The challenge and opportunity of battery lifetime prediction from field data V Sulzer, P Mohtat, A Aitio, S Lee, YT Yeh, F Steinbacher, MU Khan, ... Joule 5 (8), 1934-1955, 2021 | 184 | 2021 |
Predicting battery end of life from solar off-grid system field data using machine learning A Aitio, DA Howey Joule 5 (12), 3204-3220, 2021 | 64 | 2021 |
Bayesian parameter estimation applied to the Li-ion battery single particle model with electrolyte dynamics A Aitio, SG Marquis, P Ascencio, D Howey IFAC-PapersOnLine 53 (2), 12497-12504, 2020 | 18 | 2020 |
Combining non-parametric and parametric models for stable and computationally efficient battery health estimation A Aitio, D Howey Dynamic Systems and Control Conference 84270, V001T20A002, 2020 | 6 | 2020 |
The challenge and opportunity of battery lifetime prediction from field data. Joule 5, 1934–1955 V Sulzer, P Mohtat, A Aitio, S Lee, YT Yeh, F Steinbacher, MU Khan, ... | 5 | 2021 |
Estimation of parameter probability distributions for lithium-ion battery string models using bayesian methods LD Couto, D Zhang, A Aitio, S Moura, D Howey Dynamic systems and control conference 84270, V001T20A003, 2020 | 4 | 2020 |
Learning battery model parameter dynamics from data with recursive Gaussian process regression A Aitio, D Jöst, DU Sauer, DA Howey arXiv preprint arXiv:2304.13666, 2023 | 1 | 2023 |
Bayesian methods for battery state of health estimation A Aitio University of Oxford, 2023 | | 2023 |
Estimation of Parameter Probability Distributions for Lithium-Ion Battery String Models Using Bayesian Methods LD Couto Mendonca, D Zhang, A Aitio, S Moura, DDH Howey Dynamic Systems & Control Conference, 2021 | | 2021 |
Data repository for ‘Predicting battery end of life from solar off-grid system field data using machine learning’ A Aitio, D Howey University of Oxford, 2021 | | 2021 |