Lithium-Ion Battery State of Charge and Critical Surface Charge Estimation Using an Electrochemical Model-Based Extended Kalman Filter

Domenico, Domenico Di; Stefanopoulou, Anna G.; Fiengo, Giovanni

doi:10.1115/1.4002475

Cited by 328 publications

(181 citation statements)

References 21 publications

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“…Various battery models have been proposed so far, including black-box models (e.g., stochastic fuzzy neural network model [16]), grey-box models (e.g., electrical circuit model [25]), and white-box models (e.g., battery electrochemical model [26]). The dynamics of the electrical states of Li-ion batteries can be precisely modeled using electrical battery models.…”

Section: Battery Rc Electric Sub-modelmentioning

confidence: 99%

An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

Liu

Yang

et al. 2017

Electrochimica Acta

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. (2017) An advanced Lithiumion battery optimal charging strategy based on a coupled thermoelectric model. Electrochimica Acta, 225. pp. 330-344. Permanent WRAP URL:http://wrap.warwick.ac.uk/86302 Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. Kingdom (Email:{kliu02,k.li,zyang07,czhang07,j.deng}@qub.ac.uk).Abstract: Lithium-ion batteries are widely adopted as the power supplies for electric vehicles. A key but challenging issue is to achieve optimal battery charging, while taking into account of various constraints for safe, efficient and reliable operation. In this paper, a triple-objective function is first formulated for battery charging based on a coupled thermoelectric model. An advanced optimal charging strategy is then proposed to develop the optimal constant-current-constant-voltage (CCCV) charge current profile, which gives the best trade-off among three conflicting but important objectives for battery management. To be specific, a coupled thermoelectric battery model is first presented. Then, a specific triple-objective function consisting of three objectives, namely charging time, energy loss, and temperature rise (both the interior and surface), is proposed.Heuristic methods such as Teaching-learning-based-optimization (TLBO) and particle swarm optimization (PSO) are applied to optimize the triple-objective function, and their optimization performances are compared.The impacts of the weights for different terms in the objective function are then assessed. Experimental results show that the proposed optimal charging strategy is capable of offering desirable effective optimal charging current profiles and a proper trade-off among the conflicting objectives. Further, the proposed optimal charging strategy can be easily extended to other battery types.

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Section: Battery Rc Electric Sub-modelmentioning

confidence: 99%

An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

Liu

Yang

et al. 2017

Electrochimica Acta

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“…The electrochemical model is actually based on a series of differential algebraic equations describing the internal potential and ion diffusion. The specific equations and boundary conditions are shown in Table 1 [23], which an ideal model can be constructed from, and the detailed derivation process can be referenced to [14]. = 0…”

Section: Average Electrode Modelmentioning

confidence: 99%

“…Then, the terminal voltage can be simplified as a polynomial expressed by the average values at the positive and negative electrodes in accordance with the boundary conditions in the table. The specific derivation process can be referred to [14], and the voltage output Equation is:…”

Section: Average Electrode Modelmentioning

confidence: 99%

“…Di Domenico et al proposed the average electrode model of the battery in References [14,15], which was simplified on the basis of the micro-macroscopic coupled battery model advanced in the literature [8]. In order to reduce the complexity of the model, the electrolyte concentration in the average electrode model is considered as a constant value, and the electrode dynamics characteristic of the X axis in the cross section is considered only.…”

Section: Average Electrode Modelmentioning

confidence: 99%

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Parameter Identification of Electrochemical Model for Vehicular Lithium-Ion Battery Based on Particle Swarm Optimization

Yang

Chen

et al. 2017

Energies

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Abstract:The dynamic characteristics of power batteries directly affect the performance of electric vehicles, and the mathematical model is the basis for the design of a battery management system (BMS).Based on the electrode-averaged model of a lithium-ion battery, in view of the solid phase lithium-ion diffusion equation, the electrochemical model is simplified through the finite difference method. By analyzing the characteristics of the model and the type of parameters, the solid state diffusion kinetics are separated, and then the cascade parameter identifications are implemented with Particle Swarm Optimization. Eventually, the validity of the electrochemical model and the accuracy of model parameters are verified through 0.2-2 C multi-rates battery discharge tests of cell and road simulation tests of a micro pure electric vehicle under New European Driving Cycle (NEDC) conditions. The results show that the estimated parameters can guarantee the output accuracy. In the test of cell, the voltage deviation of discharge is generally less than 0.1 V except the end; in road simulation test, the output is close to the actual value at low speed with the error around ±0.03 V, and at high speed around ±0.08 V.

