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Development of Near Optimal Rule-Based Control for Plug-In Hybrid Electric Vehicles Taking into Account Drivetrain Component Losses
Open AccessArticle

Online Power Management with Embedded Offline-Optimized Parameters for a Three-Source Hybrid Powertrain with an Experimental Emulation Application

Chair of Dynamics and Control, University of Duisburg-Essen, Lotharstr. 1, Duisburg 47057, Germany
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Author to whom correspondence should be addressed.
Academic Editor: K. T. Chau
Energies 2016, 9(6), 439; https://doi.org/10.3390/en9060439
Received: 29 February 2016 / Revised: 25 May 2016 / Accepted: 27 May 2016 / Published: 7 June 2016
(This article belongs to the Special Issue Power Management for Hybrids and Vehicle Drivetrains)
Real-time power management in the presence of one or more reversible energy storage systems is a current issue with hybrid electric vehicles (HEVs). To evaluate the potentials of rule-based power management, optimization with respect to two conflicting objectives, fuel consumption and state of charge (SoC) deviation, is considered in this contribution. A modular structure of power management with decoupled offline and online parts is presented. The online part incorporates look-up tables (LUTs) with parameters from the offline optimization part. This permits an inclusion of more LUTs corresponding to different drive patterns. The goal of this contribution is to combine the real-time applicability of rule-based power management and the multi-objective optimization property of genetic algorithms in a single control strategy. Component aging problems are addressed by suitable design. The influence of sizing is investigated. Finally, an experimental setup consisting of components capable of realizing the dynamics of real powertrain components is realized and introduced. A verification/plausibility assessment of modeled dynamics based on the literature is considered. This newly-introduced concept represents a class of power management, which is easy to implement, can tackle different objectives in real time, and adapt itself to unknown driver demands. View Full-Text
Keywords: rule-based power management; optimization; HEV rule-based power management; optimization; HEV
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Moulik, B.; Söffker, D. Online Power Management with Embedded Offline-Optimized Parameters for a Three-Source Hybrid Powertrain with an Experimental Emulation Application. Energies 2016, 9, 439.

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