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Power Electronics and Energy Management for Battery Storage Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D2: Electrochem: Batteries, Fuel Cells, Capacitors".

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 24746

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Special Issue Editors


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Guest Editor
Power Electronics Research Group, Department of Electrical Power Engineering and Mechatronics, School of Engineering, Tallinn University of Technology, 19086 Tallinn, Estonia
Interests: power electronic converters; batteries; power semiconductor devices; renewable energy
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Special Issue Information

Dear Colleagues,

Deployment of distributed renewable generation and e-mobility systems is creating a demand for improved dynamic performance, flexibility, and resilience of the electrical grid.

Various energy storages, such as stationary and electric vehicle batteries together with power electronic interfaces, will play a key role in addressing these requests thanks to their enhanced functionality, fast response times, and configuration flexibility. However, several barriers still stand in the way of massive implementation of this technology, and the associated enabling developments are becoming of paramount importance. These include energy management algorithms; optimal sizing and coordinated control strategies of different storage technologies, including e-mobility storage; power electronic converters for interfacing renewables and battery systems, which allow advanced interactions with the grid; increase of round-trip efficiencies by means of advanced materials, components, and algorithms.

This Special Issue aims to encourage researchers to share new developments and potential solutions addressing the aforementioned and other related topics aiming to make the most out of these emerging technologies.

Dr. Andrei Blinov
Prof. Sheldon Williamson
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 system
  • Renewable energy source
  • Energy management
  • Demand response
  • Power electronic converter
  • Battery charger
  • Bidirectional power flow
  • Electric vehicles
  • Wide band gap semiconductors
  • Energy efficiency

Published Papers (8 papers)

