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Special Issue "Advanced Energy Storage Technologies and Their Applications (AESA)"

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

Deadline for manuscript submissions: closed (15 May 2017)

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Guest Editor
Assoc. Prof. Dr. Rui Xiong

Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, No.5 Zhongguancun Street, Beijing 100081, China
Website | E-Mail
Phone: +86(10)6891-4070
Fax: +86(10)6891-4070
Interests: Electric/hybrid vehicles; Electric/hybrid driven systems; Energy storage and battery management systems; Model-based diagnostics and prognostics
Guest Editor
Assoc. Prof. Dr. Hailong Li

Energy Technology, School of Business, Society and Technology Mälardalens University, Box 883, 721 23 Västerås, Sweden
Website | E-Mail
Interests: smart energy management, including: demand response, efficiency improvement, energy storage, smart energy network, heat transfer enhancement, etc.
Guest Editor
Assist. Prof. Dr. Joe (Xuan) Zhou

Department of Electrical and Computer Engineering, Kettering University, 1700 University Ave., Flint, MI 48504, USA
Website | E-Mail
Interests: materials and systems for energy storage; battery modeling and management for electric vehicles

Special Issue Information

Dear Colleagues,

The depletion of fossil fuels, the increase of energy demands, and the concerns over climate change are the major driving forces for the development of renewable energy, such as solar energy and wind power. However, the intermittency of renewable energy has hindered the deployment of large-scale intermittent renewable energy, which, therefore, has necessitated the development of advanced large-scale energy storage technologies. The use of large-scale energy storage can effectively improve the efficiency of energy resource utilization, and increase the use of variable renewable resources, the energy access, and the end-use sector electrification (e.g., electrification of transport sector).

This Special Issue will provide a platform for presenting the latest research results on the technology development of large-scale energy storage. We welcome research papers about theoretical, methodological and empirical studies, as well as review papers, that provide critical overview on the state of the art of technologies. This special issue is open to all types of energy, such as thermal energy, mechanical energy, electrical energy and chemical energy, using different types of systems, such as phase change materials, batteries, supercapacitors, fuel cells, compressed air, etc., which are applicable to various types of applications, such as heat and power generation, electrical/hybrid transportation, etc.

Topics of interest of this Special Issue include, but are not limited to:
  • Novel energy storage materials and topologies;
  • Application in electrical/hybrid driven system and electrical/hybrid vehicles;
  • Next generation energy storage devices, systems or techniques;
  • Large scale energy storage system modeling, simulation and optimization, including testing and modeling ageing processes;
  • Advanced energy storage management systems, including advanced control algorithms and fault diagnosis/online condition monitoring for energy storage systems;
  • Business model for the application and deployment of energy storage;
  • Lifecycle analysis, repurposing, and recycling

Assoc. Prof. Dr. Rui Xiong
Assoc. Prof. Dr. Hailong Li
Assist. Prof. Dr. Joe Zhou
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 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

  • Battery
  • Ultracapacitor
  • Fuel cell
  • Compressed air
  • Electric vehicles
  • Thermal energy storage
  • Phase change material
  • Energy storage Management System
  • Heat transfer enhancement

Published Papers (23 papers)

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Editorial

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Open AccessEditorial Advanced Energy Storage Technologies and Their Applications (AESA2017)
Energies 2017, 10(9), 1366; https://doi.org/10.3390/en10091366
Received: 24 August 2017 / Revised: 7 September 2017 / Accepted: 7 September 2017 / Published: 9 September 2017
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Abstract
This editorial summarizes the performance of the special issue entitled Advanced Energy Storage Technologies and Applications (AESA), which is published in MDPI’s Energies journal in 2017. The special issue includes a total of 22 papers from four countries. Lithium-ion battery, electric vehicle, and
[...] Read more.
This editorial summarizes the performance of the special issue entitled Advanced Energy Storage Technologies and Applications (AESA), which is published in MDPI’s Energies journal in 2017. The special issue includes a total of 22 papers from four countries. Lithium-ion battery, electric vehicle, and energy storage were the topics attracting the most attentions. New methods have been proposed with very sound results. Full article

