Special Issue "Challenges of Battery Management System"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: 30 June 2021.

Special Issue Editor

Prof. Dr. Jong Hoon Kim
Website
Guest Editor
Department of Electrical Engineering, Chungnam National University, Daejeon, Korea
Interests: battery management system (SOx estimation/prediction algorithms); screening; battery modeling; voltage/SOC equalization; thermal management; heuristic method-based BMS (artificial intelligence); next-generation battery (VRFB/Li–Air/LiS/Al-Ion, etc.); energy storage system; energy management system; fault diagnosis; xEV retired battery (second-use) pack configuration and BMS; fuel cell system modeling and EMS; power electronics circuits control and design; renewable energy
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Special Issue Information

Dear Colleagues,

At present, the rechargeable battery industry has reported significant growth in the use of battery systems for portable device and power electronics and renewable energy storage applications. Specifically, with great attention on multicell battery string for electric-powered applications, such as electric vehicles (EV), hybrid electric vehicles (HEV), and energy storage systems (ESS), the necessity of the battery management system (BMS) for having high confidence on operational performance in EV, HEV, and ESS have substantially increased together. Therefore, this Special Issue focuses on variable challenges of battery management system considered in electric-powered application. The topics of interest include but are not limited to:

  • Advanced equivalent electrical circuit modeling
  • Electrochemical-based modeling
  • SOx estimation and prediction algorithms
  • Thermal modeling and management system
  • Artificial intelligence (AI)-based BMS
  • Fault diagnosis and detection
  • Remaining-useful life
  • Voltage and SOC equalization
  • Variable issues of second-use battery (retired battery)
  • Variable issues of energy storage system (ESS)
  • New-generation battery
  • Power electronics-based battery charger and fast charging

Prof. Dr. Jonghoon Kim
Guest Editor

Manuscript Submission Information

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Published Papers (6 papers)

