Vehicle Dynamics

We develop mathematical models, simulation tools and advanced control algorithms to analyse and improve vehicle behaviour in both normal and critical driving situations. The work ranges from fundamental dynamic models to the implementation of control systems in real vehicles.
The research is often carried out in close collaboration with the automotive industry and focuses on future mobility, including electrified and automated vehicles.

Research areas

The group’s research includes, among other things:

• Vehicle dynamics modelling: Development of mathematical models that describe how vehicles move and respond to steering, acceleration and external forces.
• Control of vehicle motion: Design of control systems for stability, manoeuvrability and safety, including advanced chassis and braking systems.
• Automated driving: Methods for motion planning and stable control of automated vehicles.
• Tyre–road/ground interaction: Modelling of tyre forces and how they affect vehicle dynamics and stability.
• Energy-efficient motion planning: Strategies to reduce energy consumption through optimal control of vehicle motion.
• Modelling of vehicle usage: Approaches to understand how vehicles are used, in order to estimate, for example, energy consumption and match design to end users.

Our methods

The research is based on a combination of:

• Physics-based modelling
• System identification and state estimation
• Simulation using advanced vehicle models
• Real-time implementation in test vehicles

A central principle in our research is the use of physics-based models that are sufficiently simple for analysis and algorithm development, yet sufficiently detailed to capture relevant vehicle dynamics.
Vehicle systems are often modelled in a hierarchical structure consisting of environment, driver and vehicle. The vehicle model is in turn divided into interconnected sub-models. At the lowest level, the models are based on established engineering principles such as kinematic relationships, force balance, laws of motion, friction models and elastic relationships.

This type of deductive modelling makes it possible to clearly understand which physical phenomena are represented in the model. The models are then used for analysis and development of both physical systems and control algorithms.

When verifying new hypotheses, we prefer testing with real vehicles or high-fidelity models of complete vehicle systems.

We use advanced simulation and development environments such as MATLAB/Simulink, CarMaker/TruckMaker and optimisation tools based on CasADi for modelling, simulation and development of vehicle control algorithms. The choice of methods and tools is governed by the nature of the problem, as our work is problem-oriented rather than method-driven.

Heavy vehicles

Heavy vehicles introduce particular dynamic challenges compared with passenger cars. Examples include vehicles with multiple articulations, multiple axles, stability issues such as rollover, and very long vehicle combinations. These characteristics place specific demands on modelling, analysis and control systems to ensure safe and efficient operation.

Collaboration with industry

The research group frequently collaborates closely with Swedish and international automotive industry partners in the development of future transport solutions. Research is often conducted in joint projects where industrial applications and real-world problems guide our research questions. These projects are typically carried out in collaboration with industry partners and research programmes in areas such as electrification, automation and road safety.