Research Projects

Ongoing Research Projects
  • Hy-Nets
    "Efficient hybrid powertrains by vehicle communication"
  • FOR 2401
    "Optimization-Based Multiscale Control of Low-Temperature Combustion Engines"
  • IMPERIUM
    "Implementation of Powertrain Control for Economic, Low Real Driving Emissions and Fuel Consumption"
  • HIFI ELEMENTS
    "High Fidelity Electric Modelling and Testing"
  • STEP
    "Smart Traffic Eco Powertrain"
  • ICCC
    "Ion-Current Sensor based Closed-Loop Control of Lean Gasoline Combustion with High Compression Ratio"

Completed Research Projects
  • ACOSAR
    "Advanced Co-Simulation Open System Architecture"
  • NET-ECU
    "Connected Engine Control"
Logo Hy Nets
Title Efficient hybrid powertrains by vehicle communication
Acronym Hy-Nets
Funding European Union (European Regional Development Fund, ERDF)
Description

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.

Term

04/2016 - 01/2019

Logo FOR 2401
Title Research Units 2401 – Optimization-Based Multiscale Control of Low-Temperature Combustion Engines
Acronym FOR 2401
Funding German Research Foundation (DFG)
Description

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.

Term

10/2016 - 09/2019

IMPERIUM Project Logo
Title Implementation of Powertrain Control for Economic, Low Real driving Emissions and Fuel Consumption
Acronym IMPERIUM
Funding European Commission, Horizon 2020
Description

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.

Term

09/2016 - 08/2019

HIFI-ELEMENTS
Title High Fidelity Electric Modelling and Testing
Acronym HIFI-ELEMENTS
Funding European Commission, Horizon 2020
Description

HIFI-ELEMENTS is a three-year research and innovation action involving 16 European partners. The project kickoff took place in Aachen, Germany at FEV Europe GmbH. HIFI-ELEMENTS will develop, validate and publish a recommendation for standardisation of model interfaces for common e-drive components, and will implement compliant versions of existing models. Secondly, the project will implement a seamless workflow linking extended versions of existing tools – a model/data management tool and a co-simulation tool for MiL and HiL environments – augmented with effort-saving automated methods for model parameterisation and test case generation. Validation of standardised models and workflow will be done in four industrially relevant use cases depicting common scenarios in e-drivetrain and EV development. On project conclusion, the interface recommendations and workflow methods will be disseminated in order to gain widespread EV-industry adoption.

Term 10/2017 – 09/2020

STEP
Title Smart Traffic Eco Powertrain
Acronym STEP
Funding German Federal Environmental Foundation (DBU)
Description

The follow-up project "STEP - Smart Traffic Eco Powertrain" aims to extend the promising approaches of the previous project "NET-ECU - Networked Engine Control" and to test these in real traffic situations. The previously developed OCT will be extended by additional interfaces for further sensors so that vehicles which are not equipped with V2X can also be detected by using radar, lidar and camera. In addition, the software will be extended so that additional traffic information sources can be used. The previously developed algorithms for reducing emissions will be supplemented in such a way, that energy requirements will also be reduced. These algorithms will then be transferred to electrified drive trains.

Term 04/2018 – 06/2020

ION C
Title Ion-Current Sensor based Closed-Loop Control of Lean Gasoline Combustion with High Compression Ratio
Acronym ICCC
Funding German Federal Environmental Foundation (DBU)
Description

In this project, the applicants aim a deeper understanding of the correlations of the ion current sensor signal and the underlying chemical and physical effects in the cylinder charge and the resulting conductivity, combining a detailed simulation with investigations on test benches in Shanghai and Aachen to improve measurement and signal processing. The analysis circuit will be adapted to improve the signal-to-noise ratio. The identified correlation between the ion current and the cylinder charge state will be used to perform a feasibility study for a new FPGA-based in-cycle control algorithm.

Term 06/2018 – 05/2021