| Data-driven state of health modelling—A review of state of the art and reflections on applications for maritime battery systems E Vanem, CB Salucci, A Bakdi, ØÅ sheim Alnes Journal of Energy Storage 43, 103158, 2021 | 56 | 2021 |
| Multivariable fractional polynomials for lithium-ion batteries degradation models under dynamic conditions CB Salucci, A Bakdi, IK Glad, E Vanem, R De Bin Journal of Energy Storage 52, 104903, 2022 | 18 | 2022 |
| A novel semi-supervised learning approach for State of Health monitoring of maritime lithium-ion batteries CB Salucci, A Bakdi, IK Glad, E Vanem, R De Bin Journal of Power Sources 556, 232429, 2023 | 16 | 2023 |
| Simple statistical models and sequential deep learning for lithium-ion batteries degradation under dynamic conditions: Fractional polynomials vs neural networks CB Salucci, A Bakdi, IK Glad, E Vanem, R De Bin arXiv preprint arXiv:2102.08111, 2021 | 5 | 2021 |
| Data-Driven Approaches to Diagnostics and State of Health Monitoring of Maritime Battery Systems E Vanem, Q Liang, C Ferreira, C Agrell, N Karandikar, S Wang, ... PROCEEDINGS OF THE ANNUAL CONFERENCE OF THE PHM SOCIETY 2023, 2023 | 2 | 2023 |
| A novel semi-supervised learning approach for maritime lithium-ion battery monitoring C Bertinelli Salucci, A Bakdi, IK Glad, E Vanem, R De Bin EUT Edizioni Università di Trieste, 2022 | | 2022 |
