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

Download or read book Probabilistic Prediction of Energy Demand and Driving Range for Electric Vehicles with Federated Learning written by Thorgeirsson, Adam Thor and published by KIT Scientific Publishing. This book was released on 2024-09-03 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.