Project Description

Modern vehicles are mostly hybrid, i.e., composed of multiple energy sources and reservoirs, and integrate multiple electrified systems. Advanced control methods have to be found to control such multiple-inputs and multi-objectives systems. The Christian-Doppler-Laboratory (CDL) work focuses on splitting the control into multiple levels, the high-level controller for long term operating strategy and the low-level for components control. Taking advantage of the available vehicle predictive information is one of the key elements of the various centralized and distributed controllers developed in the CDL.

Truck on a road and four diagrams left, right, top, bottom
three circles with schematic content like crosses, lines, squares, graphs

Finally, modularity of the proposed algorithm is crucial to develop strategy that can be reused for different vehicle applications, from passenger vehicles to heavy-duty trucks, and with different powertrain components such as a fuel cell, a battery, an engine, emission after treatment systems, cooling units…

Video Presentation

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Watch our project video on this exciting topic!

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Video Title: A predictive control strategy of nonlinear multivariate systems

A predictive control strategy of nonlinear multivariate systems applied to hybrid powertrains by Alexis Benaitier


Euler-Rolle, Nikolaus, Ferdinand Krainer, Stefan Jakubek, and Christoph Hametner. "Automated synthesis of a local model network based nonlinear model predictive controller applied to the engine air path., opens an external URL in a new windowControl Engineering Practice 110 (2021): 104768.

Cooperation Partner


  • February 2017 - January 2024


CDL Powertrain

Associate Prof. Dipl.-Ing. Dr.techn. Christoph Hametner

Send email to Christoph Hametner