Advanced Online State-of-Health Prediction and Monitoring of Na-Ion Battery for Electric Vehicles Application

Na-ion batteries are growing interest due to their sustainability and low cost. A wide implementation in stationary applications, but also for short range transportation, is envisaged. This is further supported by the recent progress on Na-ion cells with increased energy density. To this regards the development of procedures for real-time assessment of batteries state of health is of crucial relevance. The present paper provides an innovative procedure to assess sodium-ion battery capacity fading based on the application of Discrete Wavelet Transform to voltage signals, acquired once a certain load pattern is applied at the battery terminals. The procedure development is provided through Na-ion cell aging test. During all the test battery capacity measurements are carried out. RMSE between assessed and measured values equals 1.18%. Moreover, during the aging test significant differences between performance evolution of Na-ion and NCR Li-ion cells are highlighted and discussed.

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Publication Details

Journal
IEEE Open Journal of Industry Applications
Published
2025-01-01
DOI
https://doi.org/10.1109/ojia.2025.3527721
Citations
3
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
2.05
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article

Advanced Online State-of-Health Prediction and Monitoring of Na-Ion Battery for Electric Vehicles Application

A. Ottaviano, Dario Pelosi, Lorenzo Trombetti, Linda Barelli et al.
3 citations
IEEE Open Journal of Industry Applications
Advanced Battery Technologies Research
2.05
article

Advanced Online State-of-Health Prediction and Monitoring of Na-Ion Battery for Electric Vehicles Application

A. Ottaviano, Dario Pelosi, Lorenzo Trombetti, Linda Barelli, Federico Gallorini
article en
3 citations

Abstract

Na-ion batteries are growing interest due to their sustainability and low cost. A wide implementation in stationary applications, but also for short range transportation, is envisaged. This is further supported by the recent progress on Na-ion cells with increased energy density. To this regards the development of procedures for real-time assessment of batteries state of health is of crucial relevance. The present paper provides an innovative procedure to assess sodium-ion battery capacity fading based on the application of Discrete Wavelet Transform to voltage signals, acquired once a certain load pattern is applied at the battery terminals. The procedure development is provided through Na-ion cell aging test. During all the test battery capacity measurements are carried out. RMSE between assessed and measured values equals 1.18%. Moreover, during the aging test significant differences between performance evolution of Na-ion and NCR Li-ion cells are highlighted and discussed.

IEEE Open Journal of Industry ApplicationsVol. 6
University of Perugia (IT)
Affordable and clean energy
Openalex Percentile: Top 16%
Advanced Battery Technologies Research
2.05
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Advanced Online State-of-Health Prediction and Monitoring of Na-Ion Battery for Electric Vehicles Application — A. Ottaviano, Dario Pelosi, et al. · IEEE Open Journal of Industry Applications (2025) | TGRS Research Map | TGRS