The global environmental pollution issue and global warming caused by internal combustion engines (ICE) have prompted automotive manufacturers to pioneer the development of emission-free or pure electric vehicles. The Indian government declared that all ICE cars will be replaced by electric vehicles by 2030. Thus, after 2030, ICE vehicle scrapping will be prevented by retrofitting. Transforming traditional cars into electric vehicles in Indian markets reduces emissions and enhances sustainability. This work aims to transform the Maruti Suzuki Zen petrol car into a fully electric vehicle while keeping its pristine transmission system with an onboard charging system. During the fieldwork, all unnecessary components of the ICE are removed to transform it into an electric vehicle. The E Zen’s maximum speed, gradeability, and driving range on both level and sloping roads were also examined. The performance was assessed using a 72 V, 144 Ah lithium-ion battery pack and an AC induction motor

Suryavanshi, Shweta S., Ghanegaonkar, Pravin M., Kawade, Ramesh K.

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99-07-01-0TOC

02/17/2025

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Tobolski, Sue

Cloud-Based Monitoring of Lithium-Ion Battery Management Systems for Health Estimation in Manufacturing Industries

2025-28-0200

02/07/2025

The increasing reliance on lithium-ion batteries in manufacturing necessitates advanced monitoring techniques to ensure their longevity and reliability. Cloud technology offers a solution by enabling real-time data collection, analysis, and accessibility, facilitating thorough monitoring and predictive maintenance. Digital twin technology, creating a virtual replica of the physical battery system, provides a platform for simulating real-world conditions and predicting potential issues before they arise. By integrating sensor data and historical usage patterns, the digital twin model can accurately predict battery degradation, aiding in timely maintenance strategies. This proactive approach enhances battery operational efficiency and extends lifespan, leading to cost savings and improved safety. The paper explores using cloud-based monitoring systems to enhance the health estimation and management of lithium-ion batteries. A comprehensive feasibility study on adopting battery digital

Zeeshan, Mohammad, Akre, Vineet

Crash Performance Study on High-Speed Electric Two-Wheeler Battery Enclosure

2025-28-0203

02/07/2025

The usage of Electric Vehicles (EVs) and the annual production rate have increased significantly over the years. This is due to the development of rechargeable electrical energy storage system (battery pack), which is the main power source for EVs. Lithium-ion batteries (LIBs) pack is predominantly used across all major vehicle categories such as 2-wheelers, 3-wheelers and light commercial vehicle. LIB is one of the high energy-dense sources of volume. However, LIBs have a challenge to pose a risk of short circuits and battery pack explosions, when exposed to damage scenarios. In the present study, the controlled crash analysis is performed for various velocities ranging from 50 kmph to 72 kmph against an obstruction directly and at an offset from the wheel, so as to mimic the real-world crash of high-speed two-wheelers. The behavior of the battery enclosure is examined through evaluating the structural integrity of the battery enclosure used in a realistic two-wheeler after crash at

Venkatesan Sr, Aiyappan, Nelson, N Rino, Hariharan Nair, Adarsh

Modeling and Simulation Analysis of Thermal Management System for Hydrogen Fuel Cell Vehicle

2025-01-7091

01/31/2025

An effective vehicle integrated thermal management system (ITMS) is critical for the safe and efficient operation of proton exchange membrane fuel cell (PEMFC) vehicles. This paper takes a fuel cell vehicle (FCV) as the research object, comprehensively considers the vehicle layout environment and thermal management requirements, and designs a complete thermal management system for FCV. The key components are selected and designed to match the performance and the control strategy of ITMS of fuel cell vehicle is developed. To do that, the ITMS model is established based on the heating principle and heat transfer theory of each key component. Then, the ITMS under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) operating conditions at different ambient temperatures are simulated and analyzed by selecting indicators such as coolant flow rate and temperature. Under the ambient temperature of 40°C, the temperature of PEMFC is basically stable between 78 °C and 83°C, the coolant outlet

Jiang, Qi, Xiong, Shusheng, Wang, Yupeng, Zhu, Shaopeng, Chen, Huipeng

Advanced SOH and SOC Prediction Models for Lithium-Ion Batteries: Integrating Machine Learning with Battery Management Systems

