PUBLICATIONS
Paper
[Domestic Journals] Hyun-Yong Park, Hee-Sung Lim, and Kyo-Beum Lee, "SOH Estimation of Batteries using Lithium-Ion Internal Parameters with Convolution Neural Network and Gated Recurrent," The Transactions of the Korean Institute of Electrical Engineers, vol. 72, no. 3, pp. 387-394, Mar. 2023.
- 글쓴이 관리자
- 날짜 2023-06-28 21:08
- 조회 749
This paper proposes an estimation method for Lithium-Ion Batteries SOH by learning the batteries’ internal parameters using the Convolution Neural
Network and the Gated Recurrent Unit. Various equivalent circuit models exist to represent the batteries’ internal parameters. Among these
equivalent circuit models, the most representative model is the Randles model, and the data measured based on the Randles model is used as
learning input data. The internal parameters of batteries change non-linearly depending on the operation condition and use time. So, nonlinear
features are extracted using the CNN input as the batteries' parameters. The extracted features are used as an input of the GRU to learn the
characteristics of change over time, and SOH is predicted through this. The learning dataset utilizes 17IND10 LibForSecUse of EMPIR, which
validates the performance of the proposed model.
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