• 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"
• CEVOLVER
  "Connected Electric Vehicle Optimized for Life, Value, Efficiency and Range"
• Hy-Nets4all
  "Validation environment for the optimization of electrified driving in urban space "
• ConneCDT
  "Co-Simulation Platform Connecting Chemistry and Powertrain Dynamics to Traffic Simulation "

• Hy-Nets
  "Efficient hybrid powertrains by vehicle communication"
• ACOSAR
  "Advanced Co-Simulation Open System Architecture"
• NET-ECU
  "Connected Engine Control"
• 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"
• CREST
  "Collaborative Embedded Systems"

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

09/2016 - 08/2019

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.

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.

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.

The current generation of electric vehicles is still generally too expensive and limited in range. For this reason, the CEVOLVER project takes a user-centric approach to create battery-electric vehicles that are usable for comfortable long day trips while the installed battery is dimensioned for affordability. Furthermore, the vehicles will be designed to take advantage of future improvements in the fast-charging infrastructure that many countries are now planning.

CEVOLVER tackles the challenge by improving the vehicle itself to reduce energy consumption. Moreover, the usage of connectivity is maximized for further optimizations of both component and system design as well as control and operating strategies. Within the project, it will be demonstrated that long-trips are achievable even without any further increases in battery size, thus avoiding higher cost. The efficient transferability of the results to further vehicles is ensured by adopting a methodology that proves the benefit with an early assessment approach before an implementation in OEM demonstrator vehicles.

In Hy-Nets4all, a development and validation environment is being set up that will enable automated driving functions for electrified vehicles to be developed holistically and efficiently secured. The aim is to reduce the energy requirements and emissions of electrified vehicles in urban areas, to further develop electrical components in a targeted manner, to design driving concepts in line with available and future charging infrastructure, to optimise cooperative driving scenarios and to liquefy traffic flows.

The future project "Collaborative Embedded Systems" (CrESt) aims to create a comprehensive framework for the development of collaborating embedded systems that addresses the novel challenges in the development of collaborating embedded systems in dynamic system networks on the basis of the SPES development methodology and thus gives German industry a decisive competitive advantage in these promising and important fields of application.