Electrification seems to be the future for heavy transports. But this places new and high demands on planning for vehicle use and charging. In collaboration with Scania and Ragn-Sells, researchers at Linköping University have launched a project with the final aim of developing calculation software for planning routes for electric trucks.
Two trucks on a road – illustrative photo. Image credit: İsmail Enes Ayhan via Unsplash, free license
In Sweden alone there are currently about 85,000 heavy goods trucks on the road, almost all of them diesel-powered. Most are owned by haulage companies tasked with delivering and collecting goods at many different locations at specific points in time while driving as economically as possible.
Maximising heavy transport vehicle fleet efficiency requires advanced route planning based on mathematical optimisation models and large-scale calculations.
But the heavy transport sector is facing a change, with electrification at its centre, making earlier route optimisation models obsolete.
Charging an electric car – illustrative photo. Image credit: Tommy Krombacher via Unplash, free license
“Planning will be more sensitive. Planning for traditional vehicles hasn’t required taking into account how far a full tank will get you. You only had to refuel quickly at the next petrol station and continue. Electric vehicle transport involves many more parameters, which makes route planning calculations more advanced,” says Elina Rönnberg, senior associate professor in the Department of Mathematics at Linköping University, LiU.
Dynamic methods
Factors that may affect the planning of a route include location of charging stations, number of vehicles charging at a given time, weather, driving style, accidents, etc.
With heavy transport haulage companies needing to plan the routes for a whole vehicle fleet, up to 40 electric trucks to be used as efficiently as possible, the scope of calculations increases further.
“If you’ve planned a route and the weather gets colder than you expected, this will affect the range, and you might not reach the next charging station. This means that the methods we are developing must also be dynamic, as external circumstances impact these vehicles more,” says Daniel Ljung, associate professor in the Division of Vehicular Systems.
Heavy transport, truck, sustainable transportation – artistic impression. Image credit: Sven Brandsma via Unsplash, free license
Scania is not only a project partner and one of the financers of the project, but also one of the world’s largest truck producers. They see a demand for electric heavy vehicles. But before production is tailored to meet demands, they need to know the opportunities for and challenges of electrified heavy transport.
“Our customers depend on reliable and efficient heavy goods trucks and electrification has the potential to lower costs. However, they are more expensive to purchase and more complex to manage. Thusly, more advanced software is needed but so far there are no algorithms that can handle the necessary complexities. That is why more research is needed,” says Viktor Leek, engineer and project manager at Scania.
Electric Heavy Transport Utilisation
The final aim of the project is to develop calculation software for planning routes for a fleet of electric heavy vehicles.
“The software should be able to provide both rough overall planning, plan individual routes in detail, and make adjustments when parameters change. It should be an aid in the electrification, a tool for doing this in a good way. We are pleased that we can combine industry needs with academia’s knowledge about vehicles and large-scale calculations. In this way, we link theory and practice to make a tangible difference for the good of society,” says Elina Rönnberg.
The name of the project is Condore (Customer Oriented Operations Research for Electrification) and it has a total budget of SEK 27 million.
Scania and the Swedish Energy Agency have contributed equal funding. At LiU, two doctoral students are active in the project: Svante Johansson, industrial doctoral student in the Division of Vehicular Systems at the Department of Electrical Engineering, and Lukas Eveborn, doctoral student in the Department of Mathematics’ group Mathematics and algorithms for intelligent decision-making.
Written by Anders Törneholm
Source: Linköping University