Research

Jump to: Editorial, Review

Open AccessArticle Parametric Design of an Ultrahigh-Head Pump-Turbine Runner Based on Multiobjective Optimization
Energies 2017, 10(8), 1169; https://doi.org/10.3390/en10081169
Received: 19 April 2017 / Revised: 29 July 2017 / Accepted: 4 August 2017 / Published: 8 August 2017
Cited by 5 | PDF Full-text (7996 KB) | HTML Full-text | XML Full-text
Abstract
Pumped hydro energy storage (PHES) is currently the only proven large-scale energy storage technology. Frequent changes between pump and turbine operations pose significant challenges in the design of a pump-turbine runner with high efficiency and stability, especially for ultrahigh-head reversible pump-turbine runners. In
[...] Read more.
Pumped hydro energy storage (PHES) is currently the only proven large-scale energy storage technology. Frequent changes between pump and turbine operations pose significant challenges in the design of a pump-turbine runner with high efficiency and stability, especially for ultrahigh-head reversible pump-turbine runners. In the present paper, a multiobjective optimization design system is used to develop an ultrahigh-head runner with good overall performance. An optimum configuration was selected from the optimization results. The effects of key design parameters—namely blade loading and blade lean—were then investigated in order to determine their effects on runner efficiency and cavitation characteristics. The paper highlights the guidelines for application of inverse design method to high-head reversible pump-turbine runners. Middle-loaded blade loading distribution on the hub, back-loaded distribution on the shroud, and large positive blade lean angle on the high pressure side are good for the improvement of runner power performance. The cavitation characteristic is mainly influenced by the blade loading distribution near the low pressure side, and large blade lean angles have a negative impact on runner cavitation characteristics. Full article
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Open AccessArticle Analysis of Low Temperature Preheating Effect Based on Battery Temperature-Rise Model
Energies 2017, 10(8), 1121; https://doi.org/10.3390/en10081121
Received: 13 May 2017 / Revised: 22 June 2017 / Accepted: 27 July 2017 / Published: 1 August 2017
Cited by 3 | PDF Full-text (3253 KB) | HTML Full-text | XML Full-text
Abstract
It is difficult to predict the heating time and power consumption associated with the self-heating process of lithium-ion batteries at low temperatures. A temperature-rise model considering the dynamic changes in battery temperature and state of charge is thus proposed. When this model is
[...] Read more.
It is difficult to predict the heating time and power consumption associated with the self-heating process of lithium-ion batteries at low temperatures. A temperature-rise model considering the dynamic changes in battery temperature and state of charge is thus proposed. When this model is combined with the ampere-hour integral method, the quantitative relationship among the discharge rate, heating time, and power consumption, during the constant-current discharge process in an internally self-heating battery, is realized. Results show that the temperature-rise model can accurately reflect actual changes in battery temperature. The results indicate that the discharge rate and the heating time present an exponential decreasing trend that is similar to the discharge rate and the power consumption. When a 2 C discharge rate is selected, the battery temperature can rise from −10 °C to 5 °C in 280 s. In this scenario, power consumption of the heating process does not exceed 15% of the rated capacity. As the discharge rate gradually reduced, the heating time and power consumption of the heating process increase slowly. When the discharge rate is 1 C, the heating time is more than 1080 s and the power consumption approaches 30% of the rated capacity. The effect of discharge rate on the heating time and power consumption during the heating process is significantly enhanced when it is less than 1 C. Full article
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Open AccessArticle Thermodynamic Analysis of Three Compressed Air Energy Storage Systems: Conventional, Adiabatic, and Hydrogen-Fueled
Energies 2017, 10(7), 1020; https://doi.org/10.3390/en10071020
Received: 10 May 2017 / Revised: 15 June 2017 / Accepted: 27 June 2017 / Published: 18 July 2017
Cited by 3 | PDF Full-text (3582 KB) | HTML Full-text | XML Full-text
Abstract
We present analyses of three families of compressed air energy storage (CAES) systems: conventional CAES, in which the heat released during air compression is not stored and natural gas is combusted to provide heat during discharge; adiabatic CAES, in which the compression heat
[...] Read more.
We present analyses of three families of compressed air energy storage (CAES) systems: conventional CAES, in which the heat released during air compression is not stored and natural gas is combusted to provide heat during discharge; adiabatic CAES, in which the compression heat is stored; and CAES in which the compression heat is used to assist water electrolysis for hydrogen storage. The latter two methods involve no fossil fuel combustion. We modeled both a low-temperature and a high-temperature electrolysis process for hydrogen production. Adiabatic CAES (A-CAES) with physical storage of heat is the most efficient option with an exergy efficiency of 69.5% for energy storage. The exergy efficiency of the conventional CAES system is estimated to be 54.3%. Both high-temperature and low-temperature electrolysis CAES systems result in similar exergy efficiencies (35.6% and 34.2%), partly due to low efficiency of the electrolyzer cell. CAES with high-temperature electrolysis has the highest energy storage density (7.9 kWh per m3 of air storage volume), followed by A-CAES (5.2 kWh/m3). Conventional CAES and CAES with low-temperature electrolysis have similar energy densities of 3.1 kWh/m3. Full article
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Open AccessArticle Big-Data-Based Thermal Runaway Prognosis of Battery Systems for Electric Vehicles
Energies 2017, 10(7), 919; https://doi.org/10.3390/en10070919
Received: 15 May 2017 / Revised: 25 June 2017 / Accepted: 26 June 2017 / Published: 4 July 2017