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Research

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17 pages, 5830 KiB  
Article
An Efficient Non-Inverting Buck-Boost Converter with Improved Step Up/Down Ability
by Omar Abdel-Rahim, Andrii Chub, Andrei Blinov, Dmitri Vinnikov and Dimosthenis Peftitsis
Energies 2022, 15(13), 4550; https://doi.org/10.3390/en15134550 - 22 Jun 2022
Cited by 9 | Viewed by 2499
Abstract
In this article, a new non-inverting buck-boost converter with superior characteristics in both bucking and boosting is presented. The proposed converter has some distinct features, such as high step-up/-down ability and low voltage/current stress on its switching devices. The voltage gain of the [...] Read more.
In this article, a new non-inverting buck-boost converter with superior characteristics in both bucking and boosting is presented. The proposed converter has some distinct features, such as high step-up/-down ability and low voltage/current stress on its switching devices. The voltage gain of the proposed converter is double the reported value for the traditional buck-boost converter. Although it has three switches, the three switches operate simultaneously, hence no dead-time is required. Two out of the three switches are under voltage stress equal to half of the output voltage. The overall efficiency of the system is promising because of the ability to select devices with low voltage drops. Converter analysis and steady-state performance in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) are presented in detail. A 1 kW hardware prototype of the converter was implemented in the laboratory; with a step-up ratio of 3.5 and 1 kW power, the measured efficiency is above 95.4%, and with step-up ratio 8, it is around 91.5%. Full article
(This article belongs to the Special Issue Power Electronics and Energy Management for Battery Storage Systems)
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21 pages, 18098 KiB  
Article
Smart Core and Surface Temperature Estimation Techniques for Health-Conscious Lithium-Ion Battery Management Systems: A Model-to-Model Comparison
by Sumukh Surya, Akash Samanta, Vinicius Marcis and Sheldon Williamson
Energies 2022, 15(2), 623; https://doi.org/10.3390/en15020623 - 17 Jan 2022
Cited by 7 | Viewed by 2116
Abstract
Estimation of core temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. It is impractical to measure the core temperature of each cell using physical sensors, while at [...] Read more.
Estimation of core temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. It is impractical to measure the core temperature of each cell using physical sensors, while at the same time implementing a complex core temperature estimation strategy in onboard low-cost BMS is also challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models with different levels of accuracy and complexity. Broadly, there are first-order and second-order heat resistor–capacitor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simulation study. The aim was to determine whether it is worth investing towards developing a second-order thermal model instead of a first-order model with respect to prediction accuracy considering the modeling complexity and experiments required. Both the thermal models along with the parameter estimation scheme were modeled and simulated in a MATLAB/Simulink environment. Models were validated using laboratory test data of a cylindrical 18,650 LIB cell. Further, a Kalman filter with appropriate process and measurement noise levels was used to estimate the core temperature in terms of measured surface and ambient temperatures. Results from the first-order model and second-order models were analyzed for comparison purposes. Full article
(This article belongs to the Special Issue Power Electronics and Energy Management for Battery Storage Systems)
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15 pages, 5542 KiB  
Article
Controlled Energy Flow in Z-Source Inverters
by Zbigniew Rymarski, Krzysztof Bernacki and Łukasz Dyga
Energies 2021, 14(21), 7272; https://doi.org/10.3390/en14217272 - 03 Nov 2021
Cited by 2 | Viewed by 1475
Abstract
This paper proposes a method to reduce the output voltage distortions in voltage source inverters (VSI) working with impedance networks. The three main reasons for the voltage distortions include a discontinuous current in the coils of the impedance network, the double output frequency [...] Read more.
This paper proposes a method to reduce the output voltage distortions in voltage source inverters (VSI) working with impedance networks. The three main reasons for the voltage distortions include a discontinuous current in the coils of the impedance network, the double output frequency harmonics in the VSI’s voltage output caused by insufficient capacitance in the impedance network, and voltage drops on the bridge switches during the shoot-through time. The first of these distortions can be reduced by increasing the current of the impedance network when the output VSI current is low. This method requires storing energy in the battery connected to the DC link of the VSI during the “non-shoot through” time. Furthermore, this solution can also be used when the Z-source inverter works with a photovoltaic cell to help it attain a maximum power point. The Z-source inverter is essentially a voltage source inverter with the Z-source in the input. In this paper, the theory behind basic impedance networks of Z-source and quasi-Z-source (qZ-source) is investigated where simulations of the presented solutions and experimental verification of the results are also presented. Full article
(This article belongs to the Special Issue Power Electronics and Energy Management for Battery Storage Systems)
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16 pages, 3916 KiB  
Article
All-SiC ANPC Submodule for an Advanced 1.5 kV EV Charging System under Various Modulation Methods
by Rafał Kopacz, Michał Harasimczuk, Bartosz Lasek, Rafał Miśkiewicz and Jacek Rąbkowski
Energies 2021, 14(17), 5580; https://doi.org/10.3390/en14175580 - 06 Sep 2021
Cited by 8 | Viewed by 2645
Abstract
This work is focused on the design and experimental validation of the all-SiC active neutral-point clamped (ANPC) submodule for an advanced electric vehicle (EV) charging station. The topology of the station is based on a three-wire bipolar DC bus (±750 V) connecting an [...] Read more.
