Heron

Defines on-route energy consumption according to exogenous variables.

The range and technology of electric vehicles are evolving rapidly but remain limited compared to diesel vehicles.

Vehicle autonomy must be carefully assessed to ensure it meets a route’s energy demands, considering factors such as weather conditions, terrain, and traffic congestion.

Heron is an advanced digital solution designed to precisely define on-route energy consumption of electric buses by analyzing a range of exogenous variables. Leveraging automated Python scripts deployed on AWS cloud infrastructure, Heron seamlessly integrates data acquisition, processing, and predictive modelling to optimize electric bus operations.

features

MODELLING OF YOUR RECHARGE INFRASTRUCTURE

Comprehensive Data Acquisition: Accesses live and historical data from multiple sources, including traffic conditions, climate variables, vehicle specifics, and road network information, ensuring a rich dataset for analysis.
Robust Data Cleaning and Processing: Employs sophisticated data pipelines, aggregators, and databases to clean, harmonize, and prepare data for accurate modelling.
Predictive Energy Consumption Model: Delivers high-accuracy energy consumption predictions for known vehicle and network configurations.
Custom AI Model Development: Using additional client-specific data such as ridership statistics and driver behavior, develops and trains tailored AI models to enhance prediction precision.

Benefits

Beyond energy consumption forecasting, Heron provides valuable operational benefits including eco-driving analysis and detailed on-route consumption assessments, supporting sustainable and efficient fleet management.

By integrating cutting-edge cloud computing, data science, and AI techniques, Heron empowers transit agencies and fleet operators to optimize electric bus energy use, reduce operational costs, and support environmental sustainability goals.