Cited by 1 | PDF Full-text (15729 KB) | HTML Full-text | XML Full-text
Abstract
A thermal runaway prognosis scheme for battery systems in electric vehicles is proposed based on the big data platform and entropy method. It realizes the diagnosis and prognosis of thermal runaway simultaneously, which is caused by the temperature fault through monitoring battery temperature
[...] Read more.
A thermal runaway prognosis scheme for battery systems in electric vehicles is proposed based on the big data platform and entropy method. It realizes the diagnosis and prognosis of thermal runaway simultaneously, which is caused by the temperature fault through monitoring battery temperature during vehicular operations. A vast quantity of real-time voltage monitoring data is derived from the National Service and Management Center for Electric Vehicles (NSMC-EV) in Beijing. Furthermore, a thermal security management strategy for thermal runaway is presented under the Z-score approach. The abnormity coefficient is introduced to present real-time precautions of temperature abnormity. The results illustrated that the proposed method can accurately forecast both the time and location of the temperature fault within battery packs. The presented method is flexible in all disorder systems and possesses widespread application potential in not only electric vehicles, but also other areas with complex abnormal fluctuating environments. Full article
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Open AccessArticle Optimization of Battery Capacity Decay for Semi-Active Hybrid Energy Storage System Equipped on Electric City Bus
Energies 2017, 10(6), 792; https://doi.org/10.3390/en10060792
Received: 9 May 2017 / Revised: 1 June 2017 / Accepted: 6 June 2017 / Published: 9 June 2017
Cited by 1 | PDF Full-text (4836 KB) | HTML Full-text | XML Full-text
Abstract
In view of severe changes in temperature during different seasons in cold areas of northern China, the decay of battery capacity of electric vehicles poses a problem. This paper uses an electric bus power system with semi-active hybrid energy storage system (HESS) as
[...] Read more.
In view of severe changes in temperature during different seasons in cold areas of northern China, the decay of battery capacity of electric vehicles poses a problem. This paper uses an electric bus power system with semi-active hybrid energy storage system (HESS) as the research object and proposes a convex power distribution strategy to optimize the battery current that represents degradation of battery capacity based on the analysis of semi-empirical LiFePO4 battery life decline model. Simulation results show that, at a room temperature of 25 °C, during a daily trip organized by the Harbin City Driving Cycle including four cycle lines and four charging phases, the percentage of battery degradation was 9.6 × 10−3%. According to the average temperature of different months in Harbin, the percentage of battery degradation of the power distribution strategy proposed in this paper is 3.15% in one year; the electric bus can operate for 6.4 years until its capacity reduces to 80% of its initial value, and it can operate for 0.51 year more than the rule-based power distribution strategy. Full article
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Open AccessArticle PTC Self-Heating Experiments and Thermal Modeling of Lithium-Ion Battery Pack in Electric Vehicles
Energies 2017, 10(4), 572; https://doi.org/10.3390/en10040572
Received: 10 March 2017 / Revised: 18 April 2017 / Accepted: 18 April 2017 / Published: 22 April 2017
Cited by 2 | PDF Full-text (5838 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a positive temperature coefficient (PTC) self-heating method, in which EVs can be operated independently of external power source at low temperature, with a lithium-ion battery (LIB) pack discharging electricity to provide PTC material with power. Three comparative heating experiments have
[...] Read more.
This paper proposes a positive temperature coefficient (PTC) self-heating method, in which EVs can be operated independently of external power source at low temperature, with a lithium-ion battery (LIB) pack discharging electricity to provide PTC material with power. Three comparative heating experiments have been carried out respectively. With charge/discharge tests implemented, results demonstrate the superiority of the self-heating method, proving that the discharge capability, especially the discharge capacity of the self-heated pack is better than that of the external power heated pack. In order to evaluate the heating effect of this method, further studies are conducted on temperature distribution uniformity in the heated pack. Firstly, a geometric model is established, and heat-generation rate of PTC materials and LIB are calculated. Then, thermal characteristics of the self-heating experiment processes are numerically simulated, validating the accuracy of our modeling and confirming that temperature distributions inside the pack after heating are kept in good uniformity. Therefore, the PTC self-heating method is verified to have a significant effect on the improvement of performance of LIB at low temperature. Full article
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Open AccessArticle Impact of Silicon Carbide Devices on the Powertrain Systems in Electric Vehicles
Energies 2017, 10(4), 533; https://doi.org/10.3390/en10040533
Received: 7 February 2017 / Revised: 11 April 2017 / Accepted: 11 April 2017 / Published: 14 April 2017
Cited by 4 | PDF Full-text (18295 KB) | HTML Full-text | XML Full-text
Abstract
The DC/DC converters and DC/AC inverters based on silicon carbide (SiC) devices as battery interfaces, motor drives, etc., in electric vehicles (EVs) benefit from their low resistances, fast switching speed, high temperature tolerance, etc. Such advantages could improve the power density and efficiency
[...] Read more.
