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Yousef Firouz

Researcher at Vrije Universiteit Brussel

Publications -  37
Citations -  1373

Yousef Firouz is an academic researcher from Vrije Universiteit Brussel. The author has contributed to research in topics: Battery (electricity) & State of charge. The author has an hindex of 16, co-authored 37 publications receiving 982 citations. Previous affiliations of Yousef Firouz include VU University Amsterdam & K.N.Toosi University of Technology.

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Lithium iron phosphate based battery: Assessment of the aging parameters and development of cycle life model

TL;DR: In this article, the impact of the working temperature on the battery performance over its lifetime was analyzed and a cycle life model was developed to predict the battery cycleability accurately, which revealed that the cycle life of the battery degrades the more the charge current rate increases.
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Concept of reliability and safety assessment of lithium-ion batteries in electric vehicles: Basics, progress, and challenges

TL;DR: The role, mechanism, outcome, and contribution of Li-ion battery degradation in five main failure modes and capacity and power fade for providing reliability assessment models as solutions of existing challenges have been investigated.
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Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion

TL;DR: In this article, an advanced equivalent circuit models (ECMs) were developed to model large format and high energy nickel manganese cobalt (NMC) lithium-ion 20 Ah battery cells.
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Efficiency of three-level neutral-point clamped converters: analysis and experimental validation of power losses, thermal modelling and lifetime prediction

TL;DR: In this article, the analysis and practice of power losses in a three-level neutral-point clamped (NPC) inverter is presented. And the lifetime of semiconductors is predicted using the heating curves in line with the power-cycling concept.
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Developing a real-time data-driven battery health diagnosis method, using time and frequency domain condition indicators

TL;DR: A data-driven algorithm based on multiple condition indicator to estimate battery health using application-based load profiles is proposed and is capable of estimating battery SoH with low computational costs and a relative error of less than 1%.