"PhD Scholarship in AI Controlled Combustion Engine - Closed Loop Combustion Control"

We need to reduce climate impact by replacing fossil fuel. In this PhD project you can help with the green transition by enabling widespread use of alternative fuels. As biofuels and e-fuels will be more expensive, at least initially, it is of paramount importance to use them with the highest possible efficiency. Traditional Spark Ignition and Compression Ignition Internal Combustion Engines, ICE, have been optimized for fossil fuels for more than 140 years but the new fuels have properties that can enable a more efficient operation. Advanced combustion processes like HCCI, SACI and PPC will be used in this project. The overall goal of the project is to use AI to optimize combustion in real time and select which combustion mode is the best at each instance.

The AI controlled engine will rely on closed loop combustion control. 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.

This part of the three-student project is focusing on setting up the closed loop combustion control and adapting this control using self-learning algorithms.

Qualifications

You should have a basic understanding of combustion and engines. Knowledge of advanced combustion concepts is a merit but not a prerequisite. Practical experience of engine operation in a lab is a merit. Knowledge of control theory is a merit and even better is knowledge of adaptive control, machine learning and AI.

But the most important qualification is an eagerness to learn the mysteries of fuel-combustion-engine interaction.

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Salary and appointment terms

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.

The period of employment is 3 years. The starting date is 1 December 2025, or according to mutual agreement. The position is a full-time position, and the work will be conducted in the section of Thermal Energy Systems, DTU Construct.

Application procedure

To apply, please read the full job advertisement by clicking the 'Apply' button.

Further information

Further information may be obtained from Professor Bengt Johansson bhajo@dtu.dk. You can read more about Department of Civil and Mechanical Engineering at www.constuct.dtu.dk and about DTU at www.dtu.dk/english.