Master thesis

Background 

Heavy-duty road transport is undergoing a significant transition toward CO2 neutrality. To support this transition, advanced engine modeling and simulation techniques are crucial for developing and optimizing new powertrain solutions efficiently and cost-effectively. Hydrogen combustion, particularly pre-mixed hydrogen combustion, is emerging as a promising technology in this field. 

About Us 

At Volvo Powertrain we shape technology strategies and inform business decisions for new powertrain solutions. We actively explore emerging powertrain technologies, regulatory shifts, and future societal needs to prepare a powertrain roadmap. Furthermore, we develop technology solutions that support the transition from concept to production, enabling the next generation of sustainable transport solutions. 

Thesis Background 

The development of new engine concepts, especially those involving pre-mixed hydrogen combustion, is a complex and resource-intensive process. Single-cylinder engine (SCE) tests, combined with advanced 0D/1D simulations, offer an efficient way to evaluate future engine concepts before investing in full-scale prototypes. However, there's still a gap between experimental data and simulation models that, if bridged, could significantly enhance our predictive capabilities for hydrogen-fueled engines. 

The thesis introduces a HIL/SIL type of methodology, which we refer to as “Virtual Multi-Cylinder Engine”, designed to enable a dynamic exchange between experimental single-cylinder engine (SCE) data and simulation models, with a particular emphasis on pre-mixed hydrogen combustion. The central concept involves feeding near real-time pressure trace data from an operating single-cylinder engine directly into a 0D/1D simulation environment. This data enables a three-pressure analysis, which yields a burn rate profile. The resulting burn rate is then integrated into a comprehensive engine model, establishing more realistic boundary conditions for simulating the performance of various pre-mixed hydrogen engine configurations. 

Content 

Initially, a literature study should be conducted to gain an understanding of the target domain, including single-cylinder engine testing, 0D/1D modeling, three-pressure analysis techniques, and the specifics of pre-mixed hydrogen combustion.The next step is to evaluate the existing methodology for integrating experimental data from a running single-cylinder engine with simulation models, tailored for hydrogen combustion. This will involve: 

• Evaluating and learning a method to feed actual pressure trace data from a running single-cylinder engine to a simulation model, considering the unique characteristics of hydrogen combustion. 

• Implementing a three-pressure analysis on a single-cylinder 0D/1D model to generate a burn rate for pre-mixed hydrogen combustion. 

• Creating or evaluating existing full-scale engine model that uses the generated burn rate to provide correct boundary conditions for the single-cylinder hydrogen engine. 

• Comparing the accuracy of the integrated setup in relation to a simulation model generating the boundary conditions with existing combustion model and no experimental data input, specifically for pre-mixed hydrogen combustion. 

• Evaluating a suitable data pipeline that handles large amounts of data from the test cell, processing this data to extract relevant information for the simulation models and feedback the resulting engine settings based on simulation suggestion. This particular item may be computer science oriented rather than combustion specific. 
  
  

Research Depth 

The research will focus on investigating the accuracy of exchange setup in relation to directly using boundary conditions from a simulation model with an integrated combustion model for pre-mixed hydrogen combustion. 

• Evaluation of a data pipeline allowing this exchange to occur in regards to measurement productivity. Methods of ensuring data exchange – "batch" data vs "streamed" data, considering the rapid combustion characteristics of hydrogen. 

• Sensitivity analysis on cycle-to-cycle variation of experimental data on the resulting output of boundary conditions to determine importance, particularly relevant for hydrogen combustion. 

• Analysis of the effectiveness of the data exchange in improving the resulting output – "fingerprint" measurement of a virtual engine concept for various operating conditions specific to pre-mixed hydrogen combustion. 

• Given favorable project progression - Evaluation of the system's potential for reducing development time and costs in hydrogen engine concept exploration. 

• Investigation of potential limitations and areas for further improvement in the integrated experimental-simulation approach for pre-mixed hydrogen combustion. 
  
  

This research aims to bridge the gap between experimental testing and simulation, enabling more accurate and efficient evaluation of new hydrogen engine concepts without the need for full prototype development.  

Suitable Background 

The thesis scope in relation to above content could either be computer science oriented (data engineering pipeline facilitating this exchange in an effective way) or combustion oriented focusing on effectiveness of this method for engine development. The choice of scope will be decided based on applications we receive. 

 
We are looking for candidates in the final year of their Master's studies, preferably from faculties of Mechanical Engineering, Applied Physics, Computer Science and Chemical Engineering. An interest in automotive engineering, internal combustion engines (particularly hydrogen engines), and simulation techniques is valued. Experience or interest in data processing, control systems, or engine modeling will be beneficial.
 

Supervision and examination 

Powertrain Engineering, GTT,  

Thesis Level: Master 

Language: English 

Starting date: January/February 2025 

Number of students: 2 

Physical location: Volvo Lundby (CampX) 

Contact: 

Djordje Purkovic, djordje.purkovic@volvo.com 

Jian Zhu, jian.zhu@volvo.com  

Last application date: 14th of December. We will be performing a continuous selection.