Experimental Assessment of First- and Second-Life Electric Vehicle Batteries: Performance, Capacity Dispersion, and Aging

Braco, Elisa; Martín, Idoia San; Berrueta, Alberto; Sanchis, Pablo

doi:10.1109/tia.2021.3075180

Cited by 36 publications

(17 citation statements)

References 41 publications

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“…To show the effectiveness of our proposed scheme, we consider a cyber attack: (1) on the CEV buying and selling price data and (2) on the CEV seller power data using for The battery depletion threshold (BDT) [23] both our proposed method to compare simulations with and without FDIA.…”

Section: Simulation Resultsmentioning

confidence: 99%

Cyber-Attack on P2P Energy Transaction Between Connected Electric Vehicles: A False Data Injection Detection Based Machine Learning Model

2022

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When cybersecurity is neglected, any network system loses its efficiency, reliability, and resilience. With the huge integration of the Information, Communication and Technology capabilities, the Connected Electric Vehicle (CEV) as a transportation form in cities is becoming more and more efficient and able to reply to citizen and environmental expectations which improve the quality of citizens' life. However, this CEV technological improvement increases the CEV vulnerabilities to cyber-attacks resulting to serious risks for citizens. Thus, they can intensify their negative impact on societies and cause unexpected physical damage and economic losses. This paper targets the cybersecurity issues for CEVs in parking lots where a peer-to-peer(P2P) energy transaction system based on blockchain, and smart contract scheme is launched. A False Data Injection Attack (FDIA) on the electricity price and power signal is proposed and a Machine Learning/SVM classification protocol is used to detect and extract the right values. Simulation results are conducted to prove the effectiveness of this proposed model.

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Section: Simulation Resultsmentioning

confidence: 99%

Cyber-Attack on P2P Energy Transaction Between Connected Electric Vehicles: A False Data Injection Detection Based Machine Learning Model

2022

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“…Furthermore, this can result in an internal short-circuit due to the dendrites built by the metallic lithium. The poorer performance of LIBs under low temperatures has been duly reported in the literature, measuring capacity reductions of 30% at 5ºC [7]. Considering the battery internal resistance, previous studies report increases of up to 15-fold at -20 ºC [8].…”

Section: Introductionmentioning

confidence: 91%

Noninvasive Aging Analysis of Lithium-Ion Batteries in Extreme Cold Temperatures

Soto

Berrueta

Oficialdegui

et al. 2022

IEEE Trans. on Ind. Applicat.

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This paper presents a non-invasive technical analysis of the degradation of four lithium-ion batteries (LIBs) used in extreme frigid weather. In contrast to other studies in which the batteries were tested in laboratory conditions, the LIBs studied in this paper were aged in a real application, more specifically in the WindSled project. In this project, an expedition was made using a zero-emission vehicle drawn by kites, covering more than 2500 kilometers on the East Antarctic Plateau. The study performed in this paper aims to quantify the degradation of the LIBs during the expedition. The results show a 5 % capacity fade, a 30 % increase in the internal resistance and no substantial increase in the impedance of the solid electrolyte interface (SEI). Moreover, no evidence of dendrite growth at the anode is inferred by the interpretation of the distribution of relaxation times (DRT), incremental capacity analysis (ICA) and differential voltage analysis (DV). Based on these results, it can be claimed that the LIBs used in the WindSled Project can successfully operate under -50 ºC. Furthermore, since non-invasive techniques were used to characterize the batteries, they can still be used in upcoming expeditions, with subsequent financial and environmental benefits.

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“…The degradation primarily affects the Perspective Chapter: Thermal Runaway in Lithium-Ion Batteries DOI: http://dx.doi.org/10.5772/intechopen.106539 anode and, specifically, the SEI layer. The analysis of SOH as an influencing factor in TR is currently taking on particular importance given the growing interest in second life applications for lithium-ion batteries [55][56][57]. In this second life, due to the fact that the SOH is below the design value, this could give rise to phenomena for which the cell has not been designed.…”

Section: State Of Health (Soh)mentioning

confidence: 99%

Perspective Chapter: Thermal Runaway in Lithium-Ion Batteries

Lalinde¹,

Berrueta²,

Valera³

et al. 2024

Lithium Batteries - Recent Advances and Emerging Topics

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Lithium-ion batteries (LIBs) are becoming well established as a key component in the integration of renewable energies and in the development of electric vehicles. Nevertheless, they have a narrow safe operating area with regard to the voltage and temperature conditions at which these batteries can work. Outside this area, a series of chemical reactions take place that can lead to component degradation, reduced performance and even self-destruction. The phenomenon consisting of the sudden failure of an LIB, causing an abrupt temperature increase, is known as thermal runaway (TR) and is considered to be the most dangerous event that can occur in LIBs. Therefore, the safety of LIBs is one of the obstacles that this technology must overcome in order to continue to develop and become well established for uses in all types of applications. This chapter presents a detailed study of the general issues surrounding this phenomenon. The origin of the problem is identified, the causes are detailed as well as the phases prior to TR. An analysis is made of the most relevant factors influencing this phenomenon, and details are provided of detection, prevention and mitigation measures that could either prevent the TR or reduce the consequences.

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Experimental Assessment of First- and Second-Life Electric Vehicle Batteries: Performance, Capacity Dispersion, and Aging

Cited by 36 publications

References 41 publications

Cyber-Attack on P2P Energy Transaction Between Connected Electric Vehicles: A False Data Injection Detection Based Machine Learning Model

Cyber-Attack on P2P Energy Transaction Between Connected Electric Vehicles: A False Data Injection Detection Based Machine Learning Model

Noninvasive Aging Analysis of Lithium-Ion Batteries in Extreme Cold Temperatures

Perspective Chapter: Thermal Runaway in Lithium-Ion Batteries

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