An approach towards AGV battery cell voltage prediction using DL and data pre-processing
Modern methods for solving the AGV battery cell voltage prediction problem include a
symbiosis of probabilistic and machine learning methods. In this study, we propose to use …
symbiosis of probabilistic and machine learning methods. In this study, we propose to use …
Predicting AGV Battery Cell Voltage Using a Neural Network Approach with Preliminary Data Analysis and Processing
O Pavliuk, M Medykovskyy… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Modern methods for solving the AGV battery cell voltage prediction problem include a
symbiosis of probabilistic and machine learning methods. In this study, we propose to use …
symbiosis of probabilistic and machine learning methods. In this study, we propose to use …
Online data-driven battery voltage prediction
We consider in this article battery state of power (SoP) estimation, in particular, we propose
two algorithms for predicting voltage corresponding to a future current profile that is known to …
two algorithms for predicting voltage corresponding to a future current profile that is known to …
An auto-regressive model for battery voltage prediction
Accurate modelling of the dynamic behaviour of Lithium-ion (Li-ion) batteries is important in
a wide range of scenarios from the determination of appropriate battery-pack size, to battery …
a wide range of scenarios from the determination of appropriate battery-pack size, to battery …
Hybrid neural networks architectures for SOC and voltage prediction of new generation batteries storage
This paper presents some experiences and results obtained about the problem of the SOC
and voltage prediction and simulation of new generation batteries. A complex pipelined …
and voltage prediction and simulation of new generation batteries. A complex pipelined …
Battery voltage prediction technology using machine learning model with high extrapolation accuracy
T Kawahara, K Sato, Y Sato - International Journal of Energy …, 2023 - Wiley Online Library
Battery performance prediction techniques based on machine learning (ML) models and
lithium‐ion battery (LIB) data collected in the real world have received much attention …
lithium‐ion battery (LIB) data collected in the real world have received much attention …
Accurate circuit model for predicting the performance of lead-acid AGM batteries
W Peng - 2011 - digitalscholarship.unlv.edu
Energy storage technologies are becoming of great importance in many modern electrical
systems. In particular, electrochemical batteries are rapidly gaining wide-spread application …
systems. In particular, electrochemical batteries are rapidly gaining wide-spread application …
Microcontroller compatible sealed lead acid battery remaining energy prediction using adaptive neural fuzzy inference system
All over the world, many portable devices need battery to run. Every expert has to use
efficient hardware and software documentation to make battery last longer and make a …
efficient hardware and software documentation to make battery last longer and make a …
[PDF][PDF] A Novel Methodology Based on a Deep Neural Network and Data Mining for Predicting the Segmental Voltage Drop in Automated Guided Vehicle Battery Cells …
AGVs are important elements of the Industry 4.0 automation process. The optimization of
logistics transport in production environments depends on the economical use of battery …
logistics transport in production environments depends on the economical use of battery …
Power battery charging state-of-charge prediction based on genetic neural network
Y Zhou, J Sun, X Wang - 2010 2nd International Conference on …, 2010 - ieeexplore.ieee.org
The problem of power battery state of charge estimation for hybrid vehicle directly affects the
vehicle performance and driving distance. Considering there exists nonlinear relationship …
vehicle performance and driving distance. Considering there exists nonlinear relationship …