Zerrendatu honen arabera: egilea "Martínez Laserna, Egoitz"
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Calendar Ageing Model for Li-Ion Batteries Using Transfer Learning Methods
Azkue, Markel ; Aizpuru, Iosu (MDPI, 2021)Getting accurate lifetime predictions for a particular cell chemistry remains a challenging process, largely dependent on time and cost-intensive experimental battery testing. This paper proposes a transfer learning (TL) ... -
Creating a Robust SoC Estimation Algorithm Based on LSTM Units and Trained with Synthetic Data
Azkue, Markel; Miguel, Eduardo; Oca, Laura; IRAOLA, UNAI (MDPI, 2023)Creating SoC algorithms for Li-ion batteries based on neural networks requires a large amount of training data, since it is necessary to test the batteries under different conditions so that the algorithm learns the ... -
Li-ion Battery State-of-Charge estimation algorithm with CNN-LSTM and Transfer Learning using synthetic training data
Azkue, Markel; Oca, Laura; IRAOLA, UNAI (2022)The development of State-of-Charge (SoC) algorithms for Li-ion batteries involves carrying out different laboratory tests with the money and time that this entails. Furthermore, such laboratory labours must typically be ... -
Module-Level Modelling Approach for a Cloudbased Digital Twin Platform for Li-Ion Batteries
Miguel, Eduardo; IRAOLA, UNAI (IEEE, 2022)The pursue of the new increasingly intelligent, and heavier state estimation algorithms requires a significant amount of data and computing power, which may challenge their deployment in current BMS solutions. To address ...
