Robust control approach to battery health accommodation of EMS in HEV

In the recent years, growing public concern has been given both on the energy problem and on the environment problem resulted from dramatically increased vehicles equipped with Internal Combustion Engine (ICE). Subsequently, intensive contributions have been made by the automotive industries and research institutes on vehicles that depend less on the fossil fuels, and introduce less pollutant emissions. This has led to the emergence of environment-friendly and energy-saving vehicles such as the Hybrid Electric Vehicle (HEV) that is usually equipped with one or more additional electric motors and the associated power battery compared with the Conventional vehicles (CVs) propelled solely by the ICE. The key point of an HEV is to design a proper Energy Management Strategy (EMS) that decides how to split the demanded power between the engine and the motor (battery). As the most important and expensive part of an HEV, it is important to take into account battery states, such as battery State of Charge (SOC) and battery ageing, aiming at maintain the optimality of the achieved EMS, as well as prolonging the battery life. In this dissertation, an HEV of parallel structure, which is equipped with a Lithiumion battery is considered. This dissertation is focused on accounting for battery related items, i.e. battery SOC and SOH indicated by battery parameters, in the EMS developments leading to a kind of fault tolerant EMS. Some brief introduction on the control methods and realization approaches involved in this work is presented first, followed by two big parts: the first part is focused on the battery modeling and estimation, while the second part is concerned by the vehicle modeling and few kinds of EMS development methods.

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Source https://theses.hal.science/tel-00947310
Author Wang, Tinghong
Maintainer CCSD
Last Updated May 6, 2026, 09:15 (UTC)
Created May 6, 2026, 09:15 (UTC)
Identifier NNT: 2013GRENT038
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Grenoble Images Parole Signal Automatique (GIPSA-lab) ; Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)
creator Wang, Tinghong
date 2013-10-23T00:00:00
harvest_object_id 7cb61d37-4613-4ef0-b2ff-e6bce7975ec3
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE