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Special Issue "Electrochemical Energy Storage - 2015"

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

Deadline for manuscript submissions: closed (15 February 2016)

Special Issue Editor

Guest Editor
Dr. Sheng S. Zhang

Electrochemistry Branch, RDRL-SED-C, Sensors and Electron Devices Directorate, U.S. Army Research Laboratory, Adelphi, MD 20783-1138, USA
Website | E-Mail
Interests: Li-ion battery; Li-air battery; lithium-sulfur battery; Li/CFx battery; non-aqueous electrolyte; polymer electrolyte; separator; electrode material

Special Issue Information

Dear Colleagues,

This is the 3rd Special Issue regarding Electrochemical Energy Storage. Similarly, the scopes of this Special Issue cover all aspects of electrochemical energy storage devices, including batteries, electrochemical capacitors, and their combinations. Batteries cover all types of primary or secondary batteries, metal-air batteries, and redox flow batteries, and electrochemical capacitors include electric double-layer capacitors and pseudocapacitors. This Special Issue addresses current and future advancements in all aspects of the science, technology, engineering and applications of electrochemical energy storage systems.

We invite research and review articles on a wide range of subjects within materials science and engineering, nanotechnology, physics, chemistry, and electrochemistry. Manuscripts on the testing methods, simulations, electric or thermal management of single cells or battery packs, as well as on the
applications and recycling technologies of the electrochemical energy storage devices are also within the scope of this Special Issue.

Dr. Sheng S. Zhang
Guest Editor

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 papers will be 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 monthly 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 1600 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

  • energy storage
  • battery
  • capacitor
  • battery pack
  • battery management
  • electric vehicle

Published Papers (7 papers)

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Research

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Open AccessArticle Modeling and Simulation of the Thermal Runaway Behavior of Cylindrical Li-Ion Cells—Computing of Critical Parameters
Energies 2016, 9(4), 292; https://doi.org/10.3390/en9040292
Received: 11 February 2016 / Revised: 31 March 2016 / Accepted: 7 April 2016 / Published: 16 April 2016
Cited by 9 | PDF Full-text (5212 KB) | HTML Full-text | XML Full-text
Abstract
The thermal behavior of Li-ion cells is an important safety issue and has to be known under varying thermal conditions. The main objective of this work is to gain a better understanding of the temperature increase within the cell considering different heat sources
[...] Read more.
The thermal behavior of Li-ion cells is an important safety issue and has to be known under varying thermal conditions. The main objective of this work is to gain a better understanding of the temperature increase within the cell considering different heat sources under specified working conditions. With respect to the governing physical parameters, the major aim is to find out under which thermal conditions a so called Thermal Runaway occurs. Therefore, a mathematical electrochemical-thermal model based on the Newman model has been extended with a simple combustion model from reaction kinetics including various types of heat sources assumed to be based on an Arrhenius law. This model was realized in COMSOL Multiphysics modeling software. First simulations were performed for a cylindrical 18650 cell with a L i C o O 2 -cathode to calculate the temperature increase under two simple electric load profiles and to compute critical system parameters. It has been found that the critical cell temperature T crit , above which a thermal runaway may occur is approximately 400 K , which is near the starting temperature of the decomposition of the Solid-Electrolyte-Interface in the anode at 393 . 15 K . Furthermore, it has been found that a thermal runaway can be described in three main stages. Full article
(This article belongs to the Special Issue Electrochemical Energy Storage - 2015)
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Open AccessArticle Joint Estimation of the Electric Vehicle Power Battery State of Charge Based on the Least Squares Method and the Kalman Filter Algorithm
Energies 2016, 9(2), 100; https://doi.org/10.3390/en9020100
Received: 6 October 2015 / Revised: 27 December 2015 / Accepted: 22 January 2016 / Published: 8 February 2016
Cited by 15 | PDF Full-text (3638 KB) | HTML Full-text | XML Full-text
Abstract
An estimation of the power battery state of charge (SOC) is related to the energy management, the battery cycle life and the use cost of electric vehicles. When a lithium-ion power battery is used in an electric vehicle, the SOC displays
[...] Read more.
An estimation of the power battery state of charge (SOC) is related to the energy management, the battery cycle life and the use cost of electric vehicles. When a lithium-ion power battery is used in an electric vehicle, the SOC displays a very strong time-dependent nonlinearity under the influence of random factors, such as the working conditions and the environment. Hence, research on estimating the SOC of a power battery for an electric vehicle is of great theoretical significance and application value. In this paper, according to the dynamic response of the power battery terminal voltage during a discharging process, the second-order RC circuit is first used as the equivalent model of the power battery. Subsequently, on the basis of this model, the least squares method (LS) with a forgetting factor and the adaptive unscented Kalman filter (AUKF) algorithm are used jointly in the estimation of the power battery SOC. Simulation experiments show that the joint estimation algorithm proposed in this paper has higher precision and convergence of the initial value error than a single AUKF algorithm. Full article
(This article belongs to the Special Issue Electrochemical Energy Storage - 2015)
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Open AccessArticle A Fuzzy-Logic Power Management Strategy Based on Markov Random Prediction for Hybrid Energy Storage Systems
Energies 2016, 9(1), 25; https://doi.org/10.3390/en9010025
Received: 16 November 2015 / Revised: 23 December 2015 / Accepted: 25 December 2015 / Published: 4 January 2016
Cited by 16 | PDF Full-text (5371 KB) | HTML Full-text | XML Full-text
Abstract
Over the last few years; issues regarding the use of hybrid energy storage systems (HESSs) in hybrid electric vehicles have been highlighted by the industry and in academic fields. This paper proposes a fuzzy-logic power management strategy based on Markov random prediction for
[...] Read more.
Over the last few years; issues regarding the use of hybrid energy storage systems (HESSs) in hybrid electric vehicles have been highlighted by the industry and in academic fields. This paper proposes a fuzzy-logic power management strategy based on Markov random prediction for an active parallel battery-UC HESS. The proposed power management strategy; the inputs for which are the vehicle speed; the current electric power demand and the predicted electric power demand; is used to distribute the electrical power between the battery bank and the UC bank. In this way; the battery bank power is limited to a certain range; and the peak and average charge/discharge power of the battery bank and overall loss incurred by the whole HESS are also reduced. Simulations and scaled-down experimental platforms are constructed to verify the proposed power management strategy. The simulations and experimental results demonstrate the advantages; feasibility and effectiveness of the fuzzy-logic power management strategy based on Markov random prediction. Full article
(This article belongs to the Special Issue Electrochemical Energy Storage - 2015)
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Open AccessArticle Electrochemical Properties for Co-Doped Pyrite with High Conductivity
Energies 2015, 8(9), 9584-9593; https://doi.org/10.3390/en8099584
Received: 27 June 2015 / Revised: 17 August 2015 / Accepted: 26 August 2015 / Published: 2 September 2015
Cited by 2 | PDF Full-text (1299 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, the hydrothermal method was adopted to synthesize nanostructure Co-doped pyrite (FeS2). The structural properties and morphology of the synthesized materials were characterized using X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. Co in the crystal lattice of
[...] Read more.
In this paper, the hydrothermal method was adopted to synthesize nanostructure Co-doped pyrite (FeS2). The structural properties and morphology of the synthesized materials were characterized using X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. Co in the crystal lattice of FeS2 could change the growth rate of different crystal planes of the crystal particles, which resulted in various polyhedrons with clear faces and sharp outlines. In addition, the electrochemical performance of the doping pyrite in Li/FeS2 batteries was evaluated using the galvanostatic discharge test, cyclic voltammetry and electrochemical impedance spectroscopy. The results showed that the discharge capacity of the doped material (801.8 mAh·g−1) with a doping ratio of 7% was significantly higher than that of the original FeS2 (574.6 mAh·g−1) because of the enhanced conductivity. Therefore, the doping method is potentially effective for improving the electrochemical performance of FeS2. Full article
(This article belongs to the Special Issue Electrochemical Energy Storage - 2015)
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Open AccessArticle Glucose-Treated Manganese Hexacyanoferrate for Sodium-Ion Secondary Battery
Energies 2015, 8(9), 9486-9494; https://doi.org/10.3390/en8099486
Received: 8 July 2015 / Revised: 18 August 2015 / Accepted: 25 August 2015 / Published: 1 September 2015
Cited by 5 | PDF Full-text (490 KB) | HTML Full-text | XML Full-text
Abstract
Manganese hexacyanoferrate (Mn-PBA) is a promising cathode material forsodium-ion secondary battery (SIB) with high average voltage (=3.4 V) against Na. Here,we find that the thermal decomposition of glucose modifies the surface state of Mn-PBA,without affecting the bulk crystal structure. The glucose treatment significantly
[...] Read more.
Manganese hexacyanoferrate (Mn-PBA) is a promising cathode material forsodium-ion secondary battery (SIB) with high average voltage (=3.4 V) against Na. Here,we find that the thermal decomposition of glucose modifies the surface state of Mn-PBA,without affecting the bulk crystal structure. The glucose treatment significantly improves therate properties of Mn-PBA in SIB. The critical discharge rate increases from 1 C (as-grown)to 15 C (glucose-treated). Our observation suggests that thermal treatment is quite effectivefor insulating coordination polymers. Full article
(This article belongs to the Special Issue Electrochemical Energy Storage - 2015)
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Open AccessArticle State-of-Charge Estimation for Lithium-Ion Batteries Using a Kalman Filter Based on Local Linearization
Energies 2015, 8(8), 7854-7873; https://doi.org/10.3390/en8087854
Received: 29 April 2015 / Revised: 6 June 2015 / Accepted: 24 July 2015 / Published: 30 July 2015
Cited by 20 | PDF Full-text (634 KB) | HTML Full-text | XML Full-text
Abstract
State of charge (SOC) estimation is of great significance for the safe operation of lithium-ion battery (LIB) packs. Improving the accuracy of SOC estimation results and reducing the algorithm complexity are important for the state estimation. In this paper, a zeroaxial straight line,
[...] Read more.
State of charge (SOC) estimation is of great significance for the safe operation of lithium-ion battery (LIB) packs. Improving the accuracy of SOC estimation results and reducing the algorithm complexity are important for the state estimation. In this paper, a zeroaxial straight line, whose slope changes along with SOC, is used to map the predictive SOC to the predictive open circuit voltage (OCV), and thus only one parameter is used to linearize the SOC-OCV curve near the present working point. An equivalent circuit model is used to simulate the dynamic behavior of a LIB, updating the linearization parameter in the measurement equation according to the present value of the state variables, and then a standard Kalman filter is used to estimate the SOC based on the local linearization. This estimation method makes the output equation of the nonlinear battery model contain only one parameter related to its dynamic variables. This is beneficial to simplify the algorithm structure and to reduce the computation cost. The linearization method do not essentially lose the main information of the dynamic model, and its effectiveness is verified experimentally. Fully and a partially charged battery experiments indicate that the estimation error of SOC is better than 0.5%. Full article
(This article belongs to the Special Issue Electrochemical Energy Storage - 2015)
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Review

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Open AccessReview Theoretical Modelling Methods for Thermal Management of Batteries
Energies 2015, 8(9), 10153-10177; https://doi.org/10.3390/en80910153
Received: 17 August 2015 / Revised: 30 August 2015 / Accepted: 9 September 2015 / Published: 17 September 2015
Cited by 9 | PDF Full-text (1081 KB) | HTML Full-text | XML Full-text
Abstract
The main challenge associated with renewable energy generation is the intermittency of the renewable source of power. Because of this, back-up generation sources fuelled by fossil fuels are required. In stationary applications whether it is a back-up diesel generator or connection to the
[...] Read more.
The main challenge associated with renewable energy generation is the intermittency of the renewable source of power. Because of this, back-up generation sources fuelled by fossil fuels are required. In stationary applications whether it is a back-up diesel generator or connection to the grid, these systems are yet to be truly emissions-free. One solution to the problem is the utilisation of electrochemical energy storage systems (ESS) to store the excess renewable energy and then reusing this energy when the renewable energy source is insufficient to meet the demand. The performance of an ESS amongst other things is affected by the design, materials used and the operating temperature of the system. The operating temperature is critical since operating an ESS at low ambient temperatures affects its capacity and charge acceptance while operating the ESS at high ambient temperatures affects its lifetime and suggests safety risks. Safety risks are magnified in renewable energy storage applications given the scale of the ESS required to meet the energy demand. This necessity has propelled significant effort to model the thermal behaviour of ESS. Understanding and modelling the thermal behaviour of these systems is a crucial consideration before designing an efficient thermal management system that would operate safely and extend the lifetime of the ESS. This is vital in order to eliminate intermittency and add value to renewable sources of power. This paper concentrates on reviewing theoretical approaches used to simulate the operating temperatures of ESS and the subsequent endeavours of modelling thermal management systems for these systems. The intent of this review is to present some of the different methods of modelling the thermal behaviour of ESS highlighting the advantages and disadvantages of each approach. Full article
(This article belongs to the Special Issue Electrochemical Energy Storage - 2015)
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