The DC/DC converters and DC/AC inverters based on silicon carbide (SiC) devices as battery interfaces, motor drives, etc., in electric vehicles (EVs) benefit from their low resistances, fast switching speed, high temperature tolerance, etc. Such advantages could improve the power density and efficiency of the converter and inverter systems in EVs. Furthermore, the total powertrain system in EVs is also affected by the converter and inverter system based on SiC, especially the capacity of the battery and the overall system efficiency. Therefore, this paper investigates the impact of SiC on the powertrain systems in EVs. First, the characteristics of SiC are evaluated by a double pulse test (DPT). Then, the power losses of the DC/DC converter, DC/AC inverter, and motor are measured. The measured results are assigned into a powertrain model built in the Advanced Vehicle Simulator (ADVISOR) software in order to explore a direct correlation between the SiC and the performance of the powertrain system in EVs, which are then compared with the conventional powertrain system based on silicon (Si). The test and simulation results demonstrate that the efficiency of the overall powertrain is significantly improved and the capacity of the battery can be remarkably reduced if the Si is replaced by SiC in the powertrain system. Full article
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Open AccessArticle Data-Driven Predictive Torque Coordination Control during Mode Transition Process of Hybrid Electric Vehicles
Energies 2017, 10(4), 441; https://doi.org/10.3390/en10040441
Received: 16 November 2016 / Revised: 20 March 2017 / Accepted: 22 March 2017 / Published: 1 April 2017
Cited by 3 | PDF Full-text (2188 KB) | HTML Full-text | XML Full-text
Abstract
Torque coordination control significantly affects the mode transition quality during the mode transition dynamic process of hybrid electric vehicles (HEV). Most of the existing torque coordination control methods are based on the mechanism model, whose control effect heavily depends on the modeling accuracy
[...] Read more.
Torque coordination control significantly affects the mode transition quality during the mode transition dynamic process of hybrid electric vehicles (HEV). Most of the existing torque coordination control methods are based on the mechanism model, whose control effect heavily depends on the modeling accuracy of the HEV powertrain. However, the powertrain structure is so complex, that it is difficult to establish its precise mechanism model. In this paper, a torque coordination control strategy using the data-driven predictive control (DDPC) technique is proposed to overcome the shortcomings of mechanism model-based control methods for a clutch-enabled HEV. The proposed control strategy is only based on the measured input-output data in the HEV powertrain, and no mechanism model is needed. The conflicting control requirements of comfortability and economy are included in the cost function. The actual physical constraints of actuators are also explicitly taken into account in the solving process of the data-driven predictive controller. The co-simulation results in Cruise and Simulink validate the effectiveness of the proposed control strategy and demonstrate that the DDPC method can achieve less vehicle jerk, faster mode transition and smaller clutch frictional losses compared with the traditional model predictive control (MPC) method. Full article
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Open AccessArticle Optimal Energy Management Strategy for a Plug-in Hybrid Electric Vehicle Based on Road Grade Information
Energies 2017, 10(4), 412; https://doi.org/10.3390/en10040412
Received: 9 January 2017 / Revised: 11 March 2017 / Accepted: 18 March 2017 / Published: 23 March 2017
Cited by 3 | PDF Full-text (7251 KB) | HTML Full-text | XML Full-text
Abstract
Energy management strategies (EMSs) are critical for the improvement of fuel economy of plug-in hybrid electric vehicles (PHEVs). However, conventional EMSs hardly consider the influence of uphill terrain on the fuel economy and battery life, leaving vehicles with insufficient battery power for continuous
[...] Read more.
Energy management strategies (EMSs) are critical for the improvement of fuel economy of plug-in hybrid electric vehicles (PHEVs). However, conventional EMSs hardly consider the influence of uphill terrain on the fuel economy and battery life, leaving vehicles with insufficient battery power for continuous uphill terrains. Hence, in this study, an optimal control strategy for a PHEV based on the road grade information is proposed. The target state of charge (SOC) is estimated based on the road grade information as well as the predicted driving cycle on uphill road obtained from the GPS/GIS system. Furthermore, the trajectory of the SOC is preplanned to ensure sufficient electricity for the uphill terrain in the charge depleting (CD) and charge sustaining (CS) modes. The genetic algorithm is applied to optimize the parameters of the control strategy to maintain the SOC of battery in the CD mode. The pre-charge mode is designed to charge the battery in the CS mode from a reasonable distance before the uphill terrain. Finally, the simulation model of the powertrain system for the PHEV is established using MATLAB/Simulink platform. The results show that the proposed control strategy based on road-grade information helps successfully achieve better fuel economy and longer battery life. Full article
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Open AccessEditor’s ChoiceArticle Online Reliable Peak Charge/Discharge Power Estimation of Series-Connected Lithium-Ion Battery Packs
Energies 2017, 10(3), 390; https://doi.org/10.3390/en10030390
Received: 22 January 2017 / Revised: 27 February 2017 / Accepted: 7 March 2017 / Published: 19 March 2017
Cited by 2 | PDF Full-text (8277 KB) | HTML Full-text | XML Full-text
Abstract
The accurate peak power estimation of a battery pack is essential to the power-train control of electric vehicles (EVs). It helps to evaluate the maximum charge and discharge capability of the battery system, and thus to optimally control the power-train system to meet
[...] Read more.
