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Academic Journal of Mathematical Sciences, 2023, 4(1); doi: 10.25236/AJMS.2023.040110.

Mathematical Model and Prediction Analysis of Automobile Power Battery Decommissioning Based on Weibull Distribution

Author(s)

Song Hu, Xiaotong Jiang, Fengyun Zhao, Jingyi Wang, Rui Wang, Meng Wu

Corresponding Author:
Song Hu
Affiliation(s)

China Automotive Technology and Research Center Co., Ltd., Tianjin, China

Abstract

With the significant increase of lithium battery consumption in China, resource safety is widely concerned by the industry. However, the industry lacks relevant models for the specific temporal and spatial prediction analysis of retired batteries, and how to determine the future amount of retired new energy vehicles has become a hotspot in the industry. In this paper, based on the data of the national new energy vehicle sales terminals, the Weibull distribution is used to construct the retirement volume model, and the model parameters are calculated by vehicle type to realize the spatial and temporal prediction analysis of the retirement of the retired power battery. The model has good interpretation, and has strong correlation in 51% of the model data and correlation in 90% of the model data, which can provide a theoretical basis for the industry layout and research.

Keywords

Weibull Distribuion, New Energy Vehicle, Retired Batteries

Cite This Paper

Song Hu, Xiaotong Jiang, Fengyun Zhao, Jingyi Wang, Rui Wang, Meng Wu. Mathematical Model and Prediction Analysis of Automobile Power Battery Decommissioning Based on Weibull Distribution. Academic Journal of Mathematical Sciences (2023) Vol. 4, Issue 1: 61-66. https://doi.org/10.25236/AJMS.2023.040110.

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