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Dual-phase optimized deep learning framework for accurate, efficient, and robust battery SoC estimation. [PDF]
R S, Mani G.
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Cycle based state of health estimation of lithium ion cells using deep learning architectures. [PDF]
Bairwa B, Pareek K, Jadoun VK.
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State-of-Charge Estimation of Medium- and High-Voltage Batteries Using LSTM Neural Networks Optimized with Genetic Algorithms. [PDF]
Carrera R +3 more
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Role of deep learning in battery management system (BMS) for electric vehicles – A review
Rasel Ahmed +6 more
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Lithium battery fault diagnosis by integrating improved EMD decomposition algorithm and 2DCNN. [PDF]
Yin X +6 more
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Design of an Aging Estimation Block for a Battery Management System (BMS) :
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Battery-Management System (BMS) and SOC Development for Electrical Vehicles
IEEE Transactions on Vehicular Technology, 2011Battery 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 +4 more
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