Particle Reduced, Efficient Gasoline Engines
The Particle Reduced, Efficient Gasoline Engines (PaREGEn) project focuses on the twin challenges of improving the fuel efficiency of next-generation gasoline engines whilst controlling their emissions of particles. The project has committed to demonstrate a 15% CO2 reduction in mid- to premium-sized passenger cars, along with real driving emissions target compliance including the measurement of particles as small as 10 nm in diameter. Ricardo are coordinating the research initiative as part of a 16-partner consortium, representing all sectors of the European automotive industry.
The gasoline engine is likely to continue playing a significant role in passenger cars in the coming decade, particularly in the mid- to premium-sized passenger cars that are used for longer-distance journeys. Manufacturers of components and vehicles will need to continue to meet the demand for powertrain technology. The PaREGEn project will demonstrate both the technical and process development routes to support this need.
Through the use of state-of-the-art development techniques, such as optically accessed single cylinder engines, a range of modelling and simulation tools, and the application of novel engine componentry, the optimal trade-offs between cleanliness and efficiency are being identified for such next-generation gasoline engines.
Specifically, as well as coordinating the project, Ricardo and its work package partners are developing a lean-burn homogeneous direct-injection engine matched with a lean gasoline aftertreatment system at up to TRL 7.
The overall concept and technical approach comprises three major elements:
1. Research for improved understanding
2. Innovation and demonstration of new technology combinations where the developed know-how, software and control strategies are implemented into two novel optimised gasoline engine vehicles
3. Independent assessment of their performance and impact to track the progress of the project towards reaching the targets.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 723954