Result Details
Hybrid Model Predictive Control for Fully Electric Vehicle Thermal Management System Optimal Mode Selection
Šolc František, prof. Ing., CSc., RG-2-02 (CEITEC)
Otava Lukáš, Ing., Ph.D., RG-2-02 (CEITEC), UAMT (FEEC)
Václavek Pavel, prof. Ing., Ph.D., RG-2-02 (CEITEC), UAMT (FEEC)
Vehicle thermal management systems of Fully Electric Vehicles bring increased demands on control algorithms to operate the vehicle efficiently. Especially, if there are multiple heat sources and sinks (cabin, batteries, electric drive, thermal energy storage, etc.), it is necessary to select the system operating mode (configuration of actuators), under which the system will operate efficiently with respecting defined constraints and references tracking. This paper brings a novel approach to the decision-making algorithm, which is based on the Hybrid Model Predictive Control and optimally solves the problem with regards to the defined objective function.
vehicle thermal management system; VTMS; model predictive control; MPC; hybrid model predictive control; HMPC; piecewise-affine; PWA; thermal energy storage; TES; heat pump; fully electric vehicle; FEV; vapor compression refrigeration system; VCRS; waste heat recovery; decision-making algorithm
@inproceedings{BUT165335,
author="Jan {Glos} and František {Šolc} and Lukáš {Otava} and Pavel {Václavek}",
title="Hybrid Model Predictive Control for Fully Electric Vehicle Thermal Management System Optimal Mode Selection",
booktitle="Proceedings of the IECON 2020 - The 46th Annual Conference of the IEEE Industrial Electronics Society",
year="2020",
pages="2036--2043",
publisher="IEEE",
address="New York",
doi="10.1109/IECON43393.2020.9254286",
isbn="978-1-7281-5414-5",
url="https://ieeexplore.ieee.org/document/9254286"
}