Street Vehicles

The institute develops a variety of innovative approaches for mechatronic X-by-Wire chassis, which aim to simultaneously improve energy efficiency, driving safety and comfort. Key fields of research are the development of model- and cognition-based control systems with a focus on motion planning, vehicle dynamics and chassis control, vehicle state estimation, model-predictive overall vehicle control as well as active and semi-active chassis control, together with other core topics of electromobility. The latter include energy management, battery control and battery state estimation.

Projects:

AI For Mobility

“AI For Mobility” (AFM) is a new testing platform to investigate and implement novel control methods based on Artificial Intelligence (AI) within the department of vehicle system dynamics at DLR. This project was launched with the aim of modifying and equipping a production vehicle so it can be used as a test platform for new types of control system functions.

KIFAHR: AI-based vertical dynamic control

In the automotive sector, the aim of vertical dynamic design is to optimise the vehicle's chassis suspension in such a way that certain objectives such as ride comfort and vehicle stability are achieved. The main objective is to maximise ride comfort for the vehicle occupants and road grip for the tyres at the same time.

AICloud: Development of an AI-based Virtual Sensor using a Cloud Computing Platform

Within the AICloud project, the DLR institute SR researched together with EFS TechHub GmbH on innovative AI-based sensor algorithms using a cloud platform. The project aims at implementing a cloud environment that will be referred to as SDK/AICloud , in which the data processing and the computationally intensive training of artificial neural networks can be performed.

AFM Experiments on a Vertical Dynamics Test Rig for AI-based Control Algorithms

The semi-active suspension of the testing platform AI For Mobility (AFM) enables the real-time control of the vertical dynamics of the vehicle. This allows to adapt to varying road excitations, critical driving situations and to optimize both driving safety and riding comfort. In order to design an AI-based damper controller, a high-fidelity model of the vertical dynamics is needed. It can be used for model-based controller-design, as well as learning-based (AI) control methods.

eFMI: Functional Mock-up Interface for Embedded Systems

The eFMI standard (Functional Mock-Up Interface for embedded systems) enables a standardized workflow for the application of physical models, like Modelica models, in algorithms on embedded hardware.