2025-01-7015

01/31/2025

This paper focuses on the development and validation of predictive models for battery management systems, specifically targeting State of Health (SOH) and State of Charge (SOC) estimation, as well as the design of a comprehensive Battery Management System (BMS). The study begins by establishing and evaluating SOH prediction models, employing both linear regression and Long Short-Term Memory (LSTM) algorithms. Comparative analysis is conducted to assess the prediction accuracy between Recurrent Neural Networks (RNN) and LSTM, highlighting the superior performance of the LSTM algorithm in forecasting battery health. The second part of the paper addresses SOC estimation, outlining common methods and introducing an Extended Kalman Filter (EKF) algorithm for real-time SOC prediction. The EKF model is constructed through three primary stages: the establishment of the observed signal section, the ECU section, and the algorithmic structure itself. Rigorous validation confirms the EKF model’s

Yuan, Chuo, Bao, Zhiming, Li, Weizhuo, Liu, Zezheng, Zhao, Xu, Jiao, Kui

Design and Performance Optimization of an Air-Cooled Battery Thermal Management System Based on Flow Field Disturbance

2025-01-7013

01/31/2025

As global energy concerns and environmental challenges intensify, the automotive industry is rapidly transitioning toward more sustainable solutions, with new energy vehicles, particularly battery electric vehicles (BEVs), at the forefront. BEVs depend on lithium-ion batteries due to their high energy efficiency, large storage capacity, and ability to support long-range driving. However, maintaining optimal performance, safety, and battery longevity is critical, especially during high-rate charging and discharging operations. To address these challenges, effective battery thermal management systems (BTMS) are essential. Poor thermal management can lead to overheating, reduced battery lifespan, and potential safety hazards. This study focuses on improving air-cooled BTMS, which are widely used for their cost-effectiveness, by introducing spoilers to enhance airflow within the cooling channels. By combining simulation with experimental methods, experiments on the air-cooled BTMS

An, Dou, Cui, Feifei, Meiwei, Wang, Wang, Chun, Xi, Huan

Correlation Analysis of Automotive Battery State-of-Health Indicators for Advanced Battery Management Systems

2025-01-7012

01/31/2025

With increasing global attention on environmental issues and the greenhouse effect, electric vehicles (EVs) have become a focal point for sustainable transportation solutions. Lithium-ion batteries are integral to EVs due to their high energy density, elevated operating voltage, and long service life. However, their performance is highly influenced by factors such as ambient temperature, charge and discharge rates, and aging processes. To enhance the safety, reliability, and efficiency of lithium-ion battery systems, it is critical to develop a robust and advanced battery management system (BMS) that can monitor battery states accurately and in real-time. A key aspect of BMS design is the estimation and prediction of the battery's state of health (SOH). Accurately characterizing SOH during actual usage conditions is essential for optimal battery performance and longevity. This study investigates various SOH indicator extraction methods reported in the literature, including features

Long, Tianfeng, Shang, Huaqing, Liu, Xiaoqi, Zhang, Pengcheng, Yue, Meiling, Meng, Jianwen

Prediction of Gear Defect Based on WPT & CEEMDAN & SVD

2025-01-7048

01/31/2025

After the defected gears are determined, a novel method, combined with wavelet packet decomposition, complementary ensemble empirical mode decomposition with adaptive noise and singular value decomposition, is put forward. It is utilized to exclude disturbance of irrelevant signals that generated by the defect gears. Firstly, wavelet packet decomposition is used to extract the defect signals and retain original features. The processed signal is called S1 and the irrelevant frequency bands could be filtered out. Secondly, complementary ensemble empirical mode decomposition with adaptive noise decomposes S1 into a series of intrinsic modal functions. The correlations between S1 and intrinsic modal functions are analyzed. The intrinsic modal functions that are highly correlated with S1 are screened out and reconstructed into a new signal, called S2. The disturbance of irrelevant signals could be further filtered out, but some of them still disturb the judgement. Thirdly, singular value

Gu, Junqing, Zuo, Yueyun, Zhang, Ni, Deng, Feng, Wu, Xiaolong

Analysis of Influencing Factors in the Thermal Management System of Cylindrical Lithium-Ion Batteries Based on CPCM under High Discharge Rates

2025-01-7064

01/31/2025

With the rapid development of new energy vehicles, lithium-ion batteries (LIBs) have been widely used in the automotive sector. The performance and safety of LIBs in electric vehicles (EVs) are significantly influenced by operating temperature, making the development of an effective battery thermal management system (BTMS) crucial. In recent years, phase change material (PCM)-based BTMS technology has been recognized as one of the most promising solutions. Compared to traditional air and liquid cooling systems, PCM cooling technology exhibits superior cooling performance due to its large latent heat and efficient heat dissipation capabilities, while also eliminating the need for additional pump power consumption. Therefore, in-depth research on PCM cooling technology is of significant academic and practical value for enhancing the effectiveness and safety of power battery thermal management. This study investigates the effects of thermal conductivity, melting point, and thickness of

