Capacity-loss diagnostic and life-time prediction in lithium-ion batteries: Part 1. Development of a capacity-loss diagnostic method based on open-circuit voltage analysis

Wang, Tiansi; Pei, Lei; Wang, Tingting; Lu, Rengui; Zhu, Chunbo

doi:10.1016/j.jpowsour.2015.09.110

Cited by 36 publications

(9 citation statements)

References 21 publications

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“…Lithium-ion batteries are popular in the fields of EV and Energy Storage Systems (ESS) due to their high energy and power density, low self-discharge rate and high coulombic efficiency. However, the battery capacity fades with the process of charging and discharging due to the loss of active material (LAM) and the loss of lithium inventory (LLI) [17]. This fading capacity determines the useable life and function of a battery.…”

Section: Aging Experiments Of Lithium-ion Batteriesmentioning

confidence: 99%

“…where C bat , C bat,0 and C l , respectively, indicate the current capacity (Ah), initial capacity (Ah) and capacity loss (Ah) of the BS. A multiple stress coupling capacity loss model for lithium ion batteries is used, which takes the loss of lithium inventory and the loss of active materials into consideration [17]. The mode is expressed as follows.…”

Section: ) Fixed Costmentioning

confidence: 99%

“…A battery ages with the decrease of capacity and increase of internal resistance, which in turn limit the energy and capacity of the BESS and increase the scheduling cost. The published studies focus on studying the aging mechanism [13]- [15] and state estimation methods [16], [17]. While useful for understanding the failure mechanism and predicting the remaining useful life, such detail makes it difficult to extend the models to various use cases.…”

Section: Introductionmentioning

confidence: 99%

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Economic Operation Optimization for 2nd Use Batteries in Battery Energy Storage Systems

et al. 2019

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The lithium-ion batteries retired from electric vehicles (EVs) and hybrid EVs have been exponentially utilized in battery energy storage systems (BESSs) for 2nd use due to their economic and environmentally friendly benefits. Therefore, research on their aging mechanism and state of health (SOH) has attracted increasing amounts of attention across the world. However, few studies focus on optimizing the economic operation of BESSs that are built by retired batteries with various SOHs. This paper proposes an economic operation optimization method for BESSs comprised of retired batteries with different SOHs, which provides a way for the BESS to operate with new and retired battery systems (BSs) together. An operation cost model is put forward that considers the cost increase caused by aging. This method aims to minimize the operating cost in a time step based on the particle swarm optimization method. To validate the feasibility of the economic operation optimization method, a case was studied using a BESS consisting of four BSs with different SOHs under peak load shifting. Compared with the traditional method, which allocated power according to the available peak power of each BS, the proposed method has advantages in the scheduled number and cost.

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Section: Aging Experiments Of Lithium-ion Batteriesmentioning

confidence: 99%

Section: ) Fixed Costmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Economic Operation Optimization for 2nd Use Batteries in Battery Energy Storage Systems

et al. 2019

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“…This method is the most commonly used correction method for accurate SOC estimation. e-OCV can also be used to estimate the SOH of LIBs because the aging of LIBs is often associated with loss of lithium inventory, degradation of active material and increase of resistance, which would inevitably affect e-OCV value [20]. Therefore, accurate and rapid estimation of e-OCV is of importance for optimum operation of LIBs.However, it may take a quite long time (generally > 3 h) for LIBs to reach a complete equilibrium state after the current interruption, as shown in Figure 1, especially when they are operated at high charge/discharge rates and in low temperature with large SOC shifts [21,22].…”

mentioning

confidence: 99%

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confidence: 99%

Rapid Prediction of the Open-Circuit-Voltage of Lithium Ion Batteries Based on an Effective Voltage Relaxation Model

Yang

Wang³

et al. 2018

Energies

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The open circuit voltage of lithium ion batteries in equilibrium state, as a vital thermodynamic characteristic parameter, is extensively studied for battery state estimation and management. However, the time-consuming relaxation process, usually for several hours or more, seriously hinders the widespread application of open circuit voltage. In this paper, a novel voltage relaxation model is proposed to predict the final open circuit voltage when the lithium ion batteries are in equilibrium state with a small amount of sample data in the first few minutes, based on the concentration polarization theory. The Nernst equation is introduced to describe the evolution of relaxation voltage. The accuracy and effectiveness of the model are verified using experimental data on lithium ion batteries with different kinds of electrodes (LiCoO2/mesocarbon-microbead and LiFePO4/graphite) under different working conditions. The validation results show that the presented model can fit the experimental results very well and the predicted values are quite accurate by taking only 5 min or less. The satisfying results suggest that the introduction of concentration polarization theory might provide researchers an alternative model form to establish voltage relaxation models.

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Establishment and Testing Verification of Traction Battery Second-Order Resistor–Capacitor Digital Twin Model Based on Hybrid Pulse Power Characterization Test

Gao,

Yan,

Wang

et al. 2024

Mechanisms and Machine Science

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Capacity-loss diagnostic and life-time prediction in lithium-ion batteries: Part 1. Development of a capacity-loss diagnostic method based on open-circuit voltage analysis

Cited by 36 publications

References 21 publications

Economic Operation Optimization for 2nd Use Batteries in Battery Energy Storage Systems

Economic Operation Optimization for 2nd Use Batteries in Battery Energy Storage Systems

Rapid Prediction of the Open-Circuit-Voltage of Lithium Ion Batteries Based on an Effective Voltage Relaxation Model

Establishment and Testing Verification of Traction Battery Second-Order Resistor–Capacitor Digital Twin Model Based on Hybrid Pulse Power Characterization Test

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