The accurate peak power estimation of a battery pack is essential to the power-train control of electric vehicles (EVs). It helps to evaluate the maximum charge and discharge capability of the battery system, and thus to optimally control the power-train system to meet the requirement of acceleration, gradient climbing and regenerative braking while achieving a high energy efficiency. A novel online peak power estimation method for series-connected lithium-ion battery packs is proposed, which considers the influence of cell difference on the peak power of the battery packs. A new parameter identification algorithm based on adaptive ratio vectors is designed to online identify the parameters of each individual cell in a series-connected battery pack. The ratio vectors reflecting cell difference are deduced strictly based on the analysis of battery characteristics. Based on the online parameter identification, the peak power estimation considering cell difference is further developed. Some validation experiments in different battery aging conditions and with different current profiles have been implemented to verify the proposed method. The results indicate that the ratio vector-based identification algorithm can achieve the same accuracy as the repetitive RLS (recursive least squares) based identification while evidently reducing the computation cost, and the proposed peak power estimation method is more effective and reliable for series-connected battery packs due to the consideration of cell difference. Full article
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Open AccessArticle Impact of Silicon Carbide Devices on the Dynamic Performance of Permanent Magnet Synchronous Motor Drive Systems for Electric Vehicles
Energies 2017, 10(3), 364; https://doi.org/10.3390/en10030364
Received: 5 January 2017 / Revised: 5 March 2017 / Accepted: 6 March 2017 / Published: 15 March 2017
Cited by 2 | PDF Full-text (8998 KB) | HTML Full-text | XML Full-text
Abstract
This paper investigates the impact of silicon carbide (SiC) metal oxide semiconductor field effect transistors (MOSFETs) on the dynamic performance of permanent magnet synchronous motor (PMSM) drive systems. The characteristics of SiC MOSFETs are evaluated experimentally taking into account temperature variations. Then the
[...] Read more.
This paper investigates the impact of silicon carbide (SiC) metal oxide semiconductor field effect transistors (MOSFETs) on the dynamic performance of permanent magnet synchronous motor (PMSM) drive systems. The characteristics of SiC MOSFETs are evaluated experimentally taking into account temperature variations. Then the switching characteristics are firstly introduced into the transfer function of a SiC-inverter fed PMSM drive system. The main contribution of this paper is the investigation of the dynamic control performance features such as the fast response, the stability and the robustness of the drive system considering the characteristics of SiC MOSFETs. All the results of the SiC-drive system are compared to the silicon-(Si) insulated gate bipolar transistors (IGBTs) drive system counterpart, and the SiC-drive system manifests a higher dynamic performance than the Si-drive system. The analytical results have been effectively validated by experiments on a test bench. Full article
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Open AccessArticle Numerical Analysis of Shell-and-Tube Type Latent Thermal Energy Storage Performance with Different Arrangements of Circular Fins
Energies 2017, 10(3), 274; https://doi.org/10.3390/en10030274
Received: 1 December 2016 / Revised: 15 February 2017 / Accepted: 20 February 2017 / Published: 25 February 2017
Cited by 5 | PDF Full-text (2656 KB) | HTML Full-text | XML Full-text
Abstract
Latent thermal energy storage (LTS) systems are versatile due to their high-energy storage density within a small temperature range. In shell-and-tube type storage systems fins can be used in order to achieve enhanced charging and discharging power. Typically, circular fins are evenly distributed
[...] Read more.
Latent thermal energy storage (LTS) systems are versatile due to their high-energy storage density within a small temperature range. In shell-and-tube type storage systems fins can be used in order to achieve enhanced charging and discharging power. Typically, circular fins are evenly distributed over the length of the heat exchanger pipe. However, it is yet to be proven that this allocation is the most suitable for every kind of system and application. Consequently, within this paper, a simulation model was developed in order to examine the effect of different fin distributions on the performance of shell-and-tube type latent thermal storage units at discharge. The model was set up in MATLAB Simulink R2015b (The MathWorks, Inc., Natick, MA, USA) based on the enthalpy method and validated by a reference model designed in ANSYS Fluent 15.0 (ANSYS, Inc., Canonsburg, PA, USA). The fin density of the heat exchanger pipe was increased towards the pipe outlet. This concentration of fins was implemented linearly, exponentially or suddenly with the total number of fins remaining constant during the variation of fin allocations. Results show that there is an influence of fin allocation on storage performance. However, the average storage performance at total discharge only increased by three percent with the best allocation compared to an equidistant arrangement. Full article
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Open AccessArticle A Cell-to-Cell Equalizer Based on Three-Resonant-State Switched-Capacitor Converters for Series-Connected Battery Strings
Energies 2017, 10(2), 206; https://doi.org/10.3390/en10020206
Received: 23 December 2016 / Revised: 1 February 2017 / Accepted: 6 February 2017 / Published: 11 February 2017
Cited by 8 | PDF Full-text (8669 KB) | HTML Full-text | XML Full-text
Abstract
Due to the low cost, small size, and ease of control, the switched-capacitor (SC) battery equalizers are promising among active balancing methods. However, it is difficult to achieve the full cell equalization for the SC equalizers due to the inevitable voltage drops across
[...] Read more.
Due to the low cost, small size, and ease of control, the switched-capacitor (SC) battery equalizers are promising among active balancing methods. However, it is difficult to achieve the full cell equalization for the SC equalizers due to the inevitable voltage drops across Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET) switches. Moreover, when the voltage gap among cells is larger, the balancing efficiency is lower, while the balancing speed becomes slower as the voltage gap gets smaller. In order to soften these downsides, this paper proposes a cell-to-cell battery equalization topology with zero-current switching (ZCS) and zero-voltage gap (ZVG) among cells based on three-resonant-state SC converters. Based on the conventional inductor-capacitor (LC) converter, an additional resonant path is built to release the charge of the capacitor into the inductor in each switching cycle, which lays the foundations for obtaining ZVG among cells, improves the balancing efficiency at a large voltage gap, and increases the balancing speed at a small voltage gap. A four-lithium-ion-cell prototype is applied to validate the theoretical analysis. Experiment results demonstrate that the proposed topology has good equalization performances with fast equalization, ZCS, and ZVG among cells. Full article
