Lithium Battery State-of-Charge Estimation Based on a Bayesian Optimization Bidirectional Long Short-Term Memory Neural Network

Lithium Battery State-of-Charge Estimation Based on a Bayesian Optimization Bidirectional Long Short-Term Memory Neural Network

State of charge (SOC) is the most important parameter in battery management systems (BMSs), but since the SOC is not a directly measurable state quantity, it is particularly important to use advanced strategies for accurate SOC estimation. In this paper, we first propose a bidirectional long short-t...

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Bibliographic Details
Main Authors: Wang, Y. (Author), Yang, B. (Author), Zhan, Y. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Battery management systems
Battery state of charge
Bayesian optimization
Bayesian optimization algorithm
Bayesian optimization algorithms
bidirectional long short-term memory neural network
Bidirectional long short-term memory neural network
Brain
Charging (batteries)
Data characteristics
Lithium batteries
lithium battery
Long short-term memory
Mean square error
Memory modeling
Network topology
Neural-networks
Optimization
Parameter estimation
state of charge
State-of-charge estimation
States of charges
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