DNRF Chair: Bengt Håkan Johansson

The proposed concept is an engine relying on AI to select combustion mode depending on engine speed and load (torque) to optimize engine efficiency and emissions for all operating points. Should the conditions at high load be right for Compression Ignition, the engine control system will be tuned to optimize this mode with multiple injections of fuel per cycle. Should the conditions be right for PPC, HCCI or SACI, the engine will automatically switch to the one best suited and then tune it.

The AI controlled engine will rely on closed loop combustion control, a research area in which Prof Johansson has an extensive publication record in. The exact realms of the combustion modes will change with engine conditions but also with the fuel. As an example, ethanol can easily be used with CI and PPC at high load where knock will severely limit SI operation. However, at low load CI combustion cannot be used but SI works well.  By combining SI and CI, as well as the more advanced concepts of HCCI, PPC and SACI, in the same engine, we can use the best features of them.

Done right, the AI controlled engine can even be totally fuel agnostic, being capable of using any sustainable fuel without hardware modification. The AI will learn and adapt the realms of the combustion modes and fine tune the performance for each while the engine is operated. Self-tuning, adaptive, control algorithms will be used.

Only fuels from sustainable sources will be considered, enabling decarbonization of the transport sectors that are hard or impossible to electrify. Hydrogen is a major thrust for long range HD trucks. For the marine sector, the major thrust is on e-methanol for the short time horizon and e-ammonia for the longer.