Lv, Kang-Min, Su, Chu-Qi, Wang, Yi-Ping, Yuan, Xiao-Hong, Liu, Xun

Core Temperature Estimation for Lithium-Ion Batteries Based on Extended Kalman Filter

2025-01-7020

01/31/2025

Lithium-ion batteries have become the preferred energy storage component for electric vehicles due to their excellent overall performance. However, during use, they generate heat, causing the battery temperature to rise and the internal and surface temperatures to be inconsistent, affecting the battery’s performance and even leading to thermal safety issues. It is difficult to obtain real-time internal temperature measurements in actual vehicles. Therefore, accurately estimating the internal temperature of the battery, promptly detecting thermal faults, and ensuring efficient and safe operation of the battery are of great importance. This paper establishes a dual-state thermal model based on extended Kalman filtering for a square ternary lithium battery, which achieves real-time updating of external thermal resistance and online estimation of core battery temperature. For this type of lithium battery and its battery module, an experimental platform was set up, and basic performance

Jin, Yuntao, Liu, Xuanzhuo, Zhang, Zhengjie, Peng, Zhaoxia, Yang, Shichun

Multi-step Prediction of Battery Temperature and Thermal Fault Diagnosis Based on Informer

2025-01-7019

01/31/2025

Lithium-ion batteries are prone to thermal failures under extreme conditions, leading to thermal runaway and safety risks such as fire or explosion. Therefore, effective temperature prediction and diagnosis are crucial. This paper proposes a thermal fault diagnosis method based on the Informer time series model. By extracting temperature-related features and conducting correlation analysis, a 9-dimensional input parameter matrix is constructed. Experimental results show that the model can maintain an absolute temperature prediction error within 0.5°C when predicting 10 seconds in advance, with higher accuracy than the LSTM model. Additionally, a three-level warning mechanism based on the forgetting coefficient further enhances diagnostic accuracy. Validation using test data and real vehicle data demonstrates that this method can efficiently diagnose and locate thermal faults in batteries, with low computational costs, making it suitable for online applications.

Sun, Yefan, Zhu, Xiaopeng, Zhang, Zhengjie, Peng, Zhaoxia, Yang, Shichun, Liu, Xinhua

Experimental and Modeling Investigation on Thermal Runaway Propagation and Venting Gas in Cell-to-Chassis Lithium-Ion Battery System

2025-01-7011

01/31/2025

Thermal runaway propagation (TRP) within lithium-ion batteries (LIBs) poses critical barriers to the safe operation and large-scale application of cell-to-chassis (CTC) batteries. Such events can lead to severe safety incidents, including explosions and fires, in systems utilizing these batteries. However, there is a lack of research on the thermal runaway model coupled with vented gases at the CTC systems. In this study, a thermal runaway coupling model for the battery pack system was established utilizing Star-CCM+ software, allowing for the examination of thermal runaway propagation characteristics and vented gas characteristics a within power battery systems based on the measured parameters of battery thermal safety characteristic. The simulation results indicated that once thermal runaway becomes uncontrollable, combustible flue gases escape through the exhaust hole located on the side plate of the cell, thereby facilitating heat transfer to adjacent cells. The primary components

Ma, Niya, Zhang, Anwei, Zhou, Wentai, Zhou, You, Jia, Yuan, Fan, Zehong

A Multi-Time Scale FFRLS-AEKF Joint Algorithm for Lithium-Ion Battery State of Charge Estimation

2025-01-7000

01/31/2025

Accurate and reliable SOC estimation plays a vital role in the engineering application and development of LIBs. A multi-time scale joint algorithm combining FFRLS and AEKF is introduced in this paper. The FFRLS algorithm is employed for online parameter identification of a second-order resistance-capacitance ECM, while the AEKF algorithm estimates the SOC. To account for the time-varying nature of model parameters and SOC, different sampling periods are selected, enabling the parameter identification and SOC estimation processes to operate on distinct time scales. Experimental results demonstrate that, under constant current conditions at room temperature, the multi-time scale FFRLS-AEKF joint algorithm can maintain a high level of accuracy while reducing the computational burden, with MAE and RMSE values of 0.0111 and 0.0129, respectively. Simultaneously, a public data set is used to prove the application of the algorithm in complex operating conditions, and the computed results of

