Hybrid Model Predictive Control for Fully Electric Vehicle Thermal Management System Optimal Mode Selection

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9254286_accepted.pdf(1.24 MB)
Date
2020-10-18
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IEEE
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Abstract
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.
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Keywords
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
Citation
Proceedings of the IECON 2020 - The 46th Annual Conference of the IEEE Industrial Electronics Society. 2020, p. 2036-2043.
https://ieeexplore.ieee.org/document/9254286
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Peer-reviewed
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en
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(C) IEEE
DOI
10.1109/IECON43393.2020.9254286
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http://hdl.handle.net/11012/195674
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