Predictive control strategy of nonlinear multivariate systems applied to hybrid powertrains



Modern vehicles are mostly hybrid, for example 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 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.

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 aftertreatment systems, cooling units…

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Project Video

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

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February 2017 - February 2024

Project manager

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

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Nikolaus Euler-Rolle, Ferdinand Krainer, Stefan Jakubek, & Christoph Hametner (2021)

Automated synthesis of a local model network based nonlinear model predictive controller applied to the engine air path. Control Engineering Practice, 110, 104768.