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Open AccessEditor’s ChoiceArticle Application of Liquid Hydrogen with SMES for Efficient Use of Renewable Energy in the Energy Internet
Energies 2017, 10(2), 185; https://doi.org/10.3390/en10020185
Received: 6 January 2017 / Revised: 1 February 2017 / Accepted: 2 February 2017 / Published: 8 February 2017
Cited by 6 | PDF Full-text (6620 KB) | HTML Full-text | XML Full-text
Abstract
Considering that generally frequency instability problems occur due to abrupt variations in load demand growth and power variations generated by different renewable energy sources (RESs), the application of superconducting magnetic energy storage (SMES) may become crucial due to its rapid response features. In
[...] Read more.
Considering that generally frequency instability problems occur due to abrupt variations in load demand growth and power variations generated by different renewable energy sources (RESs), the application of superconducting magnetic energy storage (SMES) may become crucial due to its rapid response features. In this paper, liquid hydrogen with SMES (LIQHYSMES) is proposed to play a role in the future energy internet in terms of its combination of the SMES and the liquid hydrogen storage unit, which can help to overcome the capacity limit and high investment cost disadvantages of SMES. The generalized predictive control (GPC) algorithm is presented to be appreciatively used to eliminate the frequency deviations of the isolated micro energy grid including the LIQHYSMES and RESs. A benchmark micro energy grid with distributed generators (DGs), electrical vehicle (EV) stations, smart loads and a LIQHYSMES unit is modeled in the Matlab/Simulink environment. The simulation results show that the proposed GPC strategy can reschedule the active power output of each component to maintain the stability of the grid. In addition, in order to improve the performance of the SMES, a detailed optimization design of the superconducting coil is conducted, and the optimized SMES unit can offer better technical advantages in damping the frequency fluctuations. Full article
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Open AccessArticle Pressure Fluctuations in the S-Shaped Region of a Reversible Pump-Turbine
Energies 2017, 10(1), 96; https://doi.org/10.3390/en10010096
Received: 11 June 2016 / Revised: 16 December 2016 / Accepted: 9 January 2017 / Published: 13 January 2017
Cited by 7 | PDF Full-text (8498 KB) | HTML Full-text | XML Full-text
Abstract
Numerical simulations were performed to investigate pressure fluctuations in the S-shaped region of a pump-turbine model. Analyses focused on pressure fluctuations in the draft tube and in the gap between the guide vanes and runner. Calculations were made under six different operating conditions
[...] Read more.
Numerical simulations were performed to investigate pressure fluctuations in the S-shaped region of a pump-turbine model. Analyses focused on pressure fluctuations in the draft tube and in the gap between the guide vanes and runner. Calculations were made under six different operating conditions with a constant guide vane opening, and the best efficiency point, runaway point, and low-discharge point in the turbine brake zone were determined. The simulated results were compared with experimental measurements. In the draft tube, a twin vortex rope was observed. In the gap between the guide vanes and runner, a low frequency component was captured at both the runaway and low-discharge points in the turbine brake zone, which rotated at 65% of the runner frequency. This low frequency component was induced by the rotating stall phenomenon. At the runaway point, a single stall cell was found in the gap between the guide vanes and runner, while at the low-discharge point, four stall cells were observed. Full article
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Open AccessArticle Battery Internal Temperature Estimation for LiFePO4 Battery Based on Impedance Phase Shift under Operating Conditions
Energies 2017, 10(1), 60; https://doi.org/10.3390/en10010060
Received: 17 November 2016 / Revised: 26 December 2016 / Accepted: 3 January 2017 / Published: 6 January 2017
Cited by 5 | PDF Full-text (5051 KB) | HTML Full-text | XML Full-text
Abstract
An impedance-based temperature estimation method is investigated considering the electrochemical non-equilibrium with short-term relaxation time for facilitating the vehicular application. Generally, sufficient relaxation time is required for battery electrochemical equilibrium before the impedance measurement. A detailed experiment is performed to investigate the regularity
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An impedance-based temperature estimation method is investigated considering the electrochemical non-equilibrium with short-term relaxation time for facilitating the vehicular application. Generally, sufficient relaxation time is required for battery electrochemical equilibrium before the impedance measurement. A detailed experiment is performed to investigate the regularity of the battery impedance in short-term relaxation time after switch-off current excitation, which indicates that the impedance can be measured and also has systematical decrement with the relaxation time growth. Based on the discussion of impedance variation in electrochemical perspective, as well as the monotonic relationship between impedance phase shift and battery internal temperature in the electrochemical equilibrium state, an exponential equation that accounts for both measured phase shift and relaxation time is established to correct the measuring deviation caused by electrochemical non-equilibrium. Then, a multivariate linear equation coupled with ambient temperature is derived considering the temperature gradients between the active part and battery surface. Equations stated above are all identified with the embedded thermocouple experimentally. In conclusion, the temperature estimation method can be a valuable alternative for temperature monitoring during cell operating, and serve the functionality as an efficient implementation in battery thermal management system for electric vehicles (EVs) and hybrid electric vehicles (HEVs). Full article
