| 1. |
- Wang, Kai, et al.
(författare)
-
Zinc anode based alkaline energy storage system: Recent progress and future perspectives of zinc–silver battery
- 2024
-
Ingår i: Energy Storage Materials. - 2405-8297. ; 69
-
Forskningsöversikt (refereegranskat)abstract
- Rechargeable zinc-based batteries have come to the forefront of energy storage field with a surprising pace during last decade due to the advantageous safety, abundance and relatively low cost, making them important supplements of lithium-ion batteries. As a significant role in zinc-based batteries, zinc-silver battery owns the advantages of high specific energy density, stable working voltage, high charging efficiency, safety and environmental friendliness, and it has been widely used in military such as in aerospace, deep water manned and civil field such as energy supply for watch and hearing aid. However, it is still suffering from a few drawbacks such as unsatisfactory cycle life, low utilization of the cathode. This review introduces the basic principles of zinc-silver batteries and elaborates the battery configurations aiming to understand its working mechanisms as well as the related issues. Most importantly, the very recent research updates and the concerns have arisen in the development are summarized from conventional cell to flexible device and hybrid device. Finally, the challenges and perspectives of zinc-silver batteries are further prospected to give a broad idea to readers new in the area and trigger inspirations for motivated researchers to further widen the utilization of silver-zinc batteries.
|
|
| 2. |
- Tang, Xiaopeng, et al.
(författare)
-
A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging
- 2019
-
Ingår i: Energy Conversion and Management. - : Elsevier BV. - 0196-8904. ; 180, s. 162-170
-
Tidskriftsartikel (refereegranskat)abstract
- Temperature and cell aging are two major factors that influence the reliability and safety of Li-ion batteries. A general battery model considering both temperature and degradation is often difficult to develop, given the fact that there are many different types of cells with different shapes and/or internal chemical components. In response, a migration-based framework is proposed in this paper for battery modeling, in which the effects of temperature and aging are treated as uncertainties. An accurate model for a fresh cell is established first and then migrated to the degraded batteries through a Bayes Monte Carlo method. Experiments are carried out on both LiFePO4 batteries and Li(Ni1/3Co1/3Mn1/3) O2 batteries under various ambient temperatures and aging levels. The results indicate that the typical voltage prediction error can be limited within ±20 mV, for the cases of temperature change up to 40 °C, and capacity degradation up to 20%. The proposed method paves ways to an effective battery management and energy control for electric vehicles or micro grid applications.
|
|
| 3. |
- Tang, Xiaopeng, et al.
(författare)
-
Run-to-Run Control for Active Balancing of Lithium Iron Phosphate Battery Packs
- 2020
-
Ingår i: IEEE Transactions on Power Electronics. - 0885-8993 .- 1941-0107. ; 35:2, s. 1499-1512
-
Tidskriftsartikel (refereegranskat)abstract
- © 1986-2012 IEEE. Lithium iron phosphate battery packs are widely employed for energy storage in electrified vehicles and power grids. However, their flat voltage curves rendering the weakly observable state of charge are a critical stumbling block for charge equalization management. This paper focuses on the real-time active balancing of series-connected lithium iron phosphate batteries. In the absence of accurate in situ state information in the voltage plateau, a balancing current ratio (BCR) based algorithm is proposed for battery balancing. Then, BCR-based and voltage-based algorithms are fused, responsible for the balancing task within and beyond the voltage plateau, respectively. The balancing process is formulated as a batch-based run-to-run control problem, as the first time in the research area of battery management. The control algorithm acts in two timescales, including timewise control within each batch run and batchwise control at the end of each batch. Hardware-in-the-loop experiments demonstrate that the proposed balancing algorithm is able to release 97.1% of the theoretical capacity and can improve the capacity utilization by 5.7% from its benchmarking algorithm. Furthermore, the proposed algorithm can be coded in C language with the binary code in 118 328 bytes only and, thus, is readily implementable in real time.
|
|
| 4. |
- Dong, Guangzhong, 1991, et al.
(författare)
-
Dynamic Bayesian Network based Lithium-ion Battery Health Prognosis for Electric Vehicles
- 2021
-
Ingår i: IEEE Transactions on Industrial Electronics. - 0278-0046 .- 1557-9948. ; 68:11, s. 10949-20958
-
Tidskriftsartikel (refereegranskat)abstract
- IEEE Battery prognostics and health management (PHM) are essential for lithium-ion batteries in electric vehicles. In the battery PHM, accurate estimation of the battery state of health (SOH) and prediction of the remaining useful life (RUL) are crucial to ensure safe and efficient battery operation. This paper presents a probabilistic method for the battery degradation modeling and health prognosis based on the features extracted from the charging process using the dynamic Bayesian network (DBN). First, an aggregated feature, combining the incremental capacity analysis (ICA) of constant-current (CC) charging and the time constant of constant-voltage (CV) charging, is developed to characterize the battery degradation dynamics in case some CC or CV charging information is absent. The DBN is then employed to explore the underlying correlation between the battery aging and the extracted features. The proposed model treats the degradation dynamics as a rich family of probability distributions to model real-world battery operation more accurately. Moreover, the battery SOH estimation and RUL prediction are carried out using the particle filtering (PF) inference algorithm. Experimental tests are conducted on two different battery cells and the results show that the proposed methods can provide accurate and robust battery SOH estimation and reliable RUL prediction.
|
|
| 5. |
- Sun, Weiwei, et al.
