Einride presents the results of a pioneering study carried out together with Germany’s Fraunhofer ISI, showing how AI-based planning can make electrified freight transport both scalable and cost-effective. The study is based on real logistics data from REWE and covers more than 38,000 transport runs and more than 200 vehicles serving 500 locations around Berlin.
At the heart of the results is Einride’s Planning AI, an advanced algorithm in the company’s platform that integrates vehicle data, energy requirements and real-world transport patterns. Instead of replacing diesel trucks one for one, the technology optimises routes and charging at fleet level, which raises utilisation and cuts costs.
Key results:
• Deeper electrification: With Planning AI, electric vehicles were able to carry 85% of the total load and 54% of the distance driven, compared with 57% and 32% respectively for a simple 1:1 diesel replacement.
• Lower total cost of ownership (TCO): Fleet-level replanning reduced TCO by 8–13% compared with an all-diesel fleet, while 1:1 replacement gave savings of approx. 3%.
• More efficient charging investments: 150 kW fast chargers cut costs in both cases, but AI-optimised fleets were less dependent on expensive infrastructure.
• Resilience to market changes: Even without investment subsidies, AI-planned fleets maintained a high degree of electrification and cost parity with diesel.
“We are showing with data how AI can transform freight transport and lay the foundation for the sustainable logistics of the future,” says Einride CEO Roozbeh Charli.
Professor Patrick Plötz of Fraunhofer ISI emphasises that planning software integrating route and charging planning has a greater effect than increasing battery size or building chargers without coordination.
The study was carried out within the Swedish innovation project REEL, funded by FFI – Strategic Vehicle Research and Innovation. The full report is available on Fraunhofer Publica.