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Open AccessArticle A Dynamic Control Strategy for Hybrid Electric Vehicles Based on Parameter Optimization for Multiple Driving Cycles and Driving Pattern Recognition
Energies 2017, 10(1), 54; https://doi.org/10.3390/en10010054
Received: 5 August 2016 / Revised: 24 December 2016 / Accepted: 26 December 2016 / Published: 5 January 2017
Cited by 9 | PDF Full-text (6642 KB) | HTML Full-text | XML Full-text
Abstract
The driving pattern has an important influence on the parameter optimization of the energy management strategy (EMS) for hybrid electric vehicles (HEVs). A new algorithm using simulated annealing particle swarm optimization (SA-PSO) is proposed for parameter optimization of both the power system and
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The driving pattern has an important influence on the parameter optimization of the energy management strategy (EMS) for hybrid electric vehicles (HEVs). A new algorithm using simulated annealing particle swarm optimization (SA-PSO) is proposed for parameter optimization of both the power system and control strategy of HEVs based on multiple driving cycles in order to realize the minimum fuel consumption without impairing the dynamic performance. Furthermore, taking the unknown of the actual driving cycle into consideration, an optimization method of the dynamic EMS based on driving pattern recognition is proposed in this paper. The simulation verifications for the optimized EMS based on multiple driving cycles and driving pattern recognition are carried out using Matlab/Simulink platform. The results show that compared with the original EMS, the former strategy reduces the fuel consumption by 4.36% and the latter one reduces the fuel consumption by 11.68%. A road test on the prototype vehicle is conducted and the effectiveness of the proposed EMS is validated by the test data. Full article
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Open AccessEditor’s ChoiceArticle Improved Battery Parameter Estimation Method Considering Operating Scenarios for HEV/EV Applications
Energies 2017, 10(1), 5; https://doi.org/10.3390/en10010005
Received: 3 October 2016 / Revised: 7 December 2016 / Accepted: 13 December 2016 / Published: 22 December 2016
Cited by 9 | PDF Full-text (7886 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account,
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This paper presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account, and two separate sets of model parameters are estimated through different parts of the pulse-rest test. The model parameters for the constant-charging scenario are estimated from the data in the pulse-charging periods, while the model parameters for the dynamic driving scenario are estimated from the data in the rest periods, and the length of the fitted dataset is determined by the spectrum analysis of the load current. In addition, the unsaturated phenomenon caused by the long-term resistor-capacitor (RC) network is analyzed, and the initial voltage expressions of the RC networks in the fitting functions are improved to ensure a higher model fidelity. Simulation and experiment results validated the feasibility of the developed estimation method. Full article
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Open AccessArticle A Generalized SOC-OCV Model for Lithium-Ion Batteries and the SOC Estimation for LNMCO Battery
Energies 2016, 9(11), 900; https://doi.org/10.3390/en9110900
Received: 19 August 2016 / Revised: 19 October 2016 / Accepted: 26 October 2016 / Published: 1 November 2016
Cited by 11 | PDF Full-text (3710 KB) | HTML Full-text | XML Full-text
Abstract
A state-of-charge (SOC) versus open-circuit-voltage (OCV) model developed for batteries should preferably be simple, especially for real-time SOC estimation. It should also be capable of representing different types of lithium-ion batteries (LIBs), regardless of temperature change and battery degradation. It must therefore be
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A state-of-charge (SOC) versus open-circuit-voltage (OCV) model developed for batteries should preferably be simple, especially for real-time SOC estimation. It should also be capable of representing different types of lithium-ion batteries (LIBs), regardless of temperature change and battery degradation. It must therefore be generic, robust and adaptive, in addition to being accurate. These challenges have now been addressed by proposing a generalized SOC-OCV model for representing a few most widely used LIBs. The model is developed from analyzing electrochemical processes of the LIBs, before arriving at the sum of a logarithmic, a linear and an exponential function with six parameters. Values for these parameters are determined by a nonlinear estimation algorithm, which progressively shows that only four parameters need to be updated in real time. The remaining two parameters can be kept constant, regardless of temperature change and aging. Fitting errors demonstrated with different types of LIBs have been found to be within 0.5%. The proposed model is thus accurate, and can be flexibly applied to different LIBs, as verified by hardware-in-the-loop simulation designed for real-time SOC estimation. Full article
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Open AccessArticle Modeling of a Pouch Lithium Ion Battery Using a Distributed Parameter Equivalent Circuit for Internal Non-Uniformity Analysis
Energies 2016, 9(11), 865; https://doi.org/10.3390/en9110865
Received: 18 August 2016 / Revised: 9 October 2016 / Accepted: 10 October 2016 / Published: 25 October 2016
Cited by 6 | PDF Full-text (1359 KB) | HTML Full-text | XML Full-text
Abstract
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.
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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. Full article
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Review

