Research engineer within - Predictive Energy Control for Fuel Cell HEVs

Job description

The unit of Mechatronics is searching for a Control Engineer for developing health-aware model predictive control (MPC) for fuel cell hybrid electric vehicles (FCHEVs). Fuel Cell HEVs provide a long-term solution to sustainable and efficient transportation. Since fuel cells have slow dynamics and quick degradation, optimal and predictive energy management control is crucial for maximizing energy efficiency and extending lifetime. Most studies on this topic explore optimization and deep learning methods for finding the global optimal solutions offline and verify the results by model-in-the-loop simulations, but this project emphasizes real-time MPC executable in vehicular onboard processors. Compared to the existing control method, the new MPC solution is expected for four major improvements:

1. Overall energy consumption, including both hydrogen and net electricity costs, shall be reduced by around 10%, especially on long-distance driving routes.
2. The total on/off switch times of fuel cells shall be decreased, and frequent switches within a short period must be avoided.
3. The battery and fuel cell lifespans shall be obviously extended by eliminating unnecessary spikes on power output and assigning “sweet” operation points.
4. The scalable MPC solution shall be adaptable to various types of FCHEVs.

The project results will be ultimately applied on a physical test vehicle. The developed MPC controller shall be executable in real-time on a vehicle onboard microprocessor.

Some of the key responsibilities include, (1) research and development of the MPC controller; (2) test the controller on both simulation and a physical vehicle; (3) comparing the developed MPC controller with state-of-the-art energy management controllers for FCHEVs.

Qualifications

Requirements

• A graduate degree or an advanced level (higher education) in the research subject related to control engineering, electric vehicles, hybrid powertrains, and/or fuel cell systems or equivalent competence. 
• Working experience on dynamic programming, mixed integer nonlinear programming, model predictive control, and reinforcement learning.
• Knowledge of hybrid electric vehicles, fuel cell systems, and battery management.
• You must be well versed with one or more of the following languages and toolboxes MATLAB/Simulink/Simscape, Python, CasADi, fmincon, etc.

Preferred qualifications

• Writing scientific papers
• PhD study experience in a related field.
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality.

Great emphasis will be placed on personal skills.

Join us at KTH

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Learn more about our benefits and what it's like to work and grow at KTH.

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To apply for the position

Log into KTH's recruitment system to apply for this position. You are responsible for ensuring that your application is complete according to the instructions in the ad.

The application must include:

• CV including relevant professional experience and knowledge.
• Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
• Brief account of why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Max two pages long.

Your complete application must be received by KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).

About the employment

The employment is valid for a limited time according to the agreement - for up to 11 months, with access according to agreement.

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