How, D. N. T.

Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends

Hossain Lipu, M. S., Hannan, M. A., Hussain, A., Ayob, A., Saad, M. H. M., Karim, T. F., & How, D. N. T. (2020) · Journal of Cleaner Production

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 378

SOC Estimation of Li-ion Batteries With Learning Rate-Optimized Deep Fully Convolutional Network

Hannan, M. A., How, D. N. T., Lipu, M. S. H., Ker, P. J., Dong, Z. Y., Mansur, M., & Blaabjerg, F. (2021) · IEEE Transactions on Power Electronics

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 233

Deep learning approach towards accurate state of charge estimation for lithium-ion batteries using self-supervised transformer model

Hannan, M. A., How, D. N. T., Lipu, M. S. H., Mansor, M., Ker, P. J., Dong, Z. Y., Sahari, K. S. M., Tiong, S. K., Muttaqi, K. M., Mahlia, T. M. I., et al. (2021) · Scientific Reports

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 196

State-of-Charge Estimation of Li-ion Battery Using Gated Recurrent Unit With One-Cycle Learning Rate Policy

Hannan, M. A., How, D. N. T., Mansor, M. B., Hossain Lipu, M. S., Ker, P., & Muttaqi, K. (2021) · IEEE Transactions on Industry Applications

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 70