Overview of Methods for Battery Lifetime Extension

Jin, Siyu; Huang, Xinrong; Sui, Xin; Wang, Shunli; Teodorescu, Remus; Stroe, Daniel‐Ioan

doi:10.23919/epe21ecceeurope50061.2021.9570685

Cited by 4 publications

(4 citation statements)

References 35 publications

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“…where n stands for the nth charge cycle, C n is the estimated cycle capacity at cycle n (it is an indicator of the SOH of the battery), SOC n known,0 is the SOC value at the first point of measure in cycle n, t ini,known and t end,known establish the time interval where the measured values of the voltage-SOC curve are taken during the CC stage, t ini,forecast and t end,forecast define the time forecast interval of the voltage-SOC curve, and Q re f charge_cycle,CV is the total input charge during the CV stage of the reference cycle. Note that as shown in Figure 4, this study arbitrarily chose 3.8 V as the starting point t ini,known , while t end,known corresponds to the time at which the SOC increased by 0.2 from t ini,known , and thus, SOC(t end,known ) = SOC(t ini,known ) + 0.2 (9) Note that during the CC phase, there is a proportional relationship between the time and the SOC.…”

Section: Phase 13 Capacity Estimationmentioning

confidence: 99%

“…As a result, extending the battery life is a complex and challenging research topic that has a significant potential impact on the reliability and performance of battery-powered systems. Battery life extension strategies are receiving increased attention [9], as extended battery life can reduce operating costs and environmental impact while enabling more sustainable operation of battery systems [10,11].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Real-Time Lithium Battery Aging Prediction Based on Capacity Estimation and Deep Learning Methods

de la Vega,

Riba,

Ortega-Redondo

2023

Batteries

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Lithium-ion batteries are key elements in the development of electrical energy storage solutions. However, due to cycling, environmental, and operating conditions, battery capacity tends to degrade over time. Capacity fade is a common indicator of battery state of health (SOH) because it is an indication of how the capacity has been degraded. However, battery capacity cannot be measured directly, and thus, there is an urgent need to develop methods for estimating battery capacity in real time. By analyzing the historical data of a battery in detail, it is possible to predict the future state of a battery and forecast its remaining useful life. This study developed a real-time, simple, and fast method to estimate the cycle capacity of a battery during the charge cycle using only data from a short period of each charge cycle. This proposal is attractive because it does not require data from the entire charge period since batteries are rarely charged from zero to full. The proposed method allows for simultaneous and accurate real-time prediction of the health and remaining useful life of the battery over its lifetime. The accuracy of the proposed method was tested using experimental data from several lithium-ion batteries with different cathode chemistries under various test conditions.

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Section: Phase 13 Capacity Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Real-Time Lithium Battery Aging Prediction Based on Capacity Estimation and Deep Learning Methods

de la Vega,

Riba,

Ortega-Redondo

2023

Batteries

View full text Add to dashboard Cite

show abstract

“…The most preferable action to take is to extend the lifespan of the application for which the battery was produced as much as possible. Thermal management [8,9] and optimal charging strategies [10,11] are some solutions that can help to prolong battery lifetime [12]. When the battery is no longer suitable for its first application, the possibility of giving the battery a second life should be systematically considered.…”

Section: Introductionmentioning

confidence: 99%

Battery Passports for Second-Life Batteries: An Experimental Assessment of Suitability for Mobile Applications

Hassini,

Redondo-Iglesias,

Venet

2024

Batteries

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End-of-life electric vehicle (EV) batteries can be reused to reduce their environmental impact and economic costs. However, the growth of the second-life market is limited by the lack of information on the characteristics and performance of these batteries. As the volume of end-of-life EVs may exceed the amount of batteries needed for stationary applications, investigating the possibility of repurposing them in mobile applications is also necessary. This article presents an experimental test that can be used to collect the data necessary to fill a battery passport. The proposed procedure can facilitate the decision-making process regarding the suitability of a battery for reuse at the end of its first life. Once the battery passport has been completed, the performance and characteristics of the battery are compared with the requirements of several mobile applications. Mobile charging stations and forklift trucks were identified as relevant applications for the reuse of high-capacity prismatic cells. Finally, a definition of the state of health (SoH) is proposed to track the suitability of the battery during use in the second-life application considering not only the energy but also the power and efficiency of the battery. This SoH shows that even taking into account accelerated ageing data, a repurposed battery can have an extended life of 11 years at 25 °C. It has also been shown that energy fade is the most limiting performance factor for the lifetime and that cell-to-cell variation should be tracked as it has been shown to have a significant impact on the battery life.

show abstract

“…The most preferable action to take is to extend as much as possible the lifespan of the application for which the battery was produced. Thermal management [8,9] and optimal charging strategies [10,11] are some solutions that can help to prolong battery lifetime [12]. When the battery is no longer suitable for its first application, the possibility of giving the battery a second life should be systematically considered.…”

Section: Introductionmentioning

confidence: 99%

Battery Passport for Second-Life Batteries: Experimental Assessment of Suitability for Mobile Applications

Hassini,

Redondo-Iglesias,

Venet

2024

Preprint

View full text Add to dashboard Cite

End-of-life electric vehicle (EV) batteries can be reused to reduce their environmental impact and economic costs. However, the growth of a second-life market is limited by the lack of information on the characteristics and performance of these batteries. As the volume of end-of-life EVs may exceed the amount of batteries needed for stationary applications, investigating the possibility of repurposing them in mobile applications is also necessary. This article presents an experimental test that can be used to collect the data necessary to fill a battery passport. The proposed procedure can facilitate the decision making process regarding the suitability of a battery for reuse at the end of its first life. Once the battery passport has been completed, the performance and characteristics of the battery are compared with the requirements of several mobile applications. Mobile charging stations and forklift trucks were identified as relevant applications for the reuse of high capacity prismatic cells. Finally, a definition of a state of health (SoH) is proposed to track the suitability of the battery during use in the second life application considering not only energy but also power and efficiency of the battery. This SoH shows that even taking into account accelerated ageing data, a repurposed battery can have an extended life of 11 years at 25~°C. It has also been shown that energy fade is the most limiting performance for lifetime and that cell-to-cell variation should be tracked as it has been shown to have a significant impact on battery life.

show abstract

Overview of Methods for Battery Lifetime Extension

Cited by 4 publications

References 35 publications

Real-Time Lithium Battery Aging Prediction Based on Capacity Estimation and Deep Learning Methods

Real-Time Lithium Battery Aging Prediction Based on Capacity Estimation and Deep Learning Methods

Battery Passports for Second-Life Batteries: An Experimental Assessment of Suitability for Mobile Applications

Battery Passport for Second-Life Batteries: Experimental Assessment of Suitability for Mobile Applications

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