Predictive Model for Energy Consumption Including Weather Effects

Problem Statement

Current energy consumption benchmarks for train driving do not sufficiently reflect weather conditions, delays, or operational context. This results in misleading comparisons, low acceptance by drivers, and limited usefulness for energy efficiency programs.

Proposed Solution

Develop a predictive energy consumption model that integrates weather data, punctuality, and operational parameters. The model explains deviations transparently and enables fair, context‑aware benchmarking of driving behavior.

Required Expert Profiles

• Data scientists and machine‑learning engineers
• Software Developers

Challenge Owners

Jochen Völker, Benjamin Weber (DB)