30 credits – Machine-Learning Based Load-Change Detection for Heavy Vehicles

Scania genomgår nu en transformation från att vara en leverantör av lastbilar, bussar och motorer till en leverantör av kompletta och hållbara transportlösningar.

Carrying out a thesis project at Scania is an excellent way of making contacts for your future working life. Many of our current employees started their career with a thesis project within the company.


Information about total weight and weight distribution (between the wheels) is used by many electronic systems in modern heavy vehicles. For example, the braking system uses this to distribute the correct braking effort at each wheel, making the mass estimation a safety-critical functionality. Several sensors and algorithms are used to estimate the mass properties in different ways, but are not always quick enough when the truck is being loaded or unloaded, which can lead to unpredictable braking performance and hazardous incidents.


The project assignment is to develop a system that quickly detects or predicts changes in the vehicle’s weight, by using currently available sensors and information in Scania trucks. This system will have the most value for vehicles that are exposed to large and frequent load changes, which often are vehicles operated in a cyclic manner. By analyzing location data (e.g., GPS) from these vehicles with driving pattern recognition and machine learning algorithms, the system should be able to predict when and where the vehicle load will change. If fused with sensor information (from e.g., accelerometers) and historical vehicle mass data (from other mass estimation functions), a good guess of the new vehicle weight and weight distribution is also possible.

The project will require a theoretical survey of applicable methods, test design, and planning, as well as extensive data processing and analysis.


Preferred experience and competence of applicants:

  • Mechanical engineering, applied physics, electrical engineering, vehicle engineering, or similar.
  • Machine learning and pattern recognition
  • Signal processing
  • Sensor fusion
  • Scripting/programming (e.g., MATLAB)
  • Number of students: 2

    Start date: January-February 2020

    Estimated time needed: 20 weeks

    Contact person

    Linus Flodin, 08-553 71405

    Skicka din ansökan till med rubrikraden Ny Teknik Jobb.

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