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 …

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 …

We reviewed the existing and currently used approach in processing the residual charge of
an AGV battery. The method of setting up the experiment for collecting the historical data for …

To reduce the current crisis on energy and environmental problems, the adoption of electric
vehicles is an effective way. But limited access and availability of charging infrastructure are …

The growing demand for efficient energy storage solutions has sparked increased interest in
precise battery voltage prediction. In this study the Long Short-Term Memory networks, are …

Precise prediction of power battery SOC plays a key role in the accurate navigation of
electric vehicles that are running on the way. Since traditional models adopt methods of …

The research on traditional lithium battery charging systems has problems such as model
simplification, insufficient data, insufficient accuracy, and poor real-time performance …

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 …

In this paper, we analyze a public dataset of electricity consumption collected over 3,800
households for one year and half. We show that some socio-economic factors are critical …

The selection of input variables is important to improve the prediction accuracy of artificial
neural networks (ANNs). A three-layer feedforward backpropagation ANN is presented to …