Prediction and Analysis of Electric Truck Performance through Data Visualisation and Machine Learning
Development of a data visualisation platform to predict battery state of charge for electric haul trucks via machine learning.
Published: 17 August 2026
Through MRIWA project M10644, Electric Power Conversions Australia (EPCA) have developed a cloud-based machine learning and visualisation system to predict battery state of charge for electric heavy haul trucks. The system automates data ingestion, trains predictive models using AWS, and generates real-time dashboards and reporting to improve fleet performance, scheduling, and energy efficiency.
Read MRIWA report 10644 summarising the findings of this research
Page was last reviewed 17 August 2026