Impact of actuator dynamics on optimal energy management of a HEV (3075)
Target group: Automotive Engineering
At Research and Development you will be a key contributor to the next generation outstanding luxury cars from Volvo. Together with other engineers around the world, you and your team will create innovative human-centric car technology that makes life less complicated and more enjoyable for people. Are you interested in design and connected car technology? Do you share our passion for people, the environment and our urge to create a superior driving experience? Research and Development is the place for you to prosper.
Background
Utilizing the full potential of hybrid electric vehicles puts high requirements on the control strategy. The aim of the control strategy, or energy management, is to ensure that the additional degree of freedoms introduced through hybridisation is used when and how it is most beneficial. This depends both on the vehicle and on the driving mission ahead of the vehicle.
A common approach for real-time optimal energy management is to view the problem as a series of stationary optimization problems. This approach neglects the transition cost from one operating point to another. It also makes it hard to in an optimization context include discrete decisions, such as gear shift and engine starts, which is instead often included in a heuristic way.
Modern cars are equipped with a growing set of sensors assessing the environment, such as navigation systems, radar, camera, and even cloud connections. This information increases the possibility of predicting the driving demand along the driving mission, which then should be included in the energy management strategy.
Scope
The aim of this master thesis is to develop and implement an energy management strategy incorporating short term predictions and actuator dynamics. The energy management strategy should then be evaluated versus a strategy where the dynamics are neglected, i.e. when solved as series of stationary optimization problems. The impact of prediction horizon length should also be evaluated.
Profile
- Engineering physics/mathematics/electrical/mechatronics, M.Sc., or similar.
- Knowledge in optimal control, optimization and control theory. Specifically knowledge and experience in concepts such as model predictive control (MPC) and convex optimization is meritorious.
- Knowledge in MATLAB. Knowledge in C and Python programming is meritorious.
- Analytical and independent.
Duration
- 20 weeks / 30 ECTS
- Starting date: November-February (Flexible)
- Estimated end date: Summer 2018
- Number of students: 1 or 2 students.
- The work will be performed at dept. 97520 “Vehicle Propulsion, Strategy & Concept”, Volvo Cars Corporation, Göteborg.
Application
Apply at
- Please include a CV and cover letter with your application as soon as possible but no later than 2017-11-15.
- Selection will be ongoing during the application period.
Contact
- Name: Martin Sivertsson
- Mail:
- Telephone: +46729669071
About Volvo Car Group
The future belongs to those who are empowered by a great idea and have the ability to carry it out. At Volvo Car Group, our vision is clear: "To be the world's most progressive and desired premiumcar brand" by simplifying people's lives. We have bold targets when it comes to innovation, sales and customer satisfaction and to make this happen, we need talented people onboard. People with passion, energy, business sense and the drive to innovate. People that want to create the next generation Volvo cars in a global, dynamic and respectful environment. We will support you to reach your full potential. Join us on this exciting journey into the future.