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- Astaneh, Majid, 1990, et al.
(författare)
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Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications
- 2020
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Ingår i: Energies. - : MDPI AG. - 1996-1073 .- 1996-1073. ; 13:14
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Tidskriftsartikel (refereegranskat)abstract
- Large-scale introduction of electric vehicles (EVs) to the market sets outstanding requirements for battery performance to extend vehicle driving range, prolong battery service life, and reduce battery costs. There is a growing need to accurately and robustly model the performance of both individual cells and their aggregated behavior when integrated into battery packs. This paper presents a novel methodology for Lithium-ion (Li-ion) battery pack simulations under actual operating conditions of an electric mining vehicle. The validated electrochemical-thermal models of Li-ion battery cells are scaled up into battery modules to emulate cell-to-cell variations within the battery pack while considering the random variability of battery cells, as well as electrical topology and thermal management of the pack. The performance of the battery pack model is evaluated using transient experimental data for the pack operating conditions within the mining environment. The simulation results show that the relative root mean square error for the voltage prediction is 0.7–1.7% and for the battery pack temperature 2–12%. The proposed methodology is general and it can be applied to other battery chemistries and electric vehicle types to perform multi-objective optimization to predict the performance of large battery packs.
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| 2. |
- Astaneh, Majid, 1990, et al.
(författare)
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Lithium-Ion Battery Pack Modelling for Electric Vehicles in Mining Applications Using GT-AutoLion
- 2020
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Large traction battery packs play a pivotal role in electric vehicles (EVs) to fulfill the system demand for high voltage and capacity. Therefore, accurate and robust modeling of both individual battery cells and their aggregated behavior in battery packs is of crucial importance. This presentation proposes a novel approach to integrate the validated electrochemical-thermal models of the Lithium-ion (Li-ion) cells into battery pack simulations for electric vehicle applications. The approach employs the calibration optimization methodology that utilizes experimental measurements for battery cells and for the battery pack under realistic operating conditions in mining applications. The random variability of battery cells, as well as electrical topology and thermal management of the pack have been considered in the present study to mimic the actual behavior of the battery pack under consideration. The simulations were carried out in GT-AutoLion and the optimizations were performed using GT-SUITE direct optimizer. The experimental data were provided by Northvolt AB, a leading European manufacturer of the next-generation Li-ion battery cells and complete battery systems. The proposed methodology is general and can be applied to other battery chemistries and electric vehicle types to perform multi-objective optimization to predict the performance of large battery packs.
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