Probabilistic Prediction of Energy Demand and Driving Range for Electric Vehicles with Federated Learning

Know about the book -

Probabilistic Prediction of Energy Demand and Driving Range for Electric Vehicles with Federated Learning is written by Thorgeirsson, Adam Thor and published by KIT Scientific Publishing. It's available with International Standard Book Number or ISBN identification 3731513714 (ISBN 10) and 9783731513711 (ISBN 13).

In this work, an extension of the federated averaging algorithm, FedAvg-Gaussian, is applied to train probabilistic neural networks. The performance advantage of probabilistic prediction models is demonstrated and it is shown that federated learning can improve driving range prediction. Using probabilistic predictions, routing and charge planning based on destination attainability can be applied. Furthermore, it is shown that probabilistic predictions lead to reduced travel time.