Journal ArticleDOI
A multi-model probability SOC fusion estimation approach using an improved adaptive unscented Kalman filter technique
Yanwen Li,Chao Wang,Jinfeng Gong +2 more
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TLDR
In this paper, an improved adaptive unscented Kalman filter (AUKF) approach is developed for measurement noise variance online update based on the idea of orthogonality between residual and innovation during the estimation.About:
This article is published in Energy.The article was published on 2017-12-15. It has received 69 citations till now. The article focuses on the topics: State of charge & Kalman filter.read more
Citations
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Journal ArticleDOI
Co-estimation of lithium-ion battery state of charge and state of temperature based on a hybrid electrochemical-thermal-neural-network model
TL;DR: Experimental results illustrate that proposed ETNN-UKF can rapidly eliminate initial errors and provide satisfactory co-estimation performance, and a neural network is incorporated to enhance the performance of sub-models.
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A Sensor Fault Diagnosis Method for a Lithium-Ion Battery Pack in Electric Vehicles
TL;DR: A simple and effective model-based sensor fault diagnosis scheme is developed to detect and isolate the fault of a current or voltage sensor for a series-connected lithium-ion battery pack and the experimental and simulation results validate the effectiveness of the proposed sensor fault diagnosed scheme.
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A GRU-RNN based momentum optimized algorithm for SOC estimation
TL;DR: Simulation results verify that the momentum optimized GRU-RNN model can accurately and effectively estimate the SOC of the lithium battery.
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State of charge estimation for electric vehicle power battery using advanced machine learning algorithm under diversified drive cycles
TL;DR: The proposed model under different drive cycles show remarkable advancement in state of charge estimation with high potential to overcome the drawbacks in traditional methods and therefore provides an alternative approach in stateof charge estimation.
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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.
References
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Journal ArticleDOI
A comparative study of equivalent circuit models for Li-ion batteries
TL;DR: In this paper, a comparative study of twelve equivalent circuit models for Li-ion batteries is presented, which are selected from state-of-the-art lumped models reported in the literature.
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A review on lithium-ion battery ageing mechanisms and estimations for automotive applications
Anthony Barré,Benjamin Deguilhem,Sebastien Grolleau,Mathias Gerard,Frédéric Suard,Delphine Riu +5 more
TL;DR: In this paper, the authors present a summary of techniques, models, and algorithms used for battery ageing estimation, going from a detailed electrochemical approach to statistical methods based on data, and their respective characteristics are discussed.
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Adaptive Kalman Filtering for INS/GPS
Ahmed Mohamed,K. P. Schwarz +1 more
TL;DR: The detailed development of an innovation-based adaptive Kalman filter for an integrated inertial navigation system/global positioning system (INS/GPS) is given, based on the maximum likelihood criterion for the proper choice of the filter weight and hence the filter gain factors.
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Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles
TL;DR: In this paper, the methods for monitoring the battery state of charge, capacity, impedance parameters, available power, state of health, and remaining useful life are reviewed with the focus on elaboration of their strengths and weaknesses for the use in on-line BMS applications.
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Combined State of Charge and State of Health estimation over lithium-ion battery cell cycle lifespan for electric vehicles
TL;DR: In this paper, a combined state of charge (SOC) and SOH (State Of Health) estimation method over the lifespan of a lithium-ion battery is proposed, where the SOH is estimated in real-time and the capacity and internal ohmic resistance are updated offline.