Case Study: BluePulse achieves up to 7% fuel savings and significant CO2 reductions with Spire's historical weather data

Finding the most energy-efficient route to ship reefer containers

BluePulse, a global leader in AI-based predictive maintenance for the maritime industry, needed reliable, global weather data to feed its BlueRoute energy simulation twin so it could test thousands of alternative paths and pinpoint the most energy- and cost-efficient routes for reefer container ships. To meet that challenge, BluePulse partnered with Spire and integrated Spire’s historical weather data (solar radiation, temperature, dew point, humidity and wind) into its model.

With Spire’s data powering BlueRoute (developed with the French Space Agency and reporting ~97% accuracy), BluePulse simulated up to 1,500 alternatives for 51 Atlantic routes and ~500 alternatives for 20 Pacific routes. The results using Spire data showed up to 5% fuel savings on 63% of Atlantic routes (≈297 MWh per crossing; ~136 GWh/year; ~€20M and ~90,000 tCO2e saved) and up to 7% on 58% of Pacific routes (≈701 MWh per crossing; ~177 GWh/year; ~25M€ and ~120,000 tCO2e saved), with chosen alternatives only about 2% longer than the shortest possible routes.

BluePulse

Luc Terrel

Co-Founder