Iannucci, Luigi (2025) A Multidisciplinary Validated Modelling Framework for The Design of Battery Packs in Ground Electric Vehicles. [Tesi di dottorato]

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: A Multidisciplinary Validated Modelling Framework for The Design of Battery Packs in Ground Electric Vehicles
Autori:
Autore
Email
Iannucci, Luigi
luigi.iannucci@unina.it
Data: 11 Dicembre 2025
Numero di pagine: 198
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Ingegneria Industriale
Dottorato: Ingegneria industriale
Ciclo di dottorato: 38
Coordinatore del Corso di dottorato:
nome
email
Grassi, Michele
michele.grassi@unina.it
Tutor:
nome
email
Patalano, Stanislao
[non definito]
Vitolo, Ferdinando
[non definito]
Data: 11 Dicembre 2025
Numero di pagine: 198
Parole chiave: Electric Vehicles, Battery Pack Design, Multidisciplinary modelling
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-IND/15 - Disegno e metodi dell'ingegneria industriale
Informazioni aggiuntive: Inserisco qui il mio ciclo di dottorato siccome non è presente nella lista della pagina di "Info Dottorato": Sono un dottorando in Ingegneria Industriale del XXXVIII (38°)Ciclo
Depositato il: 19 Dic 2025 13:34
Ultima modifica: 12 Ago 2026 05:37
URI: https://www.fedoa.unina.it/id/eprint/16018

Abstract

In recent years, the electric vehicle lithium-ion battery packs have reached energy storage levels sufficient to achieve an acceptable driving range for everyday use. However, challenging operative conditions undermine their performance, longevity and safety. Collaborations with automotive manufacturers in research project activities have highlighted some of the common battery pack issues, such as the uneven temperature distribution, inherent cell ageing, and manufacturing inconsistencies. These factors strongly affect the energy and power capabilities of the pack, as well as its overall lifetime. Such key problems are still subjects of ongoing research aimed at improving the electric vehicle reliability and increasing users’ interest in the adoption of this zero-emission automotive technology. In this context, this doctoral thesis introduces a multidisciplinary modelling framework that enables battery pack designers to address these challenges in the preliminary design phases. The framework is composed of several multi-physics battery pack models developed through a bottom-up approach. The modelling methodology begins with the development of a single-cell model and its full electro-thermal characterisation, carried out through an extensive experimental campaign at the Science and Technology for Sustainable Energy and Mobility Institute. After the model validation at the cell level, the battery pack model is constructed, with different modelling strategies adopted depending on the specific investigation. The framework is applied in different studies, which explore the impact of cell positioning on temperature distribution, the optimisation of thermal management and cooling performance, the influence of user driving behaviour on pack degradation, and the effect of manufacturing variability on the electrical and thermal behaviour of the battery pack. These research activities address key design challenges through case studies based on commercial lithium-ion cells for automotive applications. The case studies are primarily investigated through numerical simulations, whose reliability is ensured by experimental validation of the proposed methodology. The main contribution of this thesis lies in the development of a modelling framework that supports electric vehicle manufacturers and researchers in evaluating (i) temperature distribution of different cell layout solutions with several thermal management strategies, (ii) assessing the state of Health degradation related to the vehicle usage, and (iii) the effects of cell-to-cell variability during the battery pack design process. By adopting this framework, manufacturers can address these challenges and design battery systems that meet performance, lifetime, and range requirements.

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