4.7 Article

Prediction of experimental thermal performance of new designed cold plate for electric vehicles' Li-ion pouch-type battery with artificial neural network

Related references

Note: Only part of the references are listed.
Article Energy & Fuels

An experimental study on the comparative analysis of the effect of the number of data on the error rates of artificial neural networks

Andac Batur Colak

Summary: The study investigated the impact of the amount of data used in the design of artificial neural networks on the predictive accuracy of ANNs for specific heat values of Al2O3/water nanofluid. The results showed that while ANNs are capable of accurately predicting specific heat values, a decrease in the amount of data led to a decrease in prediction performance.

INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2021)

Article Thermodynamics

Channel parameters for the temperature distribution of a battery thermal management system with liquid cooling

Yuzhang Ding et al.

Summary: This study investigates and quantifies the effect of variables such as channel count, channel aspect ratio, and channel inlet layout on the cooling ability of a liquid cooling system. Results show that increasing the aspect ratio of the rectangular channel can reduce the maximum temperature and temperature difference of the Li-ion battery pack, but excessive increase may lead to temperature differences. Temperature uniformity can be significantly improved by adopting an alternating arrangement in the channel inlet design.

APPLIED THERMAL ENGINEERING (2021)

Article Thermodynamics

A novel battery thermal management system using nano-enhanced phase change materials

Ravindra Jilte et al.

Summary: The study introduces a novel modified battery module configuration using two-layer nanoparticle enhanced phase change materials, which shows better cooling performance for Li-ion cells in electric vehicles. The arrangement of m x n x p maintains cell temperature below 46 degrees C even at a hot ambient temperature of 40 degrees C, indicating the potential of the proposed system for efficient battery thermal management.

ENERGY (2021)

Article Thermodynamics

Nusselt number analysis from a battery pack cooled by different fluids and multiple back-propagation modelling using feed-forward networks

Imran Mokashi et al.

Summary: This article analyzes the heat transfer situation in a battery pack cooled by flowing fluid using artificial neural network models. It is found that conductivity ratio and heat generation term do not improve the average Nusselt number (Nu(avg), while Prandtl number and Reynolds number vary it significantly in each step. Additionally, Nu(avg) is found to continuously increase with increasing Re, but for oils, an increase in Pr and Re results in a significant decrease in Nu(avg).

INTERNATIONAL JOURNAL OF THERMAL SCIENCES (2021)

Article Engineering, Chemical

Comprehensive study concerned graphene nano-sheets dispersed in ethylene glycol: Experimental study and theoretical prediction of thermal conductivity

Muhammad Ibrahim et al.

Summary: The study compared the thermal conductivity of graphene nano-sheets (GNs)/ethylene glycol (EG) nanofluid with EG alone, showing that the presence of nanoparticles enhances the thermal conductivity of EG. Additionally, loading GNs into EG reversed the temperature dependency of thermal conductivity, with nanofluid showing increased thermal conductivity as temperature rises. The positive effects of nanoparticles on thermal conductivity decreased with higher nanoparticle content, and adding GNs strengthened the impact on thermal conductivity with increasing temperature.

POWDER TECHNOLOGY (2021)

Article Physics, Condensed Matter

Artificial intelligence approach on predicting current values of polymer interface Schottky diode based on temperature and voltage: An experimental study

Tamer Guzel et al.

Summary: A neural network model was developed to predict the current values of a 6H?SiC/MEH-PPV Schottky diode with a polymer interface based on temperature and voltage. The model showed high accuracy with an average error rate of -0.15% in predicting the current values.

SUPERLATTICES AND MICROSTRUCTURES (2021)

Article Engineering, Chemical

Thermophysical properties improvement of a common liquid by adding reduced graphene oxide: An experimental study

Han Yu et al.

Summary: The rheological behavior of a water-based nanofluid containing reduced graphene oxide nanoparticles was examined. The nanofluid exhibited non-Newtonian behavior and its viscosity varied with concentration and temperature. By utilizing curve fitting and artificial neural network, a model to simulate and predict the behavior of nanofluids was successfully developed, indicating its potential applications in various industries.

POWDER TECHNOLOGY (2021)

Article Engineering, Multidisciplinary

Li-ion battery temperature estimation based on recurrent neural networks

YuHeng Jiang et al.

Summary: The study proposes using two types of recurrent neural networks to estimate the surface temperature of lithium-ion batteries under different ambient temperatures, showing that the two RNNs can achieve accurate real-time battery temperature estimation with a maximum temperature estimation error of approximately 0.75 degrees Celsius and a correlation coefficient greater than 0.95 between estimated and measured temperature curves.

