In the long haul transport sector, the reduction of real driving emissions and fuel consumption is the main societal challenge. The LONGRUN project will contribute to lower the impacts by developing different engines, drivelines and demonstrator vehicles with 10% energy saving (TtW) and related CO2, 30% lower emission exhaust (NOx, CO and others), and 50% Peak Thermal Efficiency. A second achievement will be the multiscale simulation framework to support the design and development of efficient powertrains, including hybrids for both trucks and coaches. With the proposed initiatives a leading position in hybrid powertrain technology and Internal Combustion Engine operating on renewable fuels in Europe will be guaranteed. A single solution is not enough to achieve these targets.
The LONGRUN project brings together leading original equipment manufacturers (OEMs) of trucks and coaches and their suppliers and research partners, to develop a set of innovations and applications, and to publish major roadmaps for technology and fuels in time for the revision of the CO2 emission standards for heavy duty vehicles in 2022 to support decision making with most recent and validated results and to make recommendations for future policies. The 30 partners will accelerate the transition from fossil-based fuels to alternative and renewable fuels and to a strong reduction of fossil-based CO2 and air pollutant emissions in Europe.
For control, the electrical architecture of the MY21 vehicle will be used as basis. The e-horizon system and related functionality from the Imperium-project will be “carried over”, and needs to be further developed and fine-tuned to the new vehicle (incl. available signals). This includes: Preview Eco-roll, Pulse & Glide operation of combustion engine, Predictive driver coaching, Predictive path planning, tablet for the driver-coaching functions. Where possible the “smart auxiliaries” (including controls) from the Imperium vehicle will be carried over as well. The role for IFPEN is to tune the models that are created in WP2 for the DAF-truck demonstrator and realize that the signals from “the cloud” can be made available to the truck. TU/e contribution in this project are the processing of IFPEN data and interface from Tablet to micro-autobox, study and assessment of Pulse & Glide operation for a DAF truck, and the real-time optimized driving modes advisory system to the driver.
Eindhoven University of Technology
DAF Trucks N.V.