Unconventional solid-state electrolytes for lithium-based batteries: Recent advances and challenges

Mei, Han-xin; Piccardo, Paolo; Cingolani, Alessandro; Spotorno, Roberto

doi:10.1016/j.jpowsour.2022.232257

Cited by 14 publications

(9 citation statements)

References 168 publications

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“…In this model, a state variable is chosen for high-order ECM. The terminal voltage can be described based on the electrical behaviour of the battery, which is represented by (4).…”

Section: High-order Ecmmentioning

confidence: 99%

“…The six-order polynomial function for the curve fitting is shown in (17). 6 + P 2 * (SOC ) 5 + P 3 * (SOC ) 4 + P 4 * (SOC ) 3 + P 5 * (SOC ) 2 + P 6 * (SOC ) 1 + P 7 (17) After conducting numerous experiments to compare the effect of fitting performance, it was got that the sixth-order polynomial provides robust fitting results and was deemed appropriate for the processor. Consequently, the functional relation within SOC-OCV is obtained by fitting the six-order polynomial.…”

Section: Exploration Of Open Circuit Voltagementioning

confidence: 99%

“…The coefficient obtained by MATLAB using the least-squares method from P 1 to 7 (with 95% confidence bounds) is shown in (18). 6 − 61.22 * (SOC ) 5 + 68.12 * (SOC ) 4 − 32.07 * (SOC ) 3 + 5.234 * (SOC ) 2 + 0.6794 * (SOC ) 1 + 3.36 (18) Equation ( 18) establishes a mathematical relation between SOC-OCV, where f(SOC) represents the OCV. The SOC-OCV relationship acts as a foundation for the revised mathematical support of the parameters, which measures the OCV.…”

Section: Exploration Of Open Circuit Voltagementioning

confidence: 99%

“…In order to reduce global warming, EVs have been recognized as a practical and environmentally friendly substitute [1,2]. Lithium-ion batteries are considered a top choice for the EVs because of their numerous benefits, such as the huge capacity of energy storage, long life span, low maintenance cost, and easiness in transfer [3][4][5][6]. The lithium-ion battery has been hugely popular for over a century due to the critical need for a reliable source of power for portable and non-portable electronic equipment, such as smartphones and watches, smart grids, submarines, and space vehicles [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive state of charge estimation for lithium‐ion batteries using feedback‐based extended Kalman filter

Monirul

Pan

Ruby

et al. 2023

IET Control Theory & Appl

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The battery management system (BMS) is a crucial component of electric vehicles (EVs) owing to its sustainable operation. To ensure optimal performance of the BMS, state of charge (SOC) of the equipped battery is required to be effectively and accurately estimated. In this paper, the authors consider high‐order equivalent circuit model (ECM) to capture the dynamic characteristics of lithium‐ion batteries, which are connected in series with internal resistance by 2‐RC networks. The parameters of the RC network are determined by mathematically solving the working conditions of the two states. Moreover, the parameters of the battery can be derived by hybrid pulse power characterization (HPPC) tests. Then, based on the open‐circuit voltage, the proposed feedback‐based extended Kalman filtering (FEKF) algorithm is established. The parameters from the simulation have shown that the highest error is 0.0306 V, the optimal knowledge of which can improve the SOC estimation approach remarkably and can provide a reference value. Afterwards, the non‐linear predicting and corrective techniques are applied to the experiment in the extended calculation process. The original error is reduced by the FEKF algorithm, where the maximum and average errors are 0.0298 and 0.0240 V, respectively. Consequently, the established high‐order ECM utilizing the FEKF algorithm may provide SOC estimation with an error of 1.5% or less, resulting in superb performance from the lithium‐ion battery pack.

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“…In this model, a state variable is chosen for high-order ECM. The terminal voltage can be described based on the electrical behaviour of the battery, which is represented by (4).…”

Section: High-order Ecmmentioning

confidence: 99%

Section: Exploration Of Open Circuit Voltagementioning

confidence: 99%

Section: Exploration Of Open Circuit Voltagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive state of charge estimation for lithium‐ion batteries using feedback‐based extended Kalman filter

Monirul

Pan

Ruby

et al. 2023

IET Control Theory & Appl

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show abstract

“…[26][27][28] More seriously, the notorious and sharp Li dendrite ascribed from the inhomogeneous Li + deposition may penetrate through the battery separator, causing a series of safety hazards, including thermal runaway, battery short circuit, and even explosion. [29][30][31][32][33] Besides, most solvents used in commercial liquid electrolytes are volatile and flammable, which have the possibility to ignite or even detonate, especially at high temperatures. [34][35][36] To minimize these destructive effects, the design and preparation of new and safe electrolytes are necessary.…”

Section: Introductionmentioning

confidence: 99%

Click Chemistry in Lithium‐Metal Batteries

Hu,

Wang,

Zhou

et al. 2023

Small

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Lithium‐metal batteries (LMBs) are considered the “holy grail” of the next‐generation energy storage systems, and solid‐state electrolytes (SSEs) are a kind of critical component assembled in LMBs. However, as one of the most important branches of SSEs, polymer‐based electrolytes (PEs) possess several native drawbacks including insufficient ionic conductivity and so on. Click chemistry is a simple, efficient, regioselective, and stereoselective synthesis method, which can be used not only for preparing PEs with outstanding physical and chemical performances, but also for optimizing the stability of solid electrolyte interphase (SEI) layer and elevate the cycling properties of LMBs effectively. Here it is primarily focused on evaluating the merits of click chemistry, summarizing its existing challenges and outlining its increasing role for the designing and fabrication of advanced PEs. The fundamental requirements for reconstructing artificial SEI layer through click chemistry are also summarized, with the aim to offer a thorough comprehension and provide a strategic guidance for exploring the potentials of click chemistry in the field of LMBs.

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Glory of Fire Retardants in Li‐Ion Batteries: Could They Be Intrinsically Safer?

Mishra,

Anne,

Das

et al. 2024

Advanced Sustainable Systems

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Lithium‐ion batteries (LIBs) have dramatically transformed modern energy storage, powering a wide range of devices from portable electronics to electric vehicles, yet the use of flammable liquid electrolytes raises thermal safety concerns. Researchers have investigated several ways to enhance LIB's fire resistance. Fire retarding molecules functions through cooling effects, scavenging radicals, and forming protective barriers. Incorporating fire‐suppressing molecules within the LIBs aims to delay or mitigate thermal runaway scenarios, reducing the risks of fires or explosions. Achieving an optimal balance between safety and performance is a major obstacle in the design of intrinsically safer LIBs. Therefore, it is important to consider their effects on LIB's performance, long‐term stability, and environmental impact. To overcome these challenges, collaborative research efforts among academia, industry, and regulatory sectors are necessary. This article reviews state‐of‐the‐art literature associated with LIBs safety or even fire mitigation by introducing solid‐state or quasi‐solid‐state electrolytes as well as modified liquid electrolytes. Moreover, the effectiveness of various strategies in making LIBs intrinsically safer is critically evaluated with an emphasis on fire retardants followed by shedding some light on the remaining challenges.

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Unconventional solid-state electrolytes for lithium-based batteries: Recent advances and challenges

Cited by 14 publications

References 168 publications

Adaptive state of charge estimation for lithium‐ion batteries using feedback‐based extended Kalman filter

Adaptive state of charge estimation for lithium‐ion batteries using feedback‐based extended Kalman filter

Click Chemistry in Lithium‐Metal Batteries

Glory of Fire Retardants in Li‐Ion Batteries: Could They Be Intrinsically Safer?

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