The ongoing electrification of heavy-duty vehicles creates new challenges for the transport sector in the form of large investment costs in vehicles and charging infrastructure, varying range depending on external
circumstances, and the vehicles' charging systems. Current methods for planning transport assignments need to be improved and made more efficient to meet the sector's requirements for profitability, reliability and availability.

Electrical truck. Photo credit Dan Boman

The planning of transport assignments is a well-studied optimization problem and is known as the Vehicle Routing Problem (VRP). A traditional problem usually involves a fleet of vehicles that should collect and deliver goods from a number of customers as efficiently as possible. The solution is then a route for each vehicle with a specified order of visits to subset of the customers. Usually, the route is planned considering the maximum load capacity of the vehicle and so-called time windows that define when a customer may be visited.

For a large fleet of vehicles, the route planning problem is difficult and computationally demanding. Thanks to the great interest in the problem, optimization methods for developing solutions exist and many are used in practice. However, these methods are developed for traditional vehicles and do not consider the specific characteristics and challenges of heavy-duty electric vehicles.

Electrification of heavy-duty vehicles

One of the most obvious changes requiring new models and methodologies is the need of charging of vehicles and constraints that follows from this. Charging stops need to be planned and consideration needs to be taken to the time and cost of charging and the need for drivers to rest. Due to the high investment costs for an electric vehicle, it needs to be efficiently used. This means that models and methods are needed for deciding when to charge the battery, how much energy should be charged, and with what charging rate.
In addition to the aspects linked to charging, electrification comes with additional planning challenges. One is that external conditions such as weather, temperature, traffic conditions and driving behavior can have a significant impact on energy consumption and, thus, the range of the vehicles. Changing external conditions can therefore mean that replanning is necessary and therefore methods are needed that can efficiently suggest new routes when needed.

Project information

The project is called Condore (Customer Oriented Operations Research for Electrification) and has a total budget of 27 MSEK. The funding comes in equal parts from Scania and the Swedish Energy Agency within the framework of the program FFI, Fordonsstrategisk Forskning och Innovation. At LiU, two PhD students are active in the project: Svante Johansson, industrial PhD student at the Division of Vehicle Systems, Department of Electrical Engineering, and Lukas Eveborn, PhD student in the group Mathematics and algorithms for intelligent decision-making, Department of Mathematics.

Project partners