Journal ArticleDOI
State-of-charge estimation of lithium-ion batteries using LSTM and UKF
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TLDR
A long short-term memory – recurrent neural network is proposed to model the sophisticated battery behaviors under varying temperatures and estimate battery SOC from voltage, current, and temperature variables and provides a satisfying SOC estimation under other temperatures which have no data trained before.About:
This article is published in Energy.The article was published on 2020-06-15. It has received 165 citations till now. The article focuses on the topics: State of charge & Battery (electricity).read more
Citations
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Journal ArticleDOI
Intelligent algorithms and control strategies for battery management system in electric vehicles: Progress, challenges and future outlook
M. S. Hossain Lipu,Mahammad A. Hannan,Tahia Fahrin Karim,Aini Hussain,Mohamad Hanif Md Saad,Afida Ayob,Md. Sazal Miah,T. M. Indra Mahlia +7 more
TL;DR: A comprehensive review of different intelligent approaches and control schemes of the battery management system in electric vehicle applications concerning their features, structure, configuration, accuracy, advantages, and disadvantages is delivered.
Journal ArticleDOI
State-of-charge estimation of LiFePO4 batteries in electric vehicles: A deep-learning enabled approach
TL;DR: A deep neural network (DNN) based method is proposed to estimate SOC with only 10-min charging voltage and current data as the input, which enables fast and accurate SOC estimation with an error of less than 2.03% over the entire battery SOC range.
Journal ArticleDOI
A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles
TL;DR: A review of the state-of-the-art online SOC and SOH evaluation technologies published within the recent five years in view of their advantages and limitations and suggests future work in the real-time battery management technology.
Journal ArticleDOI
A method for state-of-charge estimation of lithium-ion batteries based on PSO-LSTM
TL;DR: A long short-term memory neural network based on particle swarm optimization (PSO-LSTM), where the key parameters of LSTM are optimized by PSO algorithm, so that the data characteristics of lithium-ion battery can match the network topology.
Journal ArticleDOI
State of charge estimation for lithium-ion battery based on an Intelligent Adaptive Extended Kalman Filter with improved noise estimator
Daoming Sun,Xiaoli Yu,Chongming Wang,Cheng Zhang,Rui Huang,Quan Zhou,Tazdin Amietszajew,Rohit Bhagat +7 more
TL;DR: In this paper, the authors proposed an intelligent adaptive extended Kalman filter (IAEKF) method that can detect the moment of distribution change of EIS by the maximum likelihood function and then, the ICM is updated based on the EIS after that moment to improve the SOC estimation accuracy.
References
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Adam: A Method for Stochastic Optimization
Diederik P. Kingma,Jimmy Ba +1 more
TL;DR: This work introduces Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments, and provides a regret bound on the convergence rate that is comparable to the best known results under the online convex optimization framework.
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Dropout: a simple way to prevent neural networks from overfitting
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Simon Julier,Jeffrey Uhlmann +1 more
TL;DR: The motivation, development, use, and implications of the UT are reviewed, which show it to be more accurate, easier to implement, and uses the same order of calculations as linearization.