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Open AccessReview Seasonal Thermal-Energy Storage: A Critical Review on BTES Systems, Modeling, and System Design for Higher System Efficiency
Energies 2017, 10(6), 743; https://doi.org/10.3390/en10060743
Received: 24 February 2017 / Revised: 3 May 2017 / Accepted: 14 May 2017 / Published: 25 May 2017
Cited by 3 | PDF Full-text (1948 KB) | HTML Full-text | XML Full-text
Abstract
Buildings consume approximately ¾ of the total electricity generated in the United States, contributing significantly to fossil fuel emissions. Sustainable and renewable energy production can reduce fossil fuel use, but necessitates storage for energy reliability in order to compensate for the intermittency of
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Buildings consume approximately ¾ of the total electricity generated in the United States, contributing significantly to fossil fuel emissions. Sustainable and renewable energy production can reduce fossil fuel use, but necessitates storage for energy reliability in order to compensate for the intermittency of renewable energy generation. Energy storage is critical for success in developing a sustainable energy grid because it facilitates higher renewable energy penetration by mitigating the gap between energy generation and demand. This review analyzes recent case studies—numerical and field experiments—seen by borehole thermal energy storage (BTES) in space heating and domestic hot water capacities, coupled with solar thermal energy. System design, model development, and working principle(s) are the primary focus of this analysis. A synopsis of the current efforts to effectively model BTES is presented as well. The literature review reveals that: (1) energy storage is most effective when diurnal and seasonal storage are used in conjunction; (2) no established link exists between BTES computational fluid dynamics (CFD) models integrated with whole building energy analysis tools, rather than parameter-fit component models; (3) BTES has less geographical limitations than Aquifer Thermal Energy Storage (ATES) and lower installation cost scale than hot water tanks and (4) BTES is more often used for heating than for cooling applications. Full article
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Open AccessReview Large-Scale Electrochemical Energy Storage in High Voltage Grids: Overview of the Italian Experience
Energies 2017, 10(1), 108; https://doi.org/10.3390/en10010108
Received: 24 October 2016 / Revised: 14 December 2016 / Accepted: 10 January 2017 / Published: 17 January 2017
Cited by 10 | PDF Full-text (7561 KB) | HTML Full-text | XML Full-text
Abstract
This paper offers a wide overview on the large-scale electrochemical energy projects installed in the high voltage Italian grid. Detailed descriptions of energy (charge/discharge times of about 8 h) and power intensive (charge/discharge times ranging from 0.5 h to 4 h) installations are
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This paper offers a wide overview on the large-scale electrochemical energy projects installed in the high voltage Italian grid. Detailed descriptions of energy (charge/discharge times of about 8 h) and power intensive (charge/discharge times ranging from 0.5 h to 4 h) installations are presented with some insights into the authorization procedures, safety features, and ancillary services. These different charge/discharge times reflect the different operation uses inside the electric grid. Energy intensive storage aims at decoupling generation and utilization since, in the southern part of Italy, there has been a great growth of wind farms: these areas are characterized by a surplus of generation with respect to load absorption and to the net transport capacity of the 150 kV high voltage backbones. Power intensive storage aims at providing ancillary services inside the electric grid as primary and secondary frequency regulation, synthetic rotational inertia, and further functionalities. The return on experience of Italian installations will be able to play a key role also for other countries and other transmission system operators. Full article
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