Results 201 to 210 of about 13,049 (244)

Dual-phase optimized deep learning framework for accurate, efficient, and robust battery SoC estimation. [PDF]

Sci Rep
R S, Mani G.
europepmc   +1 more source

Cycle based state of health estimation of lithium ion cells using deep learning architectures. [PDF]

Sci Rep
Bairwa B, Pareek K, Jadoun VK.
europepmc   +1 more source

State-of-Charge Estimation of Medium- and High-Voltage Batteries Using LSTM Neural Networks Optimized with Genetic Algorithms. [PDF]

Sensors (Basel)
Carrera R, Quiroz L, Guevara C, Acosta-Vargas P.   +3 more
europepmc   +1 more source

Role of deep learning in battery management system (BMS) for electric vehicles – A review

Energy Reports
Rasel Ahmed, Md. Shaharia Hossen, Nusrat Tabassum Tithi, Humayra Khatun, Kamrul Hasan Manik, Juhi Jannat Mim, Nayem Hossain   +6 more
openaire   +1 more source

Lithium battery fault diagnosis by integrating improved EMD decomposition algorithm and 2DCNN. [PDF]

PLoS One
Yin X, Wang H, Meng X, Zhu H, Zhong L, Zhan W, Pu Y.   +6 more
europepmc   +1 more source

Design of an Aging Estimation Block for a Battery Management System (BMS) :  

, 2013
openaire   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Battery-Management System (BMS) and SOC Development for Electrical Vehicles

IEEE Transactions on Vehicular Technology, 2011
Battery monitoring is vital for most electric vehicles (EVs), because the safety, operation, and even the life of the passenger depends on the battery system. This attribute is exactly the major function of the battery-management system (BMS)-to check and control the status of battery within their specified safe operating conditions.
Ka Wai Eric Cheng, B. P. Divakar, Hongjie Wu, Kai Ding, Ho Fai Ho   +4 more
openaire   +3 more sources