Three-dimensional Multi-Particle Electrochemical Model of LiFePO4 Cells based on a Resistor Network Methodology

Mastali, Mehrdad; Samadani, Ehsan; Farhad, Siamak; Fraser, Roydon; Fowler, Michael

doi:10.1016/j.electacta.2015.12.122

Cited by 37 publications

(25 citation statements)

References 50 publications

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“…Samba et al [14] used the electrical-thermal model to design the battery thermal management system. Though simplified approaches, such as the simplified electrochemical multi-particle model and homogenous pseudo two-dimensional model, were developed by Mastali et al [15] to decrease the computational time, the speed and simplicity of three-dimensional electrochemical-thermal models are still of concern. The second kind of models is the equivalent circuit model (ECM).…”

Section: Introductionmentioning

confidence: 99%

Modeling of a Pouch Lithium Ion Battery Using a Distributed Parameter Equivalent Circuit for Internal Non-Uniformity Analysis

Chen

Jiang

et al. 2016

Energies

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A battery model that has the capability of analyzing the internal non-uniformity of local state variables, including the state of charge (SOC), temperature and current density, is proposed in this paper. The model is built using a set of distributed parameter equivalent circuits. In order to validate the accuracy of the model, a customized battery with embedded T-type thermocouple sensors inside the battery is tested. The simulated temperature conforms well with the measured temperature at each test point, and the maximum difference is less than 1°C. Then, the model is applied to analyze the evolution processes of local state variables' distribution inside the battery during the discharge process. The simulation results demonstrate drastic distribution changes of the local state variables inside the battery during the discharge process. The internal non-uniformity is originally caused by the resistance of positive and negative foils, while also influenced by the change rate of open circuit voltage and the total resistance of the battery. Hence, the factors that affect the distribution of the local state variables are addressed.

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Section: Introductionmentioning

confidence: 99%

Modeling of a Pouch Lithium Ion Battery Using a Distributed Parameter Equivalent Circuit for Internal Non-Uniformity Analysis

Chen

Jiang

et al. 2016

Energies

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“…Compared with conventional internal combustion engine (ICE) based vehicles, EVs are powered by batteries that may be charged from renewable power generated from the wind, solar or other forms of renewable sources [2]. Among all batteries types, Lithium-ion (Li-ion) batteries are preferable power supplies for EVs due to a number of favourable characteristics such as power density, less pollution, and long service life [3]. For Li-ion batteries, a proper battery charging strategy is essential in ensuring efficient and safe operations.…”

Section: Introductionmentioning

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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“…To investigate the thermal performance of lithium-ion battery pack, Qian et al [6] established a three-dimensional numerical model using a type of liquid cooling method based on mini-channel cold-plate and. Though simplified approaches, Mastali et al [7] developed the simplified electrochemical multi-particle model and homogenous pseudo two-dimensional model to decrease the computational time, the speed and simplicity of three-dimensional electrochemical-thermal models are still of concern. The second kind of models is the equivalent circuit model (ECM), where the battery is usually regarded as a mass point [8,9].…”

Section: Introductionmentioning

confidence: 99%

Big-Data-Based Thermal Runaway Prognosis of Battery Systems for Electric Vehicles

Hong¹,

Wang²,

Liu³

2017

Preprint

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This paper presents a thermal runaway prognosis scheme based on the big-data platform and entropy method for battery systems in electric vehicles. It can simultaneously realize the diagnosis and prognosis of thermal runaway caused by the temperature fault through monitoring battery temperature during vehicular operations. A vast quantity of real-time voltage monitoring data was collected in the National Service and Management Center for Electric Vehicles (NSMC-EV) in Beijing to verify the effectiveness of the presented method. The results show that the proposed method can accurately forecast both the time and location of the temperature fault within battery packs. Furthermore, a temperature security management strategy for thermal runaway is proposed on the basis of the Z-score approach and the abnormity coefficient is set to make real-time precaution of temperature abnormity.

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Three-dimensional Multi-Particle Electrochemical Model of LiFePO4 Cells based on a Resistor Network Methodology

Cited by 37 publications

References 50 publications

Modeling of a Pouch Lithium Ion Battery Using a Distributed Parameter Equivalent Circuit for Internal Non-Uniformity Analysis

Modeling of a Pouch Lithium Ion Battery Using a Distributed Parameter Equivalent Circuit for Internal Non-Uniformity Analysis

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

Big-Data-Based Thermal Runaway Prognosis of Battery Systems for Electric Vehicles

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