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Keywords : Hybrid electric vehicle, Optimal electric energy management strategy, Multi-source system, Power fluctuations.

Description of the work

Development of fuzzy logic-based control laws for Boost and Buck/Boost converters.
Design of two electrical energy management strategies based on deterministic rules and fuzzy logic.
Setting up a test bench for experimental application of the various converters control laws and the proposed energy strategies.

Future work

Addition of a third source of energy, for example a battery.
Integration of fuzzy logic type 2 at the energy management level.

07/06/2023

PhD Student : Omaima SMOUNI (UPJV, ICAM Grand Paris Sud)

Supervisors : Meriem LABOUREL NACHIDI (ICAM GPS, MIS), Abdelhamid RABHI (MIS)

Objectives of the thesis

Development of control laws for energy converters, which are in charge of managing the power flow between the various electrical energy sources namely: the fuel cell and supercapacitor.
Elaboration of an optimal energy management approach aimed at guaranteeing an appropriate power distribution between the two sources.

The load and energy sources current at DC bus level. (case : acceleration)

Schematic diagram of fuel

cell hybrid system

ANR V3EA project objectives

Energy management strategy for a hybrid electric vehicle

The load and energy sources current at DC bus level. (case :ITrac > IFC)

Research context

This research work is a continuity of the ANR V3EA project (Véhicule Electrique Econome en Energie et Autonome). The project focuses on enhancing the autonomy and efficiency of electric vehicles on a variety of levels: starting with the decision level of the autonomous vehicle to the hybridization level, while considering the constraints of vehicle dynamics to ensure safe, stable, comfortable and economical driving. Our contribution focuses on the low-level control.

Buck-Boost Converter behavior controlled by Fuzzy Logic