Electrical behavior of overdischarge-induced internal short circuit in lithium-ion cells

Lai, Xin; Zheng, Yuejiu; Zhou, Long; Gao, Wenkai

doi:10.1016/j.electacta.2018.05.048

Cited by 87 publications

(42 citation statements)

References 26 publications

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“…Concerns about the impact of environmental degradation and the energy crisis have encouraged humans to develop new sustainable energy resources, and energy conversion and storage devices involving lithium batteries (LIBs), lead-acid batteries, nickel-cadmium batteries, fuel cells and supercapacitors, have become research hotspots [1][2][3][4][5]. Currently, LIBs have been regarded as the first choice for electric vehicles (EVs) because of their low self-discharge rate, high energy density, long lifespan and almost zero memory effect [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

An All-Region State-of-Charge Estimator Based on Global Particle Swarm Optimization and Improved Extended Kalman Filter for Lithium-Ion Batteries

et al. 2018

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In this paper, a novel model parameter identification method and a state-of-charge (SOC) estimator for lithium-ion batteries (LIBs) are proposed to improve the global accuracy of SOC estimation in the all SOC range (0–100%). Firstly, a subregion optimization method based on particle swarm optimization is developed to find the optimal model parameters of LIBs in each subregion, and the optimal number of subregions is investigated from the perspective of accuracy and computation time. Then, to solve the problem of a low accuracy of SOC estimation caused by large model error in the low SOC range, an improved extended Kalman filter (IEKF) algorithm with variable noise covariance is proposed. Finally, the effectiveness of the proposed methods are verified by experiments on two kinds of batteries under three working cycles, and case studies show that the proposed IEKF has better accuracy and robustness than the traditional extended Kalman filter (EKF) in the all SOC range.

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Section: Introductionmentioning

confidence: 99%

An All-Region State-of-Charge Estimator Based on Global Particle Swarm Optimization and Improved Extended Kalman Filter for Lithium-Ion Batteries

et al. 2018

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“…Energy crisis and environmental problem are two major challenges facing humankind in recent years, and energy savings and emission reduction have become real priorities all over the world. New technologies and methods for saving energy and reducing emissions have become an important research focus in modern automobiles [1][2][3][4][5]. In this situation, the development and popularization of battery electric vehicles (BEVs) and hybrid electric vehicles (HEVs) have entered a high-speed period.…”

Section: Introductionmentioning

confidence: 99%

“…The most intuitive manifestation is voltage inconsistency, while the other is internal resistance inconsistency. These inconsistencies cause the actual capacity of the battery packs to be less than the theoretical capacity, which greatly reduces their service life [5,[15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…However, the consistency level among cells is already higher even after screening. Cell inconsistency in a battery pack can lead a cell or some cells to be overcharged, undercharged, or even overdischarged, causing serious security problems [5,16,18]. In order to maximize battery life and utilization, battery equalization technology is widely used to reduce the impact of battery inconsistencies.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Composite Equalizer Based on an Additional Cell for Series-Connected Lithium-Ion Cells

et al. 2018

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Cell inconsistency can lead to poor performance and safety hazards. Therefore, cell equalizer is essentially required to prevent the series-connected cells from overcharging, undercharging, and overdischarging. Among current equalization schemes, passive equalizer has a continuously wasting energy with low equalization efficiency, and active equalizer has high cost with complex circuit structure. In this study, a novel composite equalizer based on an additional cell with low complexity is presented. This method combines a passive equalizer and an active equalizer. Firstly, the configuration and circuit of our proposed composite equalizer are introduced, and the equalization principle is analyzed. On this basis, the control strategy and algorithm of the composite equalizer are further proposed. Finally, the composite equalizer is verified through simulation and experiment in various cases. The study results show that this method improves both the consistency level and the available capacity of the battery pack. Moreover, our proposed equalizer can overcome the shortcomings of commonly used equalizer and combining the advantages of different equalizer to maximize the equalization efficiency with a simpler equalizer structure.

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“…Due to increasing concerns about global warming, greenhouse gas emissions, and the depletion of fossil fuels, electric vehicles (EVs) have gained massive popularity due to their performances and efficiencies in recent decades [1][2][3]. Lithium-ion batteries (LIBs) are widely used in EVs for their high-energy density, long service life, and environmental friendliness [4][5][6]. In actual practice, LIBs need to be well monitored, diagnosed, and controlled by the battery management system (BMS).…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy State-of-Charge Estimation Algorithm Combining Ampere-Hour and an Extended Kalman Filter for Li-Ion Batteries Based on Multi-Model Global Identification

et al. 2018

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The popular and widely reported lithium-ion battery model is the equivalent circuit model (ECM). The suitable ECM structure and matched model parameters are equally important for the state-of-charge (SOC) estimation algorithm. This paper focuses on high-accuracy models and the estimation algorithm with high robustness and accuracy in practical application. Firstly, five ECMs and five parameter identification approaches are compared under the New European Driving Cycle (NEDC) working condition in the whole SOC area, and the most appropriate model structure and its parameters are determined to improve model accuracy. Based on this, a multi-model and multi-algorithm (MM-MA) method, considering the SOC distribution area, is proposed. The experimental results show that this method can effectively improve the model accuracy. Secondly, a fuzzy fusion SOC estimation algorithm, based on the extended Kalman filter (EKF) and ampere-hour counting (AH) method, is proposed. The fuzzy fusion algorithm takes advantage of the advantages of EKF, and AH avoids the weaknesses. Six case studies show that the SOC estimation result can hold the satisfactory accuracy even when large sensor and model errors exist.

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Electrical behavior of overdischarge-induced internal short circuit in lithium-ion cells

Cited by 87 publications

References 26 publications

An All-Region State-of-Charge Estimator Based on Global Particle Swarm Optimization and Improved Extended Kalman Filter for Lithium-Ion Batteries

An All-Region State-of-Charge Estimator Based on Global Particle Swarm Optimization and Improved Extended Kalman Filter for Lithium-Ion Batteries

A Novel Composite Equalizer Based on an Additional Cell for Series-Connected Lithium-Ion Cells

A Fuzzy State-of-Charge Estimation Algorithm Combining Ampere-Hour and an Extended Kalman Filter for Li-Ion Batteries Based on Multi-Model Global Identification

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