Enabling accurate and fast large-scale battery simulation using only a 9-cell model with variance based parameters

Fantham, Thomas L.; Gladwin, Daniel T.

doi:10.1016/j.est.2022.105225

Cited by 1 publication

(1 citation statement)

References 17 publications

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“…According to [30] and [31], battery packs consisting of cells produced by the same manufacturer have extremely similar aging characteristics. In [32], the large-scale battery energy storage system simulation is realized by only using the operation data collected from 9 cells. The characteristic similarity between the battery pack and cell is validated through both theoretically and experimentally analyses.…”

Section: Quantification Model Based On Cell Experiments Datamentioning

confidence: 99%

Aging Mitigation for Battery Energy Storage System in Electric Vehicles

Zhao

et al. 2023

IEEE Trans. Smart Grid

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Battery energy storage systems (BESS) have been extensively investigated to improve the efficiency, economy, and stability of modern power systems and electric vehicles (EVs). However, it is still challenging to widely deploy BESS in commercial and industrial applications due to the concerns of battery aging. This paper proposes an integrated battery life loss modeling and anti-aging energy management (IBLEM) method for improving the total economy of BESS in EVs. The quantification of BESS aging cost is realized by a multifactorial battery life loss quantification model established by capturing aging characteristics from cell acceleration aging tests. Meanwhile, a charging event analysis method is proposed to deploy the built life loss model in vehicle BESS management. Two BESS active anti-aging vehicle energy management models: vehicle to grid (V2G) scheduling and plug-in hybrid electric vehicle (PHEV) power distribution, are further designed, where the battery life loss quantification model is used to generate the aging cost feedback signals. The performance of the developed method is validated on a V2G peak-shaving simulation system and a hybrid electric vehicle. The work in this paper presents a practical solution to quantify and mitigate battery aging costs by optimizing energy management strategies and thus can further promote transportation electrification.

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Section: Quantification Model Based On Cell Experiments Datamentioning

confidence: 99%

Aging Mitigation for Battery Energy Storage System in Electric Vehicles

Zhao

et al. 2023

IEEE Trans. Smart Grid

View full text Add to dashboard Cite

show abstract

Enabling accurate and fast large-scale battery simulation using only a 9-cell model with variance based parameters

Cited by 1 publication

References 17 publications

Aging Mitigation for Battery Energy Storage System in Electric Vehicles

Aging Mitigation for Battery Energy Storage System in Electric Vehicles

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