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Completed PROJECT GRANT Swedish Research Council

Energy efficient and sustainable forestry

96M kr SEK

Funder Vinnova
Recipient Organization Airforestry Ab
Country Sweden
Start Date Jul 01, 2021
End Date Dec 30, 2022
Duration 547 days
Number of Grantees 1
Roles Principal Investigator
Data Source Swedish Research Council
Grant ID 2021-01792_Vinnova
Grant Description

Purpose and goal:

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 results and 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.

All Grantees

Airforestry Ab

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