This work is focused on the design and experimental validation of the all-SiC active neutral-point clamped (ANPC) submodule for an advanced electric vehicle (EV) charging station. The topology of the station is based on a three-wire bipolar DC bus (±750 V) connecting an ac grid converter, isolated DC-DC converters, and a non-isolated DC-DC converter with a battery energy storage. Thus, in all types of power converters, the same three-level submodule may be applied. In this paper, a submodule rated at 1/3 of the nominal power of the grid converter (20 kVA) is discussed. In particular, four different modulation strategies for the 1.5 kV ANPC submodule, exclusively employing fast silicon carbide (SiC) MOSFETs, are considered, and their impact on the submodule performance is analyzed. Moreover, the simulation study is included. Finally, the laboratory prototype is described and experimentally verified at a switching frequency of 64 kHz. It is shown that the system can operate with all of the modulations, while techniques PWM2 and PWM3 emerge as the most efficient, and alternating between them, depending on the load, should be considered to maximize the efficiency. Furthermore, the results showcase that the impact of the different PWM techniques on switching oscillations, including overvoltages, can be nearly fully omitted for a parasitic inductance optimized circuit, and the choice of modulation should be based on power loss and/or other factors. Full article
(This article belongs to the Special Issue Power Electronics and Energy Management for Battery Storage Systems)
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32 pages, 6496 KiB  
Article
Interface Converters for Residential Battery Energy Storage Systems: Practices, Difficulties and Prospects
by Ilya A. Galkin, Andrei Blinov, Maxim Vorobyov, Alexander Bubovich, Rodions Saltanovs and Dimosthenis Peftitsis
Energies 2021, 14(12), 3365; https://doi.org/10.3390/en14123365 - 08 Jun 2021
Cited by 15 | Viewed by 3495
Abstract
Recent trends in building energy systems such as local renewable energy generation have created a distinct demand for energy storage systems to reduce the influence and dependency on the electric power grid. Under the current market conditions, a range of commercially available residential [...] Read more.
Recent trends in building energy systems such as local renewable energy generation have created a distinct demand for energy storage systems to reduce the influence and dependency on the electric power grid. Under the current market conditions, a range of commercially available residential energy storage systems with batteries has been produced. This paper addresses the area of energy storage systems from multiple directions to provide a broader view on the state-of-the-art developments and trends in the field. Present standards and associated limitations of storage implementation are briefly described, followed by the analysis of parameters and features of commercial battery systems for residential applications. Further, the power electronic converters are reviewed in detail, with the focus on existing and perspective non-isolated solutions. The analysis covers well-known standard topologies, including buck-boost and bridge, as well as emerging solutions based on the unfolding inverter and fractional/partial power converters. Finally, trends and future prospects of the residential battery storage technologies are evaluated. Full article
(This article belongs to the Special Issue Power Electronics and Energy Management for Battery Storage Systems)
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20 pages, 6631 KiB  
Article
Design of an Effective State of Charge Estimation Method for a Lithium-Ion Battery Pack Using Extended Kalman Filter and Artificial Neural Network
by Van Quan Dao, Minh-Chau Dinh, Chang Soon Kim, Minwon Park, Chil-Hoon Doh, Jeong Hyo Bae, Myung-Kwan Lee, Jianyong Liu and Zhiguo Bai
Energies 2021, 14(9), 2634; https://doi.org/10.3390/en14092634 - 04 May 2021
Cited by 40 | Viewed by 3575
Abstract
Currently, Lithium-ion batteries (LiB) are widely applied in energy storage devices in smart grids and electric vehicles. The state of charge (SOC) is an indication of the available battery capacity, and is one of the most important factors that should be monitored to [...] Read more.
Currently, Lithium-ion batteries (LiB) are widely applied in energy storage devices in smart grids and electric vehicles. The state of charge (SOC) is an indication of the available battery capacity, and is one of the most important factors that should be monitored to optimize LiB’s performance and improve its lifetime. However, because the SOC relies on many nonlinear factors, it is difficult to estimate accurately. This paper presented the design of an effective SOC estimation method for a LiB pack Battery Management System (BMS) based on Kalman Filter (KF) and Artificial Neural Network (ANN). First, considering the configuration and specifications of the BMS and LiB pack, an ANN was constructed for the SOC estimation, and then the ANN was trained and tested using the Google TensorFlow open-source library. An SOC estimation model based on the extended KF (EKF) and a Thevenin battery model was developed. Then, we proposed a combined mode EKF-ANN that integrates the estimation of the EKF into the ANN. Both methods were evaluated through experiments conducted on a real LiB pack. As a result, the ANN and KF methods showed maximum errors of 2.6% and 2.8%, but the EKF-ANN method showed better performance with less than 1% error. Full article
(This article belongs to the Special Issue Power Electronics and Energy Management for Battery Storage Systems)
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13 pages, 1735 KiB  
Article
Simulation of Energy Exchange between Single Prosumer Residential Building and Utility Grid
by Andres Annuk, Wahiba Yaïci, Matti Lehtonen, Risto Ilves, Toivo Kabanen and Peep Miidla
Energies 2021, 14(6), 1553; https://doi.org/10.3390/en14061553 - 11 Mar 2021
Cited by 5 | Viewed by 2046
Abstract
Modern households usually have independent energy sources such as wind generators, photovoltaic (PV) panels, and similar green energy production equipment. Experts predict that soon, there will be an increasing number of such prosumers who both produce and consume energy. This process alleviates and [...] Read more.
Modern households usually have independent energy sources such as wind generators, photovoltaic (PV) panels, and similar green energy production equipment. Experts predict that soon, there will be an increasing number of such prosumers who both produce and consume energy. This process alleviates and reduces the load on large national electricity networks and also contributes to overall energy security. In this paper, a simulation model of a household, which employs a wind generator as its independent source of electricity, is developed. It is expected that this approach will be easily replicated for more complex configurations. The other components of the single prosumer microgrid that will be assessed are the non-shiftable electricity consumption equipment, which is used mainly in households and deployed separately for water heater, with a separate battery to meet the needs of these non-shiftable consumers. The 5-min data intervals for the year of simulation have been used. The characteristics of energy flow according to production and consumption schedules and the capacity of storage equipment have been modelled and simulated. Results disclose that wind turbine production size and buffer battery have a crucial impact on the demand cover factor. Full article
(This article belongs to the Special Issue Power Electronics and Energy Management for Battery Storage Systems)
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Review

