Automotive
Our activities in the automotive domain has been versatile and long-time standing for more than 20 years. They relate to optimization, robust and nonlinear control as well as estimation of vehicle dynamics (lateral and/or longitudinal). Cooperation with OEMs (BMW) and technology stakeholders (CapGemini, AKKA, IAV) has been enriching and inspiring to us. Several PhD programs have been completed based on such cooperations.
Some of the key research fields in automotive have been:
- Steer-by-wire: Force-feedback and active steering control
- Autonomous driving: Perception, decision making, planing, and control
- Electromobility: Battery-Management-Systems of E-Vehicles
- Advanced vehicle dynamics: Lateral dynamics and active traction control
- Global chassis control: Optimal tire force allocation for traction and steering
- Vehicle dynamics estimation: Tire force estimation using Kalman filter schemes.
Autonomous Driving
By combining the perspectives and algorithmic solutions of machine vision and control engineering, we are working towards an unified solution for autonomous driving. Control algorithms are at core focus of our group and are developed using not only well established concepts such as model predictive control (MPC), but also the modern machine learning techniques such as IL, RL and DNN based stochastic MPC.
Electromobility
Under Construction
Advanced Vehicle Dynamics
Under Construction