Master Thesis: Model Predictive Control for Engine Actuator Coordination

Background 

Heavy-duty powertrains must meet increasingly stringent requirements on nitrogen oxides (NOx) and carbon dioxide (CO₂), while development cycles are becoming shorter. This increases the need for simulation environments that can evaluate control concepts early, reduce dependence on physical testing and support faster, more robust development. 

 
Modern engine control is a multivariable problem. Exhaust gas recirculation (EGR), variable geometry turbine (VGT), intake throttle and start of injection (SOI) all influence engine-out NOx, boost pressure and exhaust temperature. Model Predictive Control (MPC) is attractive because it can coordinate several actuators, anticipate future system behaviour and explicitly handle actuator and operating constraints. 

A physics-based 0-D engine model is available in MATLAB. However, fast compressor-outlet and intake-manifold pressure dynamics make the model numerically stiff. Straightforward Forward Euler integration therefore requires very small time steps, which can make repeated model predictions inside an MPC computationally demanding. The thesis will investigate what model fidelity is needed to achieve useful closed-loop performance at an acceptable computational cost. 

Where You’ll Belong 

Volvo Group Powertrain Technology provides Volvo Group Trucks and Business Area’s with state-of-the-art research, cutting-edge engineering, product planning and purchasing serives, as well as aftermarket product support. The Powertrain Engineering Sweden organization has the full worldwide product platform responsibility for heavy duty engines and transmissions with a large organization of 750 colleagues in Gothenburg and Malmö. 

Why Choose This Thesis? 

• Work on a current industrial challenge at the intersection of engine technology, control engineering and numerical modelling. 

• Gain hands-on experience with MPC, physical 0-D models, reduced-order modelling and data-driven or grey-box identification. 

• Use both steady-state and dynamic data, and validate the work in a MATLAB/Simulink-based simulation environment. 

• Deliver results that can guide future model-based control, calibration and simulation development 

Scope and Content 

The work will be performed by two master’s thesis students as a joint project. The recommended core scope is to establish a reproducible simulation and evaluation chain before adding complexity. The students will work together across modelling, control design, integration and analysis. 

 
Work package Main activities: 

• Baseline and integration: Integrate and verify the existing physics-based 0-D engine model in MATLAB into Volvo’s MATLAB/Simulink environment. Define interfaces, operating conditions, signals and baseline test cases. 

• Numerical feasibility: Characterise the model stiffness and evaluate suitable approaches for efficient simulation, for example implicit integration, model reformulation or time-scale separation. Document the trade-off between accuracy, robustness and execution time. 

• Prediction models: Develop and compare MPC-oriented model alternatives, such as the full 0-D model, a reduced 0-D representation, linearised models and a grey-box identified model using ODYS software and available steady-state and dynamic data. 

• MPC development: Develop an MPC controller in MATLAB/Simulink. The target actuator set is EGR, VGT, throttle and SOI, with engine-out NOx, boost pressure and exhaust temperature as key controlled variables. A staged implementation may begin with a smaller input/output set. 

• Integration and benchmark: Integrate the MPC controller in Volvo’s simulation environment and compare it with the existing cIMC controller using common transient simulation cases. Evaluate tracking, constraint handling, actuator activity, robustness to model mismatch and computational effort. 

• Conclusions and recommendations: Identify the model fidelity required for practical MPC, explain where MPC provides value compared with traditional control, and recommend next steps for continued development. 

Who are you?  

We are looking for two motivated students who will complete this thesis together. The project suits a pair with complementary strengths in control, modelling, simulation and data analysis. 

The key qualifications include:

• Strong skills in modeling and control system
• Interest in optimisation, numerical methods and dynamic system simulation
• Proficient in MATLAB/Simulink
• Ability to work systematically with data, software integration and technical evaluation
• Good communication and collaboration skills
• Knowledge of combustion engines, engine air-path systems or system identification is a plus 
   

Ready for the next step? 

Want to kick-start your career? Please apply now, last application date is 14th of October. We value your data privacy and therefore do not accept applications via mail. 

Thesis level: Master Thesis 30p  

Language: English 

Starting date: January 2027 

For any further details please contact: Johan Dahl, Expert Systems Engineer at johan.dahl@volvo.com 

 Supervision and examination: 
- Powertrain Technology, TTI, Volvo Group 
- Chalmers