Liang, Dan, Yang, Bo, Liu, Bing, Liu, Shuai, Cao, Chang

Toward the Progression of Sustainable Structural Batteries: State-of-the-Art Review

13-05-03-0020

01/02/2025

In order to deploy renewable energy sources for balanced power generation and consumption, batteries are crucial. The large weight and significant drain on the energy efficiency of conventional batteries urge the development of structural batteries storing electrical energy in load-bearing structural components. With the current shift to a green economy and growing demand for batteries, it is increasingly important to find sustainable solutions for structural batteries as well. Sustainable structural batteries (SSBs) have strong attraction due to their lightweight, design flexibility, high energy efficiency, and reduced impact on the environment. Along with sustainability, these structural batteries increase volumetric energy density, resulting in a 20% increase in efficiency and incorporate energy storage capabilities with structural components, realizing the concept of massless energy storage. However, the significant problems in commercializing SSBs are associated with their

Kusekar, Sambhaji Kashinath, Pirani, Mahdi, Birajdar, Vyankatesh Dhanraj, Borkar, Tushar, Farahani, Saeed

Deep Learning Approaches to Predict the Life Cycle of Lithium-Ion Batteries in Electric Vehicles

2024-36-0181

12/20/2024

Predictive maintenance is crucial for Industry 4.0, and deep neural networks are a promising approach for predicting the capacity of electric batteries. However, few applications effectively utilize neural networks for this purpose with lithium-ion batteries. In this work, different deep learning models are developed, starting with simple neural networks, dense neural networks, convolutional networks, and recurrent networks. Using a public domain dataset, training, testing, and validation datasets were generated to predict battery capacity as a function of the number of cycles. Despite the limited number of samples in the dataset, deep learning techniques are employed to ensure robust prediction performance. The work presents the loss functions for each iteration of the algorithms and the average absolute error. The models made good generalizations over the test dataset within a short prediction time window. Finally, the work presents an average absolute error below 0.3, ensuring good

Branco, César Tadeu Nasser Medeiros

Recycling and Resynthesis of Cathode Materials from Lithium-Ion Batteries for EVs

2024-36-0110

12/20/2024

The cost of electric vehicles (EVs) is significantly influenced by lithium-ion batteries, which typically account for about 40% of the total price, primarily due to the critical minerals content. Notably, minerals for cathode production are prone to scarcity and market price fluctuations. Moreover, the extraction of these minerals through mining activities poses substantial environmental challenges, including carbon emissions and resource depletion. In response to these concerns, recycling emerges as strategic to ensure the sustainability of electrification and secure the mineral supply chain. This paper presents findings from a study on recycling EV batteries using hydrometallurgical processes, encompassing the resynthesis of cathode materials utilizing recycled resources. The hydrometallurgical method exhibited an extraction efficiency surpassing 90%, with no direct CO2 emissions. Validation of the resynthesis phase involved the fabrication of cells with resynthesized cathodes

Obara, Rafael Brisolla, Erthal, Leopoldo, Souza, Cleiton Oliveira, Roggerio, Leonardo, Freitas, Heverson Renan, Lima, Ana Luiza Lorenzen, Bassani, Jean Carlos

Synthesis and Characterization of Advanced Multi Nanoparticle Based Nanofluid Stabilized by Surfactants

2024-28-0139

12/05/2024

Recently, there has been a growing emphasis on Thermal Management Systems (TMS) for Lithium-ion battery packs due to safety concerns related to fire risks when temperatures exceed operating limits. Elevated temperatures accelerate electrochemical reactions, leading to cell degradation and reduced electronic system performance. These conditions can cause localized hotspots and hinder heat dissipation, increasing the risk of thermal runaway due to high temperatures, flammable gases, and heat-producing reactions. To tackle these issues, many automotive manufacturers employ indirect liquid cooling techniques to maintain battery pack and electronic system temperatures within safe limits. Engineered nanofluids, particularly those containing multi-nanoparticles dispersed in water and ethylene glycol, are being explored to enhance electrical safety in case of accidental exposure to electrical systems in EVs. This paper focuses on the experimental characterization of nanofluid containing