(författare)
-
Monodispersed FeS 2 Electrocatalyst Anchored to Nitrogen-Doped Carbon Host for Lithium–Sulfur Batteries
- 2022
-
Ingår i: Advanced Functional Materials. - : Wiley. - 1616-3028 .- 1616-301X. ; 32:43
-
Tidskriftsartikel (refereegranskat)abstract
- Despite their high theoretical energy density, lithium–sulfur (Li–S) batteries are hindered by practical challenges including sluggish conversion kinetics and shuttle effect of polysulfides. Here, a nitrogen-doped continuous porous carbon (CPC) host anchoring monodispersed sub-10 nm FeS2 nanoclusters (CPC@FeS2) is reported as an efficient catalytic matrix for sulfur cathode. This host shows strong adsorption of polysulfides, promising the inhibition of polysulfide shuttle and the promoted initial stage of catalytic conversion process. Moreover, fast lithium ion (Li-ion) diffusion and accelerated solid–solid conversion kinetics of Li2S2 to Li2S on CPC@FeS2 host guarantee boosted electrochemical kinetics for conversion process of sulfur species in Li–S cell, which gives a high utilization of sulfur under practical conditions of high loading and low electrolyte/sulfur (E/S) ratio. Therefore, the surfur cathode (S/CPC@FeS2) delivers a high specific capacity of 1459 mAh g−1 at 0.1 C, a stable cycling over 900 cycles with ultralow fading rate of 0.043% per cycle, and an enhanced rate capability compared with cathode only using carbon host. Further demonstration of this cathode in Li–S pouch cell shows a practical energy density of 372 Wh kg−1 with a sulfur loading of 7.1 mg cm−2 and an E/S ratio of 4 µL mg−1.
|
|
| 6. |
- Zhou, Yao, et al.
(författare)
-
Enabling High-Performance Polypropylene Nanocomposites With Interfacial Deep Traps
- 2023
-
Ingår i: IEEE Transactions on Dielectrics and Electrical Insulation. - 1558-4135 .- 1070-9878. ; 30:1, s. 484-487
-
Tidskriftsartikel (refereegranskat)abstract
- Polymer nanocomposites are the material of choice for dc insulation. The emerging demand for high-capacity high voltage direct current (HVdc) power transmission requires polymer nanocomposites capable of safe and stable operation at high temperatures. However, the high-temperature electrical properties of current polymer nanocomposites are still unsatisfactory. Here, we report that the modulation of polymer/nanoparticle interfaces can greatly improve the high-temperature insulation properties of polypropylene (PP)-based nanocomposite for recyclable HVdc cable insulation application. The nanoparticles are surface-modified with PP-graft-maleic anhydride (PP- g -mah), which is not only well miscible with PP but also contains polar groups to act as interfacial deep traps. We demonstrate that the interfacial deep traps can improve the dc breakdown strength and the electrical resistivity of polymer nanocomposite by inhibiting the charge injection. This work deepens the understanding of interfacial effects in polymer nanocomposites and provides new opportunities for designing high-performance recyclable insulation materials for HVdc cables.
|
|
| 7. |
- Zhou, Yao, et al.
(författare)
-
Insight Into Space Charge Suppression by Interfacial Deep Traps in Polymer Nanocomposites
- 2022
-
Ingår i: IEEE Transactions on Dielectrics and Electrical Insulation. - 1558-4135 .- 1070-9878. ; 29:6, s. 2402-2404
-
Tidskriftsartikel (refereegranskat)abstract
- Polymer nanocomposites are attractive for HVDC insulation applications, especially for HVDC cables, due to their ability to suppress space charge accumulation through interfacial effects. However, direct evidence to support the existence of interfacial effects at the nanoscale is still lacking. Therefore, rational design and molecular engineering of the interfaces to improve the insulation properties of polymer nanocomposites remain unavailable. Here, we show that efficient space charge suppression can be achieved in polymer nanocomposites at temperatures up to 100 °C by introducing local deep traps through carefully designed nanoparticle/polymer interfaces. The local interfacial deep traps are directly detected at the nanoscale using intermodulation electrostatic force microscopy (ImEFM). This work provides a deep understanding of the interfacial effects in polymer nanocomposites and will enable the rational design of interfaces for high-performance insulation materials.
|
|
