Fully coupled simplified electrochemical and thermal model for series-parallel configured battery pack

Gottapu, Manohar; Goh, Taedong; Kaushik, Anshul; Adiga, Shashishekar P.; Bharathraj, Sagar; Patil, Rajkumar S.; Kim, Dae Hyun; Ryu, Young-Ho

doi:10.1016/j.est.2021.102424

Cited by 20 publications

(4 citation statements)

References 34 publications

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“…The ECM evaluates heat generated from the various internal resistance sources, and feeds it to the thermal model to evaluate temperature distributions at both cell and pack scales. Gottapu et al [154] presented a thermal model for temperature distribution using an ECM at the pack scale for ohmic heat calculations and natural convection. Zheng et al [155] coupled a process control technique in the PI observer to a 1D electrochemical model for co-estimation of SOC, capacity, and resistance for a LIB cell.…”

Section: Combined Modelling Techniquesmentioning

confidence: 99%

Multiscale Modelling Methodologies of Lithium-Ion Battery Aging: A Review of Most Recent Developments

Ali,

Da Silva,

Amon

2023

Batteries

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Lithium-ion batteries (LIBs) are leading the energy storage market. Significant efforts are being made to widely adopt LIBs due to their inherent performance benefits and reduced environmental impact for transportation electrification. However, achieving this widespread adoption still requires overcoming critical technological constraints impacting battery aging and safety. Battery aging, an inevitable consequence of battery function, might lead to premature performance losses and exacerbated safety concerns if effective thermo-electrical battery management strategies are not implemented. Battery aging effects must be better understood and mitigated, leveraging the predictive power of aging modelling methods. This review paper presents a comprehensive overview of the most recent aging modelling methods. Furthermore, a multiscale approach is adopted, reviewing these methods at the particle, cell, and battery pack scales, along with corresponding opportunities for future research in LIB aging modelling across these scales. Battery testing strategies are also reviewed to illustrate how current numerical aging models are validated, thereby providing a holistic aging modelling strategy. Finally, this paper proposes a combined multiphysics- and data-based modelling framework to achieve accurate and computationally efficient LIB aging simulations.

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Section: Combined Modelling Techniquesmentioning

confidence: 99%

Multiscale Modelling Methodologies of Lithium-Ion Battery Aging: A Review of Most Recent Developments

Ali,

Da Silva,

Amon

2023

Batteries

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“…Scaling these cell models to the system level requires the representation of the thermal interaction with other cells, passive components such as the system housing, and the environment. This can be achieved by using highly resolved computational fluid dynamics (CFDs) models [26,38,39]. These models allow for a precise representation of the system's geometry and the calculation of complex phenomena such as heat convection.…”

Section: Introductionmentioning

confidence: 99%

“…Regarding single cell models, the published results often exhibit maximum model errors of around 1 K, e.g., 1.5 K in [34] and 1.35 K in [35]. At the module or pack level, errors of up to 3.3 K [38], or 5 % of the measured temperature [40], can be found. Higher accuracies are, among others, given by Lechermann et al [42] and Kleiner et al [29] with maximum errors below 1 K and 0.5 K, respectively.…”

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confidence: 99%

A Generic Approach to Simulating Temperature Distributions within Commercial Lithium-Ion Battery Systems

Reiter,

Lehner,

Bohlen

et al. 2023

Batteries

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Determining both the average temperature and the underlying temperature distribution within a battery system is crucial for system design, control, and operation. Therefore, thermal battery system models, which allow for the calculation of these distributions, are required. In this work, a generic thermal equivalent circuit model for commercial battery modules with passive cooling is introduced. The model approach can be easily adopted to varying system designs and sizes and is accompanied by a corresponding low-effort characterization process. The validation of the model was performed on both synthetic and measured load profiles from stationary and marine applications. The results show that the model can represent both the average temperature and the occurring temperature spread (maximum to minimum temperature) with deviations below 1 K. In addition to the introduced full-scale model, further simplifying assumptions were tested in order to reduce the computational effort required by the model. By comparing the resulting simplified models with the original full-scale model, it can be shown that both reducing the number of simulated cells and assuming electrical homogeneity between the cells in the module offer a reduction in the computation time within one order of magnitude while still retaining a high model accuracy.

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“…Gao et al, in [24], used an equivalent circuit model in combination with a convective thermal model to estimate the electrical parameters and the temperature of the cells in a 12-cell battery pack. Gottapu et al [25] proposed a simplified electrochemical model and lumped thermal model to analyze the thermal distribution at the pack level. Shabani et al, in [26], presented an overview of the different theoretical, numerical and analytical approaches to thermal modeling in batteries.…”

Section: Introductionmentioning

confidence: 99%

System-Level Modeling and Thermal Simulations of Large Battery Packs for Electric Trucks

et al. 2021

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Electromobility has gained significance over recent years and the requirements on the performance and efficiency of electric vehicles are growing. Lithium-ion batteries are the primary source of energy in electric vehicles and their performance is highly dependent on the operating temperature. There is a compelling need to create a robust modeling framework to drive the design of vehicle batteries in the ever-competitive market. This paper presents a system-level modeling methodology for thermal simulations of large battery packs for electric trucks under real-world operating conditions. The battery pack was developed in GT-SUITE, where module-to-module discretization was performed to study the thermal behavior and temperature distribution within the pack. The heat generated from each module was estimated using Bernardi’s expression and the pack model was calibrated for thermal interface material properties under a heat-up test. The model evaluation was performed for four charging/discharging and cooling scenarios typical for truck operations. The results show that the model accurately predicts the average pack temperature, the outlet coolant temperature and the state of charge of the battery pack. The methodology developed can be integrated with the powertrain and passenger cabin cooling systems to study complete vehicle thermal management and/or analyze different battery design choices.

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Fully coupled simplified electrochemical and thermal model for series-parallel configured battery pack

Cited by 20 publications

References 34 publications

Multiscale Modelling Methodologies of Lithium-Ion Battery Aging: A Review of Most Recent Developments

Multiscale Modelling Methodologies of Lithium-Ion Battery Aging: A Review of Most Recent Developments

A Generic Approach to Simulating Temperature Distributions within Commercial Lithium-Ion Battery Systems

System-Level Modeling and Thermal Simulations of Large Battery Packs for Electric Trucks

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