Journal of Energy Storage, Год журнала: 2024, Номер 103, С. 114370 - 114370
Опубликована: Окт. 30, 2024
Язык: Английский
Journal of Energy Storage, Год журнала: 2024, Номер 103, С. 114370 - 114370
Опубликована: Окт. 30, 2024
Язык: Английский
Applied Thermal Engineering, Год журнала: 2024, Номер unknown, С. 125266 - 125266
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
4Journal of Energy Storage, Год журнала: 2025, Номер 111, С. 115405 - 115405
Опубликована: Янв. 14, 2025
Язык: Английский
Процитировано
0Journal 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
0Journal of Power Sources, Год журнала: 2025, Номер 641, С. 236793 - 236793
Опубликована: Март 30, 2025
Язык: Английский
Процитировано
0Case Studies in Thermal Engineering, Год журнала: 2024, Номер 63, С. 105246 - 105246
Опубликована: Окт. 16, 2024
Язык: Английский
Процитировано
2Energy 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
2Journal of Energy Storage, Год журнала: 2024, Номер 107, С. 114958 - 114958
Опубликована: Дек. 8, 2024
Язык: Английский
Процитировано
1Journal of Energy Storage, Год журнала: 2024, Номер 99, С. 113351 - 113351
Опубликована: Авг. 25, 2024
Язык: Английский
Процитировано
0Journal of Energy Storage, Год журнала: 2024, Номер 103, С. 114370 - 114370
Опубликована: Окт. 30, 2024
Язык: Английский
Процитировано
0