Energy efficient and sustainable forestry
| Reference number | |
| Coordinator | AirForestry AB |
| Funding from Vinnova | SEK 9 600 000 |
| Project duration | July 2021 - December 2022 |
| Status | Completed |
| Venture | Fossilfria Arbetsmaskiner - FFI |
| Call | Fossil-free mobile work machines - spring 2021 |
| End-of-project report | 2021-01792sv.pdf(pdf, 659 kB) (In Swedish) |
Important results from the project
The project´s objective was to evaluate drones for forest thinning. Sweden consumes 60 million liters of diesel and emits 170,000 tonnes of fossil carbon dioxide per year in the thinning of forests. The heavy machinery also creates soil and tree damage. To get there, so-called strip roads need to be cut in the forest, which take up 20% of the productive forest land, which means large growth losses. The project has verified that it is possible to do thinning with drones in a much more gentle way, which could increase carbon sequestration in Swedish forests by up to 2 million tons of CO2 per year.
Expected long term effects
The project has succeeded in verifying the goals of the subsystems. By evaluating a drone platform with the capacity to handle trees and testing a lightweight harvester assembly and associated battery logistics. The project´s brand new technology supports the transition to renewable energy through electrification in forestry. The new technology also has the potential to reduce energy consumption by up to 50% compared to traditional machine systems. The project will be further developed in a continuation project.
Approach and implementation
The plan was to develop the subsystems drone, harvestertool, operator station and battery logistics. The drone was built in different scales and tested step by step with a parallel application process for outdoor flight permits in order to then be able to verify the drone´s capabilities in an operational environment. The functions of the harvester tool were tested and verified from a crane and prepared for integration with the drone. The battery logistics were evaluated and optimization algorithms were developed for battery use for the electrification of forest operation.