling is demonstrated to predict the thermal and electrical performances of batteries with direct oil cooling based on various operating conditions. The experiments are conducted on an 18650 battery module with direct oil cooling to generate the learning data for the development of neural network models. The neural network models are developed considering oil temperature, oil flow rate, and discharge rate as the input operating conditions and maximum temperature, temperature difference, heat transfer coefficient, and voltage as the output thermal and electrical performances. The proposed neural network models comprise two algorithms, the Levenberg–Marquardt (LM) training variant with the Tangential-Sigmoidal (Tan-Sig) transfer function and that with the Logarithmic-Sigmoidal (Log-Sig) transfer function. The ANN_LM-Tan algorithm with a structure of 3-10-10-4 shows accurate prediction of thermal and electrical performances under all operating conditions compared to the ANN_LM-Log algorithm with the same structure. The maximum prediction errors for the ANN_LM-Tan and ANN_LM-Log algorithms are restricted within ±0.97% and ±4.81%, respectively, considering all input and output parameters. The ANN_LM-Tan algorithm is suggested to accurately predict the thermal and electrical performances of batteries with direct oil cooling based on a maximum determination coefficient (R2) and variance coefficient (COV) of 0.99 and 1.65, respectively. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) offer a potential solution to face the global energy crisis and climate change issues in the transportation sector. Currently, lithium-ion (Li-ion) batteries have gained popularity as a source of energy in EVs, owing to several benefits including higher power density. To compete with internal combustion (IC) engine vehicles, the capacity of Li-ion batteries is continuously increasing to improve the efficiency and reliability of EVs. The performance characteristics and safe operations of Li-ion batteries depend on their operating temperature which demands the effective thermal management of Li-ion batteries. The commercially employed cooling strategies have several obstructions to enable the desired thermal management of high-power density batteries with allowable maximum temperature and symmetrical temperature distribution. The efforts are striving in the direction of searching for advanced cooling strategies which could eliminate the limitations of current cooling strategies and be employed in next-generation battery thermal management systems. The present review summarizes numerous research studies that explore advanced cooling strategies for battery thermal management in EVs. Research studies on phase change material cooling and direct liquid cooling for battery thermal management are comprehensively reviewed over the time period of 2018–2023. This review discusses the various experimental and numerical works executed to date on battery thermal management based on the aforementioned cooling strategies. Considering the practical feasibility and drawbacks of phase change material cooling, the focus of the present review is tilted toward the explanation of current research works on direct liquid cooling as an emerging battery thermal management technique. Direct liquid cooling has the potential to achieve the desired battery performance under normal as well as extreme operating conditions. However, extensive research still needs to be executed to commercialize direct liquid cooling as an advanced battery thermal management technique in EVs. The present review would be referred to as one that gives concrete direction in the search for a suitable advanced cooling strategy for battery thermal management in the next generation of EVs. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are incorporated with higher energy density batteries to improve the driving range and performance. The lithium-ion batteries with higher energy density generate a larger amount of heat which deteriorates their efficiency and operating life. The currently commercially employed cooling techniques are not able to achieve the effective thermal management of batteries with increasing energy density. Direct liquid cooling offers enhanced thermal management of battery packs at high discharging rates compared to all other cooling techniques. However, the flow distribution of coolant around the battery module needs to be maintained to achieve the superior performance of direct liquid cooling. The objective of the present work is to investigate the heat transfer characteristics of the lithium-ion battery pack with dielectric fluid immersion cooling for different fin structures. The base structure without fins, circular, rectangular and triangular fin structures are compared for heat transfer characteristics of maximum temperature, temperature difference, average temperature, Nusselt number, pressure drop and performance evaluation criteria (PEC). Furthermore, the heat transfer characteristics are evaluated for various fin dimensions of the best fin structure. The heat transfer characteristics of the battery pack with dielectric fluid immersion cooling according to considered fin structures and dimensions are simulated using ANSYS Fluent commercial code. The results reveal that the symmetrical temperature distribution and temperature uniformity of the battery pack are achieved in the case of all fin structures. The maximum temperature of the battery pack is lower by 2.41%, 2.57% and 4.45% for circular, rectangular, and triangular fin structures, respectively, compared to the base structure. The triangular fin structure shows higher values of Nusselt number and pressure drop with a maximum value of PEC compared to other fin structures. The triangular fin structure is the best fin structure with optimum heat transfer characteristics of the battery pack with dielectric fluid immersion cooling. The heat transfer characteristics of a battery pack with dielectric fluid immersion cooling are further improved for triangular fin structures with a base length -to -height ratio (A/B) of 4.304. The research outputs from the present work could be referred to as a database to commercialize the dielectric fluid immersion cooling for the efficient battery thermal management system at fast and higher charging/discharging rates. [ABSTRACT FROM AUTHOR]