Nahalde, Sujay, Honrao, Gaurav, More, Hemant

Review on Integrated Thermal Management Systems of Electric Vehicles

2024-28-0227

12/05/2024

Electric Vehicles use Li-ion batteries due to their high energy and power densities. Performance of Li-ion cell is sensitive to temperature. Temperature control of these batteries becomes very important to provide safety and performance under different working conditions. This paper review different integrated thermal management system developed for Electric Vehicles. integrated thermal management content. Battery thermal management, Cabin thermal management and Electric drive thermal management. These systems share some common objectives and common parts. Integration of these systems will help to optimize the number of components in the Electric Vehicles thermal management system. The integrated thermal management system also helps to optimize the weight and use of waste heat to heat the cabin or battery. This will help in optimization of energy consumed by the thermal management system and range improvement. Integrating different systems which content refrigerant and coolant circuit

Mhaske, Pramodkumar Chimaji

A Comprehensive Review of Advancement in Anode Material with Modified Architecture for Lithium-Ion Batteries

2024-28-0142

12/05/2024

Anode material, responsible for the critical storage and release of lithium ions during charge and discharge cycles, holds paramount importance. By strategically altering the material design and composition of the current graphite, researchers aim to significantly improve fast charging capabilities, energy density, cycling stability and overall electrochemical kinetics within Lithium ion battery. Anode materials operate through three primary mechanisms: insertion/de-insertion that is allowing for reversible lithium ion accommodation within the host structure; alloying, where lithium ions form chemical bonds with the anode material; and conversion reactions, involving the creation of new phases during charge/discharge cycles. This review delves into a captivating array of advanced anode materials with the potential to surpass the limitations of traditional graphite. Carbon-based nanomaterials like graphene and its derivative, reduced graphene oxide, offer exceptional conductivity and

Borkar, Shweta, Nahalde, Sujay, Ruban J S, Alwin, More, Hemant

Performance Rating of Lithium-Ion Battery Module

J1798/2_202412 (Current)12/05/2024

This document provides a recommended electrical performance testing guideline for LIBM, which makes up an xEV (Battery Electric Vehicles and Hybrid Electric Vehicles) battery pack system. This testing guideline may also be used for other applications, such as stationary, vessel, and aircraft. However, using the guideline for other applications should be determined by the users of this document. Users of this document may also be interested in conducting tests on battery cells and/or battery packs. To avoid conducting potentially redundant tests between cells, modules, and packs, this document does not specify which tests need to be conducted. Determination of which tests need to be conducted is at the user’s discretion and should be based on individual module applications. Rather than specifying which tests need to be conducted, this document describes how each test is to be conducted. This document provides a matrix of tests that can be selectively picked for the application

Battery Standards Testing Committee

Equivalent Circuit Modeling of Sodium-Ion Batteries Incorporating Temperature Effects: A Comprehensive Investigation

2024-28-0225

12/05/2024

The transition from Internal Combustion Engine (ICE) Vehicles to Electric Vehicles (EVs) has catalyzed significant advancements in battery technology, prioritizing safer and more reliable energy storage solutions. Although Lithium Iron Phosphate (LFP) batteries are recognized for their safety, they rely on critical and market-volatile elements such as copper, lithium, and graphite. To address these challenges, sodium-ion batteries (SIBs) have emerged as sustainable alternatives that are particularly suited for low-speed EVs. Ensuring the seamless integration of SIBs into EV battery packs necessitates preparedness for the rapid evolution of SIB technology. Model-based approaches, including Equivalent Circuit Models (ECMs), are crucial for developing advanced Battery Management Systems (BMSs) and State of Charge (SoC) estimation algorithms that enable precise battery control. This study comprehensively evaluates various order Resistance-Capacitance (RC) ECM configurations to accurately

Ns, Farhan Ahamed Hameed, Gupta, Shubham, Jha, Kaushal

Investigation on Thermal Performance of Battery Cooling Plate for Lithium-Ion Battery

2024-28-0259

12/05/2024

Electric vehicles are regarded to be the most effective way to lower emissions of greenhouse gases from the transportation industry. Lithium-ion batteries are rechargeable and ideally suited for vehicle electrification due to their high specific energy and energy density in comparison to other batteries. Electric vehicle performance greatly depends on the efficient operation of lithium-ion battery. Battery thermal management plays a crucial role in ensuring optimum vehicle operation. Heat dissipation from the battery should be dealt with, for safe operation and to prolong the battery life cycle. To achieve the battery’s optimal temperature, an efficient cooling system should be established. The battery cooling plate is an essential component that is necessary for heat transfer from the battery pack to the coolant. Five different battery cooling plates with linear dimple, staggered dimple, straight channel, wave channel and splitter channel are modeled for computational fluid dynamics

