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2nd Young Scholar’s Symposium on Battery Design and Management (BDM 2017)

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (1 December 2017) | Viewed by 21602

Special Issue Editors


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Guest Editor
Faculty of Automotive and Construction Machinery Engineering at Warsaw University of Technology, St. Narbutta 24, 02-524 Warsaw, Poland
Interests: electrical/hybrid vehicles; energy storage system; battery management system

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Guest Editor
School of Automotive Studies, Tongji University, No. 4800, Caoan Road, Jiading District, Shanghai 201804, China
Interests: electrical/hybrid vehicles; energy storage and battery management system; wireless power transfer
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Guest Editor
2026 Black Engineering, Iowa State University, Ames, IA 50011 USA
Interests: energy storage and battery management system; battery degradation analysis and lifetime modeling

Special Issue Information

Dear Colleagues,

It is our pleasure to announce that the 2nd Young Scholar’s Symposium on Battery Design and Management will be held this year in Tongji University, Shanghai, China, from June 8 to 10, 2017. The symposium was held for the first time last year (2016) in Tsinghua University, China. Around 100 young scholars from all over China, whose research interests fall into the fields of battery design and management, attended the symposium. There were many discussions regarding the science and technology of battery design and management in the symposium.

The Young Scholar’s Symposium on Battery Design and Management encompasses a range of disciplines concerning the technologies of battery design, modeling, state estimation, thermal management and safety, etc. This symposium aims to establish close links among these fields, set up system science based on knowledge from other sciences and promote multidisciplinary solutions to settle the complex battery system problems.

The conference website is: http://www.iceee.net/BDM2017/index.html

Topics of interest for this Special Issue include, but are not limited to:

  • Battery modeling: equivalent circuit model, electrochemical model, thermal model, and aging model

  • Battery state estimation: State of Charge, State of Health, State of Life, and State of Power Estimation

  • Battery diagnosis, prognosis, and health management (PHM): physics-based, model-based, data-driven, and hybrid approaches

  • Battery electrochemical/material characteristics: cathode, anode, separator, and electrolyte.

  • Battery cell balancing: passive and active balancing methods; cell consistency assessment

  • Battery grouping/packing techniques: architectural analysis, sensor placement, and power electronic aspects

  • Battery cooling systems and battery thermal management systems (BTMS)

  • Battery charging control

  • BMS hardware design and verification

  • System-level integration and control of batteries into electric vehicles and smart grid

For inquiries regarding this Special Issue, please contact: Dr. Rui Xiong, Editorial Board, Energies ([email protected])

Assoc. Prof. Dr. Rui Xiong
Assoc. Prof. Dr. Haifeng Dai
Assist. Prof. Dr. Chao Hu
Assist Prof. Dr. Yuhua Chang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Battery Design

  • Battery materials

  • Battery modeling

  • Battery state estimation

  • Battery safety management

  • Battery diagnosis, prognosis, and health management

  • Battery electrochemical/material characteristics

  • Battery balancing

  • Battery grouping/packing techniques

  • Battery cooling systems

  • Battery thermal management systems

  • Battery charging control

  • Battery management system

Published Papers (3 papers)

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Research

18 pages, 8666 KiB  
Article
Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient
by Haifeng Dai, Bo Jiang and Xuezhe Wei
Energies 2018, 11(1), 220; https://doi.org/10.3390/en11010220 - 17 Jan 2018
Cited by 65 | Viewed by 8548
Abstract
Battery impedance is essential to the management of lithium-ion batteries for electric vehicles (EVs), and impedance characterization can help to monitor and predict the battery states. Many studies have been undertaken to investigate impedance characterization and the factors that influence impedance. However, few [...] Read more.
Battery impedance is essential to the management of lithium-ion batteries for electric vehicles (EVs), and impedance characterization can help to monitor and predict the battery states. Many studies have been undertaken to investigate impedance characterization and the factors that influence impedance. However, few studies regarding the influence of the internal temperature gradient, which is caused by heat generation during operation, have been presented. We have comprehensively studied the influence of the internal temperature gradient on impedance characterization and the modeling of battery impedance, and have proposed a discretization model to capture battery impedance characterization considering the temperature gradient. Several experiments, including experiments with artificial temperature gradients, are designed and implemented to study the influence of the internal temperature gradient on battery impedance. Based on the experimental results, the parameters of the non-linear impedance model are obtained, and the relationship between the parameters and temperature is further established. The experimental results show that the temperature gradient will influence battery impedance and the temperature distribution can be considered to be approximately linear. The verification results indicate that the proposed discretization model has a good performance and can be used to describe the actual characterization of the battery with an internal temperature gradient. Full article
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15 pages, 5541 KiB  
Article
Practical On-Board Measurement of Lithium Ion Battery Impedance Based on Distributed Voltage and Current Sampling
by Xuezhe Wei, Xueyuan Wang and Haifeng Dai
Energies 2018, 11(1), 64; https://doi.org/10.3390/en11010064 - 01 Jan 2018
Cited by 30 | Viewed by 6659
Abstract
Battery impedance based state estimation methods receive extensive attention due to its close relation to internal dynamic processes and the mechanism of a battery. In order to provide impedance for a battery management system (BMS), a practical on-board impedance measuring method based on [...] Read more.
Battery impedance based state estimation methods receive extensive attention due to its close relation to internal dynamic processes and the mechanism of a battery. In order to provide impedance for a battery management system (BMS), a practical on-board impedance measuring method based on distributed signal sampling is proposed and implemented. Battery cell perturbing current and its response voltage for impedance calculation are sampled separately to be compatible with BMS. A digital dual-channel orthogonal lock-in amplifier is used to calculate the impedance. With the signal synchronization, the battery impedance is obtained and compensated. And the relative impedance can also be obtained without knowing the current. For verification, an impedance measuring system made up of electronic units sampling and processing signals and a DC-AC converter generating AC perturbing current is designed. A type of 8 Ah LiFePO4 battery is chosen and the valuable frequency range for state estimations is determined with a series of experiments. The battery cells are connected in series and the impedance is measured with the prototype. It is shown that the measurement error of the impedance modulus at 0.1 Hz–500 Hz at 5 °C–35 °C is less than 4.5% and the impedance phase error is less than 3% at <10 Hz at room temperature. In addition, the relative impedance can also be tracked well with the designed system. Full article
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7768 KiB  
Article
Multi-Objective Optimal Charging Method for Lithium-Ion Batteries
by Xiaogang Wu, Wenwen Shi and Jiuyu Du
Energies 2017, 10(9), 1271; https://doi.org/10.3390/en10091271 - 26 Aug 2017
Cited by 26 | Viewed by 5385
Abstract
In order to optimize the charging of lithium-ion batteries, a multi-stage charging method that considers the charging time and energy loss as optimization targets has been proposed in this paper. First, a dynamic model based on a first-order circuit has been established, and [...] Read more.
In order to optimize the charging of lithium-ion batteries, a multi-stage charging method that considers the charging time and energy loss as optimization targets has been proposed in this paper. First, a dynamic model based on a first-order circuit has been established, and the model parameters have been identified. Second, on the basis of the established model, we treat the objective function of the optimization problem as a weighted sum of charging time and energy loss. Finally, a dynamic programming algorithm (DP) has been used to calculate the charging current of the objective function. Simulation and experimental results show that the proposed charging method could effectively reduce the charging time and decrease the energy loss, compared with the constant-current constant-voltage charging method, under the premise of exerting little influence on the attenuation of battery capacity. Full article
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