Evaluation of battery inconsistency based on information entropy

Duan, Bin; Li, Zeyuan; Gu, Pingwei; Zhou, Zhongkai; Zhang, Chenghui

doi:10.1016/j.est.2018.01.010

Cited by 92 publications

(27 citation statements)

References 2 publications

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“…Therefore, the battery parameters such as internal resistance and self‐discharge rate of the same batch of batteries have a large degree of dispersion, and the performance of each single cell is inconsistent 51,52 . After the LIBs are connected in series and in parallel, the inconsistencies between the individual cells are mainly reflected in the battery terminal voltage and capacity during actual use.…”

Section: Research Aspectsmentioning

confidence: 99%

Intelligent optimization methodology of battery pack for electric vehicles: A multidisciplinary perspective

Garg

Xiao

et al. 2020

Int J Energy Res

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Past studies focused on proposing new materials for batteries components, state of health (SOH) prediction, thermal design, equivalent circuit modeling, and so on. Those studies have been implemented on individual basis on a single battery or battery pack. However, there is hardly any research found that encompasses all the multidisciplinary aspects (such as materials, SOH, intelligent configuration [assembly], thermal design, mechanical safety, and recycling of materials and pack) simultaneously for the battery pack design of electric vehicles. This research article proposes a synthetic methodology for an advanced design of battery pack and its components by incorporating optimal scenario of materials selection for battery electrodes, SOH estimation, configurations (assembly) of cells, thermal (air and liquid cooling) design, battery pack casing mechanical safety, and recycling aspects of battery and battery pack. The problem is divided into the several parts and methodology for each is proposed. Cumulative advantages of the methodology with six future critical directions are discussed in the end.

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Section: Research Aspectsmentioning

confidence: 99%

Intelligent optimization methodology of battery pack for electric vehicles: A multidisciplinary perspective

Garg

Xiao

et al. 2020

Int J Energy Res

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“…In recent years, the feature fusion-based methods have drawn increasing attention. Duan et al [14] used information entropy to analyze the inconsistency of a battery pack with twelve cells connected in series. The capacity, internal resistance, and coulomb efficiency were selected as features.…”

Section: Introductionmentioning

confidence: 99%

Joint Estimation of Inconsistency and State of Health for Series Battery Packs

et al. 2021

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Battery packs are applied in various areas (e.g., electric vehicles, energy storage, space, mining, etc.), which requires the state of health (SOH) to be accurately estimated. Inconsistency, also known as cell variation, is considered a significant evaluation index that greatly affects the degradation of battery pack. This paper proposes a novel joint inconsistency and SOH estimation method under cycling, which fills the gap of joint estimation based on the fast-charging process for electric vehicles. First, fifteen features are extracted from current change points during the partial charging process. Then, a joint estimation system is designed, where fusion weights are obtained by the analytic hierarchy process and multi-scale sample entropy to evaluate inconsistency. A wrapper is used to select the optimal feature subset, and Gaussian process regression is implemented to estimate the SOH. Finally, the estimation performance is assessed by the test data. The results show that the inconsistency evaluation can reflect the aging conditions, and the inconsistency does affect the aging process. The wrapper selection method improves the accuracy of SOH estimation by about 75.8% compared to the traditional filter method when only 10% of data is used for model training. The maximum absolute error and root mean square error are 2.58% and 0.93%, respectively.

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“…The imbalance can deteriorate with the battery degradation and may further lead to the risk of thermal runaway. [13][14][15] Therefore, battery equalization, which can enhance the pack safety and performance, is a critical technology for reduction of the cell imbalance. 16 Equalization is also critical for the second use of retired LIBs.…”

Section: Introductionmentioning

confidence: 99%

“…At the pack level, variations in cell parameters can lead to subsequent acceleration of the degradation, 12 with negative impact on the available power, capacity, lifespan, etc. The imbalance can deteriorate with the battery degradation and may further lead to the risk of thermal runaway 13‐15 . Therefore, battery equalization, which can enhance the pack safety and performance, is a critical technology for reduction of the cell imbalance 16 …”

Section: Introductionmentioning

confidence: 99%

A comprehensive review on inconsistency and equalization technology of lithium‐ion battery for electric vehicles

et al. 2020

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The rapid growth of transportation demand has been enlarged strongly which has promoted electric vehicles powered by lithium-ion batteries. However, the inconsistencies within the battery pack will deteriorate over the lifecycle and affect the performance of electric vehicles. Therefore, various thermal management systems and equalization systems have been applied in battery management system to deal with the inconsistencies, extend battery service life, and improve safety performance. This review summarizes the origination of inconsistency within lithium-ion batteries from production to usage process, and then introduces the classification methods and application scenarios of the balance management system in detail. Based on the circuit topology, equalization systems can be classified into passive and active topologies. Active topologies

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Evaluation of battery inconsistency based on information entropy

Cited by 92 publications

References 2 publications

Intelligent optimization methodology of battery pack for electric vehicles: A multidisciplinary perspective

Intelligent optimization methodology of battery pack for electric vehicles: A multidisciplinary perspective

Joint Estimation of Inconsistency and State of Health for Series Battery Packs

A comprehensive review on inconsistency and equalization technology of lithium‐ion battery for electric vehicles

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