State of Health Evaluation of Lithium-Ion Batteries Using the Statistical Properties of the Voltage. [PDF]
Hammou A +4 more
europepmc +1 more source
A Battery-Free, Data-Informed UV Dose Sensor Made of Laser-Induced Graphene and Bio-Derived Electrolytes. [PDF]
Chimerad M +4 more
europepmc +1 more source
SOC Prediction of Li-Ion Battery Based on EKF and CNN-BiLSTM-Attention. [PDF]
Zhu M, Wang Y, Wang D.
europepmc +1 more source
Swarm intelligence-optimized deep neural network for intelligent diagnosis of lithium‑ion battery state of health. [PDF]
Li C, Yan B, Zhu C, Zhou X, Jia Y.
europepmc +1 more source
Deep learning-based battery health prediction for enhancing electric vehicle performance. [PDF]
Rahman T +6 more
europepmc +1 more source
Mechanistically guided residual learning for battery state monitoring throughout life. [PDF]
Che Y +6 more
europepmc +1 more source
Uncertainty aware hybrid learning framework for fast and safe charging of lithium-ion batteries using multi-fidelity observers. [PDF]
Parimala CHH +5 more
europepmc +1 more source
Adaptive deep Q-networks for accurate electric vehicle range estimation. [PDF]
Khekare U, Vedaraj I S R.
europepmc +1 more source
Flexible Sensors for Battery Health Monitoring. [PDF]
Wang X +13 more
europepmc +1 more source
Advanced battery diagnostics for electric vehicles using CAN based BMS data with EKF and data driven predictive models. [PDF]
Kulkarni SV +4 more
europepmc +1 more source