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“…[6][7][8][9][10][11][12][13][14][15][16] Also, ROMs have been published to simulate capacity fading 17,18 and for use in parameter estimations. [19][20][21][22][23][24] The single particle model dates back to 1979, when Atlung et al 2 presented a relatively simple cell model for the Li/TiS 2 couple. Their model includes the diffusion of lithium ions in different shaped particles of TiS 2 , which they called a solid solution.…”

mentioning

confidence: 99%

Nonlinear State-Variable Method for Solving Physics-Based Li-Ion Cell Model with High-Frequency Inputs

Jin

White

2017

J. Electrochem. Soc.

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A nonlinear state-variable method is presented and used to solve the pseudo-2D (P2D) Li-ion cell model under high-frequency input current and temperature signals. The physics-based governing equations are formulated into a nonlinear state variable method (NSVM), in which the mass transfer variables are evaluated using a 1 st order exponential integrator approach at each discrete time point and the electrochemical kinetics (Butler-Volmer) equations are solved by either an iterative or an explicit method. This procedure provides an accurate, computationally efficient method to develop physics-based simulations of the performance of a dual-foil Li-ion cell during practical drive cycles. Physics-based Li-ion cell models are useful tools for analyzing the battery cell performances, characterizing material properties, supporting cell design, and developing battery management systems (BMS). 5 in their work, a dual-foil Li-ion cell was represented by a pseudo-two-dimensional domain; and therefore, this model is usually referred as the "pseudo-2D model (P2D)".3 This model contains several coupled transport phenomena described by nonlinear partial differential equations (PDEs). Due to the numerical complexity of these models, various reduced-order models (ROMs) have been proposed as substitutes for either the single particle (SP) or the P2D full-order model (FOM) in practical online simulation applications.6-16 Also, ROMs have been published to simulate capacity fading 17,18 and for use in parameter estimations. presented an approximate solution to the spherical diffusion problem with a fixed flux which provides high accuracy with only a few terms in a series when compared to the analytic solution with at least 100 terms. This approximate solution provides significant savings in computation time.In order to predict the performance of lithium ion cells operating at higher rates, more complicated models were developed. In 1982, West et al. 4 presented a Nernst-Planck model for porous insertion electrodes for a Li/TiS 2 cell. They pointed out the importance of coupling the transport of lithium ions between the insertion electrode and the electrolyte. In 1993, Mao and White 35 presented a Nernst-Planck model of the Li/TiS 2 cell which included transport of lithium ions through the separator and demonstrated quantitatively how the utilization of the TiS 2 electrode could be improved by decreasing the thickness of the separator. Also in 1993, Doyle et al. 36 published a concentrated solution theory model for a lithium/polymer/TiS 2 cell. Shortly after that in 1994 Fuller et al.5 published a concentrated solution theory model for a dual lithium ion insertion cell ("dual foil"), which is known as "pseudo-2D model (P2D)". In 1996, Doyle et al. 37 published a comparison of their model predictions to experimental data from a Bellcore plastic lithium ion cell. Unfortunately, the computation burden associated with using the program dual foil is too great to use their program for extensive simulations needed for parameter estimation an...

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Lithium-Ion Battery State of Charge and Critical Surface Charge Estimation Using an Electrochemical Model-Based Extended Kalman Filter

Cited by 328 publications

References 21 publications

An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

Parameter Identification of Electrochemical Model for Vehicular Lithium-Ion Battery Based on Particle Swarm Optimization

Nonlinear State-Variable Method for Solving Physics-Based Li-Ion Cell Model with High-Frequency Inputs

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