K, Muthukrishnan, S, Saikrishna, K, Keshavbalaje

Effect of Vibrational Abuse on the Electrodes of Nickel Manganese Cobalt (NMC) and Lithium Iron Phosphate (LFP) 18650 Cells

2024-28-0156

12/05/2024

In light of the growing demand for Electric vehicles (EVs) as a sustainable mode of transportation, it becomes essential to understand the effect of various abuse conditions that batteries undergo. Vibrational abuse is a significant condition experienced by batteries in operation. Vibrations caused by road roughness, acceleration inertia, and other factors can affect key performance indicators such as cycle life, capacity retention, and safety. These cells undergo various chemical and mechanical reactions over time, leading to the degradation of components like the anode, cathode, electrolyte, separator, and current collector, resulting in reduced performance. Therefore, understanding battery degradation is important for managing system performance. This study is focused on a detailed analysis of Lithium Iron Phosphate (LFP) and Nickel Manganese Cobalt (NMC) cells subjected to vibrational abuse. Vibration testing was carried as per International Electrotechnical Commission (IEC

Manwatkar, Asmita Ashok, Pandit, Sachin Prabhakar, Santosh Jambhale, Medha, Mahagaonkar, Nitin

SoC Estimation for LFP Battery Using Extended Kalman Filter and Particle Filter with Adaptive Battery Parameters

2024-28-0223

12/05/2024

In recent years, Lithium Iron Phosphate (LFP) has become a popular choice for Li-ion battery (LIB) chemistry in Electric Vehicles (EVs) and energy storage systems (ESS) due to its safety, long lifecycle, absence of cobalt and nickel, and reliance on common raw materials, which mitigates supply chain challenges. State-of-charge (SoC) is a crucial parameter for optimal and safe battery operation. With advancements in battery technology, there is an increasing need to develop and refine existing estimation techniques for accurately determining critical battery parameters like SoC. LFP batteries' flat voltage characteristics over a wide SoC range challenge traditional SoC estimation algorithms, leading to less accurate estimations. To address these challenges, this study proposes EKF and PF-based SoC estimation algorithms for LFP batteries. A second-order RC Equivalent Circuit Model (ECM) was used as the dynamic battery model, with model parameters varying as a function of SoC and

Ns, Farhan Ahamed Hameed, Jha, Kaushal, Shankar Ram, C S

Electrical-Thermal Modelling and Analysis of Battery Energy System in Electric Vehicles

2024-28-0155

12/05/2024

The development and implementation of Lithium-ion (Li-ion) batteries, particularly in Automotive applications, requires substantial diagnostic and practical modelling efforts to fully understand the electrical and thermal characteristics in the batteries across various operating conditions. Electrical thermal modelling prompts the understanding of the battery electrical characteristics along with the thermal behavior beyond what is possible from experiments, and it provides a basis for exploring electrical and thermal management control strategies for batteries in electric vehicles (EVs). For replicating the electrical behavior of Li-ion batteries under varied operating situations, an equivalent circuit model (ECM) must be created. This model aids in forecasting the transient distribution of electrical and thermal properties at various operating states as well as estimating heat generation within the battery pack. The paper focus in the following application areas: An equivalent

Gupta, Gaurav

Numerical Simulation of Cooling Plates/Tubes of BTMS of Electric Vehicles by Changing Internal Structure and Coolant Mass Flow Rate

2024-28-0203

12/05/2024

The lithium-ion battery is the most common type of batteries in modern electric vehicles. During vehicle operation and battery charging, the temperature of the battery cells increases. The temperature of any battery must be controlled and maintained within a specified range to ensure maximum efficiency. Considering the overall thermal effect on the battery, a battery cooling system is of great importance in electric vehicles to maintain the temperature of the battery cells inside the battery pack. There are different types of systems for battery cooling, out of which the water cooled systems are very popular. They use a mixture of water and ethylene glycol to absorb heat from the battery cells. The coolant circulates through the tubes or cold plates surrounded by the cells to absorb the heat. The paper involves the study of variation on temperature and pressure drop including overall thermal performance on the batteries by changing the internal structure. The temperature of battery

Parayil, Paulson, Ahmad, Taufeeq, Dagar, Aakash, Goel, Arunkumar

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