From Cell to Pack: Experimental Validation of a Thermo-Electrochemical 4s4p Battery Model

Growing deployment of lithium-ion batteries has intensified the need for advanced battery pack simulation tools to address the key engineering challenge of accurately predicting the electrical and thermal behaviour of battery packs. This work presents a scalable, physics-based simulation framework for arbitrary (Ms, Np) lithium-ion battery pack configurations. The framework is demonstrated and experimentally validated using a 4s4p pack with bottom cooling. Experiments were conducted on the pack, with temperatures measured throughout the assembly using 80 thermal sensors distributed uniformly across the pack. The resulting spatially and temporally resolved temperature measurements, together with measured pack voltage, are compared directly with model predictions obtained using both the standard expression for irreversible heat generation and the energetically consistent expression derived in [27], which includes heat of mixing within the electrode particles. The heat-transfer model is parametrised using a charge–discharge protocol that yields the same heat-transfer coefficients for both heating formulations. The standard expression gives only moderate agreement with the measured temperatures, whereas simulations using the energetically consistent expression show very good agreement with both the temperature evolution across the pack and its electrical response. The approach represents each cell as a set of spatially resolved finite sections, each governed by the full Doyle–Fuller–Newman (DFN) equations, with all sections coupled thermally and electrically. For the 4s4p case, this results in a network of 80 simultaneously solved DFN models. This formulation enables detailed prediction of intra-pack thermal and electrochemical behaviour. The simulation platform is implemented as a flexible API. The resulting tool can support the design of more reliable and longer-lasting lithium-ion battery systems across a range of large-scale applications.

Authors

Institutions

Publication Details

Journal
ChemRxiv
Published
2026-11-09
DOI
https://doi.org/10.26434/chemrxiv.15011851/v1
Primary Topic
Battery Modeling and Management
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
preprint

From Cell to Pack: Experimental Validation of a Thermo-Electrochemical 4s4p Battery Model

Monica Marinescu, Mohamed Waseem Marzook, Giles W. Richardson, Ivan Korotkin et al.
ChemRxiv
Battery Modeling and Management
preprint

From Cell to Pack: Experimental Validation of a Thermo-Electrochemical 4s4p Battery Model

Monica Marinescu, Mohamed Waseem Marzook, Giles W. Richardson, Ivan Korotkin, Matheus Leal de Souza
preprint en

Abstract

Growing deployment of lithium-ion batteries has intensified the need for advanced battery pack simulation tools to address the key engineering challenge of accurately predicting the electrical and thermal behaviour of battery packs. This work presents a scalable, physics-based simulation framework for arbitrary (Ms, Np) lithium-ion battery pack configurations. The framework is demonstrated and experimentally validated using a 4s4p pack with bottom cooling. Experiments were conducted on the pack, with temperatures measured throughout the assembly using 80 thermal sensors distributed uniformly across the pack. The resulting spatially and temporally resolved temperature measurements, together with measured pack voltage, are compared directly with model predictions obtained using both the standard expression for irreversible heat generation and the energetically consistent expression derived in [27], which includes heat of mixing within the electrode particles. The heat-transfer model is parametrised using a charge–discharge protocol that yields the same heat-transfer coefficients for both heating formulations. The standard expression gives only moderate agreement with the measured temperatures, whereas simulations using the energetically consistent expression show very good agreement with both the temperature evolution across the pack and its electrical response. The approach represents each cell as a set of spatially resolved finite sections, each governed by the full Doyle–Fuller–Newman (DFN) equations, with all sections coupled thermally and electrically. For the 4s4p case, this results in a network of 80 simultaneously solved DFN models. This formulation enables detailed prediction of intra-pack thermal and electrochemical behaviour. The simulation platform is implemented as a flexible API. The resulting tool can support the design of more reliable and longer-lasting lithium-ion battery systems across a range of large-scale applications.

ChemRxiv
The Faraday Institution (GB), University of Southampton (GB), Imperial College London (GB)
Battery Modeling and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon