Heat transfer enhancement of microchannel using nano-encapsulated phase change material for fuel cell thermal management systems DOI
Changgui Xie, Xiao Yang

Journal of Energy Storage, Год журнала: 2024, Номер 103, С. 114370 - 114370

Опубликована: Окт. 30, 2024

Язык: Английский

Multifaceted thermal regulation in electrochemical batteries using cooling channels and foam-embedded phase change materials DOI Creative Commons

Mehdi Vahabzadeh Bozorg,

Juan F. Torres

Applied Thermal Engineering, Год журнала: 2024, Номер unknown, С. 125266 - 125266

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

4

Bio-based, flexible, and electrically insulating phase change materials for advanced battery thermal management DOI
Jianming Guo, Hongyuan Ding,

Jianghui Xie

и другие.

Journal of Energy Storage, Год журнала: 2025, Номер 111, С. 115405 - 115405

Опубликована: Янв. 14, 2025

Язык: Английский

Процитировано

0

Recent Progress of Nano-Cooling for Electric Vehicles Battery Thermal Management Systems: A Mini Review DOI Open Access
Abdul Rahim Abdullah,

Lu Hongkun,

M. M. Noor

и другие.

Journal of Physics Conference Series, Год журнала: 2025, Номер 2933(1), С. 012032 - 012032

Опубликована: Янв. 1, 2025

Abstract This paper investigates the use of nano-fluids in Battery Thermal Management Systems (BTMS) for electric vehicles (EVs), where they are essential safety and to extend battery life. As EV industry develops rapidly, thermal management is ensure efficient performance under diverse operating conditions. In this study, recent technology BTMS using nanoparticles including CNT, graphene metal oxides enhance efficiency cooling systems will be evaluated. The research methodology conducted a literature review based on different methods such as liquid systems, phase change materials (PCM), hybrid techniques assess how handled terms temperature regulation. According findings, can make operation heat conduction more lower temperatures while improving longevity by keeping its charge. PCM with nano-fluid together indicated deliver uniform fast cooling. Overall, find not only reinforces nanoparticle sustainable functionalities but also assists effort an eco-friendly green facilitating technological revolution upon vehicles.

Язык: Английский

Процитировано

0

Preventing thermal runaway in lithium-ion batteries with nano-porous structures: A critical review DOI

Garshasp Keyvan Sarkon,

Dogus Hurdoganoglu,

Berke Eyyamoglu

и другие.

Journal of Power Sources, Год журнала: 2025, Номер 641, С. 236793 - 236793

Опубликована: Март 30, 2025

Язык: Английский

Процитировано

0

Predicting temperature of a Li-ion battery under dynamic current using long short-term memory DOI Creative Commons
Jihye Han, Junyong Seo, Jihoon Kim

и другие.

Case Studies in Thermal Engineering, Год журнала: 2024, Номер 63, С. 105246 - 105246

Опубликована: Окт. 16, 2024

Язык: Английский

Процитировано

2

Optimizing Hybrid Active–Passive Thermal Management of Prismatic Li‐Ion Batteries Using Phase Change Materials and Porous‐Filled Mini‐Channels DOI

Ramanan Venkatesh,

Vara Prasad Bhemuni,

Dilip Shyam Prakash Chinnam

и другие.

Energy Storage, Год журнала: 2024, Номер 6(7)

Опубликована: Окт. 1, 2024

ABSTRACT Tackling climate change is crucial, and electrifying the vehicular transportation sector essential to reduce greenhouse gas emissions. Lithium‐ion (Li‐ion) batteries are highly efficient for electric vehicles (EVs) but face challenges such as thermal management, risk of runaway, high costs lithium cobalt. Overcoming these vital widespread adoption hybrid EVs. To overcome this drawback, article proposed a large‐kernel attention graph convolutional network (LKAGCN) with leaf in wind optimization algorithm (LWOA) named LKAGCN‐LWOA technique, which enhances management prismatic Li‐ion by integrating both active passive cooling techniques. The system incorporates phase materials (PCMs) porous‐filled mini‐channels regulate battery temperature effectively. LKAGCN analyze properties, conditions, PCM characteristics predict optimize behavior pack using LWOA. methods tune parameters system, ensuring regulation improved performance. method compared various existing neural (CNN), Taguchi method, Finite element model (FEM).

Язык: Английский

Процитировано

2

An innovative study on high entropy energy storage mg-Y-Ni-cu systems: Machine learning-driven optimization of electrical cycling in Ni-MH battery alloys DOI
Andaç Batur Çolak

Journal of Energy Storage, Год журнала: 2024, Номер 107, С. 114958 - 114958

Опубликована: Дек. 8, 2024

Язык: Английский

Процитировано

1

Nano-enhanced phase change materials for temperature regulation of a LiFePO4 lithium-ion pouch cell using CFD simulation DOI
Yang Zhang, Keping Zhang, Jiuxin Wang

и другие.

Journal of Energy Storage, Год журнала: 2024, Номер 99, С. 113351 - 113351

Опубликована: Авг. 25, 2024

Язык: Английский

Процитировано

0

Heat transfer enhancement of microchannel using nano-encapsulated phase change material for fuel cell thermal management systems DOI
Changgui Xie, Xiao Yang

Journal of Energy Storage, Год журнала: 2024, Номер 103, С. 114370 - 114370

Опубликована: Окт. 30, 2024

Язык: Английский

Процитировано

0