SCIENCE CHINA-TECHNOLOGICAL SCIENCES (2021)

Article Thermodynamics

Experimental investigation of thermal performance of novel cold plate design used in a Li-ion pouch-type battery

Orhan Kalkan et al.

Summary: The study investigated the thermal performance of water-cooled cold plates used in thermal management of batteries for electric vehicles. It found that lower coolant inlet temperature has a significant impact on battery surface temperature, while the use of mini channel cold plate resulted in a significant reduction in battery surface temperature and improved temperature homogeneity.

APPLIED THERMAL ENGINEERING (2021)

Article Energy & Fuels

A novel comparative investigation of the effect of the number of neurons on the predictive performance of the artificial neural network: An experimental study on the thermal conductivity of ZrO2 nanofluid

Andac Batur Colak

Summary: This study investigated the impact of the number of neurons on the predictive performance of artificial neural networks using experimental data. The results showed that increasing the number of neurons could improve performance, but adding too many neurons does not necessarily enhance predictive capabilities.

INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2021)

Article Energy & Fuels

Real-time core temperature prediction of prismatic automotive lithium-ion battery cells based on artificial neural networks

Jan Kleiner et al.

Summary: An innovative NARX network was developed and compared to traditional feedforward networks for temperature prediction in Li-ion batteries, demonstrating higher accuracy and robustness. In terms of long-term prediction and dynamic applications, the NARX network showed superior performance.

JOURNAL OF ENERGY STORAGE (2021)

Article Energy & Fuels

Estimation of thermal effect of different busbars materials on prismatic Li-ion batteries based on artificial neural networks

Ozge Yetik et al.

Summary: The study evaluated the effects of different busbar materials, air velocities, and temperatures on battery modules, and estimated the data using Artificial Neural Networks. Silver busbar material showed the best result.

JOURNAL OF ENERGY STORAGE (2021)

Article Thermodynamics

EXPERIMENTAL ANALYSIS WITH SPECIFIC HEAT OF WATER-BASED ZIRCONIUM OXIDE NANOFLUID ON THE EFFECT OF TRAINING ALGORITHM ON PREDICTIVE PERFORMANCE OF ARTIFICIAL NEURAL NETWORK

Andac Batur Colak

Summary: This study investigated the impact of different training algorithms on the prediction performance of artificial neural networks, finding that the network designed with Bayesian regularization had the highest performance, while the one developed with scaled conjugate gradient had the lowest.

HEAT TRANSFER RESEARCH (2021)

Article Chemistry, Physical

The thermal conductivity, viscosity, and cloud points of bentonite nanofluids with n-pentadecane as the base fluid

Feridun Esmaeilzadeh et al.

JOURNAL OF MOLECULAR LIQUIDS (2020)

Review Thermodynamics

Review on battery thermal management system for electric vehicles

Jaewan Kim et al.

APPLIED THERMAL ENGINEERING (2019)

Article Thermodynamics

Heat dissipation optimization of lithium-ion battery pack based on neural networks

Xiao Qian et al.

APPLIED THERMAL ENGINEERING (2019)

Article Energy & Fuels

Application of artificial neural networks (ANN) for vapor-liquid-solid equilibrium prediction for CH4-CO2 binary mixture

Abulhassan Ali et al.

GREENHOUSE GASES-SCIENCE AND TECHNOLOGY (2019)

Article Thermodynamics

Thermal management optimization of a prismatic battery with shape-stabilized phase change material

Weixiong Wu et al.

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER (2018)

Review Thermodynamics

Thermal issues about Li-ion batteries and recent progress in battery thermal management systems: A review

Huaqiang Liu et al.

ENERGY CONVERSION AND MANAGEMENT (2017)

Article Nanoscience & Nanotechnology

Evaluation of thermal conductivity of MgO-MWCNTs/EG hybrid nanofluids based on experimental data by selecting optimal artificial neural networks

Masoud Vafaei et al.

PHYSICA E-LOW-DIMENSIONAL SYSTEMS & NANOSTRUCTURES (2017)

Article Electrochemistry

Thermal Management of Large-Format Prismatic Lithium-Ion Battery in PHEV Application

Henrik Lundgren et al.

JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2016)

Article Thermodynamics

Prediction of thermal conductivity of various nanofluids using artificial neural network

Ebrahim Ahmadloo et al.

INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER (2016)

Article Thermodynamics

Experimental and theoretical investigations of heat generation rates for a water cooled LiFePO4 battery

S. Panchal et al.

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER (2016)

Review Chemistry, Physical

A review on the key issues for lithium-ion battery management in electric vehicles

Languang Lu et al.

JOURNAL OF POWER SOURCES (2013)