Accelerating AI-Based Battery Management System’s SOC and SOH on FPGA
Lithium battery-based electric vehicles (EVs) are gaining global popularity as an alternative to combat the adverse environmental impacts caused by the utilization of fossil fuels. State of charge (SOC) and state of health (SOH) are vital parameters that assess the battery’s remaining charge and ove...
Saved in:
Main Authors: | Satyashil D. Nagarale, B. P. Patil |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2023-01-01
|
Series: | Applied Computational Intelligence and Soft Computing |
Online Access: | http://dx.doi.org/10.1155/2023/2060808 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SOC and SOH Prediction of Lithium‐Ion Batteries Based on LSTM–AUKF Joint Algorithm
by: Yancheng Song, et al.
Published: (2025-01-01) -
AADL Extension to Model Classical FPGA and FPGA Embedded within a SoC
by: Dominique Blouin, et al.
Published: (2011-01-01) -
Investigation of the Suitability of the DTV Method for the Online SoH Estimation of NMC Lithium-Ion Cells in Battery Management Systems
by: Jan Neunzling, et al.
Published: (2025-01-01) -
LSTM-based estimation of lithium-ion battery SOH using data characteristics and spatio-temporal attention.
by: Gengchen Xu, et al.
Published: (2024-01-01) -
A Novel Procedure for Real-Time SOH Estimation of EV Battery Packs Based on Time Series Extrinsic Regression
by: Raimondo Gallo, et al.
Published: (2025-01-01)