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Research

Open AccessFeature PaperEditor’s ChoiceArticle
Thermal Analysis of a Parallel-Configured Battery Pack (1S18P) Using 21700 Cells for a Battery-Powered Train
Electronics 2020, 9(3), 447; https://doi.org/10.3390/electronics9030447 - 06 Mar 2020
Cited by 1
Abstract
In this study, the thermal behavior of a 1S18P battery pack is examined based on the power demand during train propulsion between two stations. The proposed thermal prediction model is classified into Joules heating with equivalent resistance, reversible heat, and heat dissipation. The [...] Read more.
In this study, the thermal behavior of a 1S18P battery pack is examined based on the power demand during train propulsion between two stations. The proposed thermal prediction model is classified into Joules heating with equivalent resistance, reversible heat, and heat dissipation. The equivalent resistances are determined by 5% of the state of charge intervals using the hybrid pulse power characterization test. The power demand profile during train propulsion between two stations is provided by the Korea Railroad Research Institute. An experiment is conducted to examine the 1S18P battery pack thermal behavior during the propulsion between two stations. A comparison of the simulation and experiment results validated the proposed thermal model. Full article
(This article belongs to the Special Issue Challenges of Battery Management System)
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Open AccessFeature PaperArticle
Analysis of High-Power Charging Limitations of a Battery in a Hybrid Railway System
Electronics 2020, 9(2), 212; https://doi.org/10.3390/electronics9020212 - 24 Jan 2020
Abstract
Fuel cell (FC)-driven railroad propulsion systems (RPSs) have been much appreciated for the past two decades to get rid exhausts of fossil fuels, but the inability of FCs to capture regenerative power produced by propulsion systems during regenerative braking and the dependency of [...] Read more.
Fuel cell (FC)-driven railroad propulsion systems (RPSs) have been much appreciated for the past two decades to get rid exhausts of fossil fuels, but the inability of FCs to capture regenerative power produced by propulsion systems during regenerative braking and the dependency of its power density on operating current density necessitates the hybridization of FCs with batteries and/or supercapacitors to utilize the best features of all three power sources. Contrary to the research trend in hybridization where the purpose of hybridization such as fuel saving, high efficiency, or high mileage is achieved by certain operational algorithms without going into detail models, this study using detailed models explores the impact of high-power charging limitations of batteries on the optimization of hybridization, and proposes a solution accordingly. In this study, all three power sources were modeled, the optimal and suboptimal behaviors at the individual level were identified, and power distribution was implemented for a propulsion system, as recommended by the optimal features of all individual power sources. Since the detailed modeling of these power sources involves many mathematical equations and requires the implementation of continuous and discrete states, this study also demonstrates how, using C-MEX S-Functions, these models can be implemented with a reduced computational burden. Full article
(This article belongs to the Special Issue Challenges of Battery Management System)
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Open AccessFeature PaperArticle
Improved Efficiency Management Strategy for Battery-Based Energy Storage Systems
Electronics 2019, 8(12), 1459; https://doi.org/10.3390/electronics8121459 - 02 Dec 2019
Abstract
Battery-based energy storage systems are forecasted to have a rapid diffusion in the next future, because they can support the diffusion of renewable energy sources and can offer interesting ancillary services for the distribution grid. Consequently, energy management strategies for batteries and inverters [...] Read more.
Battery-based energy storage systems are forecasted to have a rapid diffusion in the next future, because they can support the diffusion of renewable energy sources and can offer interesting ancillary services for the distribution grid. Consequently, energy management strategies for batteries and inverters present in storage systems will play a fundamental role in order to guarantee effective energy transfer processes between storage systems and the grid. This paper proposes an efficient management strategy which allows maximizing the overall energy efficiency of grid-connected storage systems taking into account the actual relationship between the efficiency and the charging/discharging power of the storage system. The effectiveness of the strategy is as shown by analysis results, the proposed strategy can allow a remarkable efficiency increase compared with strategies which are not aimed at the efficiency optimization. Full article
(This article belongs to the Special Issue Challenges of Battery Management System)
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Open AccessArticle
Power Capability Analysis of Lithium Battery and Supercapacitor by Pulse Duration
Electronics 2019, 8(12), 1395; https://doi.org/10.3390/electronics8121395 - 22 Nov 2019
Abstract
In this report, a method for estimating pulse power performance according to pulse duration is proposed. This approach can be used for power control logic in an environmentally friendly power generation system such as electric vehicles and an energy storage system (ESS). Although [...] Read more.
In this report, a method for estimating pulse power performance according to pulse duration is proposed. This approach can be used for power control logic in an environmentally friendly power generation system such as electric vehicles and an energy storage system (ESS). Although there have been studies on pulse power capability, we are unaware of any publications on the estimation of the magnitude of pulse power according to the power usage time, and the verification of the estimation result. Therefore, we propose a method to predict power performance according to the pulse duration of batteries and supercapacitors that are used in eco-friendly power generation systems. The proposed method is systematically presented using both a lithium-ion battery module with a nominal voltage of 44 V, 11 Ah, and a supercapacitor module with a maximum voltage of 36 V and a capacitance of 30 F. Full article
(This article belongs to the Special Issue Challenges of Battery Management System)
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Open AccessFeature PaperArticle
Cell Voltage Equalizer Using a Selective Voltage Multiplier with a Reduced Selection Switch Count for Series-Connected Energy Storage Cells
Electronics 2019, 8(11), 1303; https://doi.org/10.3390/electronics8111303 - 07 Nov 2019
Cited by 1
Abstract
Cell voltage equalization is mandatory to eliminate voltage imbalance of series-connected energy storage cells, such as lithium-ion batteries (LIBs) and electric double-layer capacitors (EDLCs), to ensure years of safe operations. Although a variety of cell equalizers using selection switches have been proposed, conventional [...] Read more.
Cell voltage equalization is mandatory to eliminate voltage imbalance of series-connected energy storage cells, such as lithium-ion batteries (LIBs) and electric double-layer capacitors (EDLCs), to ensure years of safe operations. Although a variety of cell equalizers using selection switches have been proposed, conventional techniques require numerous switches in proportion to the cell count and are prone to complexity. This paper proposes a novel cell voltage equalizer using a selective voltage multiplier. By embedding selection switches into the voltage multiplier-based cell voltage equalizer, the number of selection switches can be reduced in comparison with that in conventional topologies, realizing the simplified circuit. A prototype for twelve cells was built, and an equalization test using LIBs was performed. The voltage imbalance decreased down to approximately 20 mV by the proposed equalizer, and the standard deviation of cell voltages at the end of the equalization test was as low as 10 mV, demonstrating its equalization performance. Full article
(This article belongs to the Special Issue Challenges of Battery Management System)
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Open AccessFeature PaperArticle
Incremental Capacity Curve Peak Points-Based Regression Analysis for the State-of-Health Prediction of a Retired LiNiCoAlO2 Series/Parallel Configured Battery Pack
Electronics 2019, 8(10), 1118; https://doi.org/10.3390/electronics8101118 - 04 Oct 2019
Cited by 2
Abstract
To recycle retired series/parallel battery packs, it is necessary to know their state-of-health (SOH) correctly. Unfortunately, voltage imbalances between the cells occur repeatedly during discharging/charging. The voltage ranges for the discharge/charge of a retired series/parallel battery pack are reduced owing to the voltage [...] Read more.
To recycle retired series/parallel battery packs, it is necessary to know their state-of-health (SOH) correctly. Unfortunately, voltage imbalances between the cells occur repeatedly during discharging/charging. The voltage ranges for the discharge/charge of a retired series/parallel battery pack are reduced owing to the voltage imbalances between the cells. To determine the accurate SOH of a retired series/parallel battery pack, it is necessary to calculate the total discharge capacity using fully discharging/charging tests. However, a fully discharging/charging test is impossible owing to the reduced voltage range. The SOH of a retired series/parallel battery pack with a voltage imbalance should be estimated within the reduced discharging/charging voltage range. This paper presents a regression analysis of the peak point in the incremental capacity (IC) curve from the fresh state to a 100-cycle aging state. Moreover, the SOH of the considered retired series/parallel battery pack was estimated using a regression analysis model. The error in the SOHs of the retired series/parallel battery pack and linear regression analysis model was within 1%, and hence a good accuracy is achieved. Full article
(This article belongs to the Special Issue Challenges of Battery Management System)
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