Short Description

Advanced Co-Simulation Open System Architecture

The project consortium consists of leading European vehicle manufacturers, suppliers and research establishments, which are jointly working on the standardization necessary for modular, distributed and open system development. The goal of the project is to develop a system interface that allows real-time systems to be linked together also over relatively large distances and to be merged into functional prototypes consisting of virtual and real components. The project is managed by the VIRTUAL VEHICLE Research Center in Graz. The anticipated results are a more economical development process and opportunities for new business models.


09/2015 - 08/2018


  Logo Hy Nets
Title Hy-Nets
Short Description

Efficient hybrid powertrains by vehicle communication

The objective of the Hy-Nets project is to develop a novel approach for improving the resource and energy efficiency of connected hybrid cars: hybrid propulsions on a test bench will be coupled with an environmental simulation of the vehicles as well as of the communication between the connected cars. This way, new insights can be derived of their influence in realistic city environments. We plan using the city of Paderborn as an example of a typical European city to assess the potentials of hybrid propulsion in combination with networked cars.


04/2016 - 06/2019


  Logo NET-ECU
Short Description

Connected Engine Control

One of the main reasons for increased emissions in real-world-driving are the significantly higher dynamic parts in comparison to the current legislative homologation cycles. Modern emissions optimized engine control algorithms require an accurate prediction of the driving profile. Optimal utilization of complex exhaust after treatment system is still challenging due to a lack of prediction information. At the same time, the number of environment sensors and the networking level of the vehicle with its environment (V2X), caused by security und comfort functions, is continuously rising. The goal of the project is to make these information and networking opportunities accessible for complex engine control algorithms. Connected and predictive engine control units allow the optimization of fuel consumption and emission in real world driving conditions.


04/2016 - 10/2017


  Logo FOR 2401
Title FOR 2401
Short Description

Optimization-Based Multiscale Control of Low-Temperature Combustion Engines

A state-of-the-art approach for closed-loop control of low temperature combustion processes are cycle-based control algorithms. However, these approaches allow only a stable operation in a very limited engine-map. Cycle-based controllers act such that only the system dynamics and disturbances which occur at a cycle-averaged time scale can be controlled. The relevant physico-chemical processes determining the stability and emissions characteristics of low temperature combustion, which proceed on a inner-cyclic time-level, can’t be controlled. For this reason TP1 investigates multiscale control algorithms, to also control the smaller time scales. It is expected that a successful control of these critical time scales allows for distinct enlarging of the operating range, increase of efficiency and reduction of pollutant emissions. The multiscale control is a novel approach.


10/2016 - 09/2019


  IMPERIUM Project Logo
Short Description

IMplementationof Powertrain control for Economic, low Real driving emIssionsand fuel ConsUMption

Fuel economy is a key aspect to reduce operating costs and improve efficiency of freight traffic, thus increasing truck competitiveness.

Under the coordination of AVL, the main objective of the IMPERIUM project is to achieve fuel consumption reduction up to 20% (diesel and urea) whilst keeping the vehicle within the legal limits for pollutant emissions.

The IMPERIUM consortium, regrouping major European actors, is responsible for 45% of the heavy duty vehicles manufactured in the EU and is able to provide a 100% European value chain for the development of future powertrain control strategies for trucks.


09/2016 - 08/2019