Energy-Based Functional Modelling for Control Architecture Design: An Application to Energy Management for a Hybrid Electric Vehicle

Autor: Philippe Fiani, Emmanuel Godoy, Sylvain Chavanne, Lahsen Ait Taleb, Cristina Vlad, Mert Mokukcu
Přispěvatelé: Laboratoire des signaux et systèmes (L2S), Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Sud - Paris 11 (UP11), Sherpa Engineering, Oleg Gusikhin, Kurosh Madani, Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Informatics in Control, Automation and Robotics. 14th International Conference, ICINCO 2017 Madrid, Spain, July 26-28, 2017 Revised Selected Papers
Oleg Gusikhin; Kurosh Madani. Informatics in Control, Automation and Robotics. 14th International Conference, ICINCO 2017 Madrid, Spain, July 26-28, 2017 Revised Selected Papers, 495, Springer, pp.47-72, 2020, Lecture Notes in Electrical Engineering, ⟨10.1007/978-3-030-11292-9_3⟩
Informatics in Control, Automation and Robotics ISBN: 9783030112912
ICINCO (Selected Papers)
DOI: 10.1007/978-3-030-11292-9_3⟩
Popis: The increasing complexity of energy systems leads to a growing interest in energy management that is actively studied using modelling methods and simulation tools capable to represent the re system’s behavior. In this study, a functional energetic modelling method is proposed to design the control architecture for the management of the energy flow. This method relies on local control loops, a decision manager (DM) and basic equations. When the functional level of abstraction is used to model a complex system, the evaluation of the model accuracy (from an energetic point of view) and the validation of energy management strategies are simplified by fast simulations due to low model complexity. Even if the functional model allows a first-stage validation of the energy allocation within the system, the energy management strategies have to be tested using a more precise model, which is the multi-physical model of the system. The multi-physical modelling level has its own local controllers and global resource manager (GRM) to handle the energy allocation between the different components. The second-stage in the validation is completed by adapting the functional model in order to obtain the high-level controller (i.e. the GRM) for the multi-physical level. The development of the control architecture of the multi-physical model based on the functional model requires two steps: (i) adjusting the functional elements’ parameters and (ii) proposing a method to interconnect the models at both levels of representation (functional and multi-physical levels). The modelling and the parametrization of the functional elements are demonstrated on a hybrid electric vehicle (HEV). The GRM design is detailed and the simulation results of the HEV system at multi-physical level are illustrated to validate the system architecture, the component sizing and the energy management strategy. The fuel consumption is evaluated in comparison to the HEV’s design specifications.
Databáze: OpenAIRE