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Thermal Management in Plug-In Hybrid Electric Vehicles: a Real-Time Nonlinear Model Predictive Control Implementation

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10.1109/TVT.2017.2678921
 
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López Sanz, Jorge
Ocampo-Martínez, CarlosMés informacióMés informacióMés informació
Álvarez Flórez, Jesús AndrésMés informacióMés informacióMés informació
Moreno Eguilaz, Juan ManuelMés informacióMés informacióMés informació
Ruiz Mansilla, RafaelMés informacióMés informacióMés informació
Document typeArticle
Defense date2017-09-15
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
This work is protected by the corresponding intellectual and industrial property rights. Except where otherwise noted, its contents are licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
A real-time nonlinear model predictive control (NMPC) for the thermal management (TM) of the electrical components cooling circuit in a Plug-In Hybrid Electric Vehicle (PHEV) is presented. The electrical components are highly temperature-sensitive and therefore working out of the ranges recommended by the manufacturer can lead to their premature aging or even failure. Consequently, the goals for an accurate and efficient TM are two: to keep the main component, the Li-ion battery, within optimal working temperatures, and to consume the minimum possible electrical energy through the cooling circuit actuators. This multi-objective requirement is formulated as a finite-horizon optimal control problem (OCP) that includes a multi-objective cost function, several constraints and a prediction model especially suitable for optimization. The associated NMPC is performed on real-time by the optimization package MUSCOD-II and is validated in three different repeatable test-drives driven with a PHEV. Starting from identical conditions, each cycle is driven once being the cooling circuit controlled with NMPC and once with a conventional approach based on a finite-state machine. Compared to the conventional strategy, the NMPC proposed here results in a more accurate and healthier temperature performance, and at the same time, leads to reductions in the electrical consumption up to 8%.
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© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
CitationLopez, J., Ocampo-Martinez, C.A., Alvarez, J.A., Moreno-Eguilaz, J.M., Ruiz Mansilla, R. Thermal Management in Plug-In Hybrid Electric Vehicles: a Real-Time Nonlinear Model Predictive Control Implementation. "IEEE transactions on vehicular technology", 15 Setembre 2017, vol. 66, núm. 9, p. 7751-7760. 
URIhttp://hdl.handle.net/2117/108064
DOI10.1109/TVT.2017.2678921
ISSN0018-9545
Publisher versionhttp://ieeexplore.ieee.org/document/7872511/
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  • GREENTECH - Grup de Recerca en Tecnologies Renovables - Articles de revista [21]
  • Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Articles de revista [1.539]
  • CREMIT - Centre de Recerca de Motors i Instal·lacions Tèrmiques - Articles de revista [62]
  • SAC - Sistemes Avançats de Control - Articles de revista [558]
  • Departament de Màquines i Motors Tèrmics - Articles de revista [514]
  • MCIA - Motion Control and Industrial Applications Research Group - Articles de revista [260]
  • Departament d'Enginyeria Electrònica - Articles de revista [1.864]
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