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25 pages, 2292 KiB  
Review
A Comprehensive Review of Lithium-Ion Cell Temperature Estimation Techniques Applicable to Health-Conscious Fast Charging and Smart Battery Management Systems
by Akash Samanta and Sheldon S. Williamson
Energies 2021, 14(18), 5960; https://doi.org/10.3390/en14185960 - 20 Sep 2021
Cited by 25 | Viewed by 4191
Abstract
Highly nonlinear characteristics of lithium-ion batteries (LIBs) are significantly influenced by the external and internal temperature of the LIB cell. Moreover, a cell temperature beyond the manufacturer’s specified safe operating limit could lead to thermal runaway and even fire hazards and safety concerns [...] Read more.
Highly nonlinear characteristics of lithium-ion batteries (LIBs) are significantly influenced by the external and internal temperature of the LIB cell. Moreover, a cell temperature beyond the manufacturer’s specified safe operating limit could lead to thermal runaway and even fire hazards and safety concerns to operating personnel. Therefore, accurate information of cell internal and surface temperature of LIB is highly crucial for effective thermal management and proper operation of a battery management system (BMS). Accurate temperature information is also essential to BMS for the accurate estimation of various important states of LIB, such as state of charge, state of health and so on. High-capacity LIB packs, used in electric vehicles and grid-tied stationary energy storage system essentially consist of thousands of individual LIB cells. Therefore, installing a physical sensor at each cell, especially at the cell core, is not practically feasible from the solution cost, space and weight point of view. A solution is to develop a suitable estimation strategy which led scholars to propose different temperature estimation schemes aiming to establish a balance among accuracy, adaptability, modelling complexity and computational cost. This article presented an exhaustive review of these estimation strategies covering recent developments, current issues, major challenges, and future research recommendations. The prime intention is to provide a detailed guideline to researchers and industries towards developing a highly accurate, intelligent, adaptive, easy-to-implement and computationally efficient online temperature estimation strategy applicable to health-conscious fast charging and smart onboard BMS. Full article
(This article belongs to the Special Issue Power Electronics and Energy Management for Battery Storage Systems)
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