Modeling of lithium-ion battery and state of charge estimation using matlab/simulink

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التفاصيل البيبلوغرافية
المؤلف الرئيسي: Hasan Neamah Abbas Khafaji
مؤلفون آخرون: Mohd. Junaidi Abdul Aziz, supervisor
التنسيق: Master's thesis
اللغة:الإنجليزية
منشور في: Universiti Teknologi Malaysia 2025
الموضوعات:
الوصول للمادة أونلاين:https://utmik.utm.my/handle/123456789/40802
Abstract Abstract here
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author Hasan Neamah Abbas Khafaji
author2 Mohd. Junaidi Abdul Aziz, supervisor
author_facet Mohd. Junaidi Abdul Aziz, supervisor
Hasan Neamah Abbas Khafaji
author_sort Hasan Neamah Abbas Khafaji
description Not available
format Master's thesis
id utm-123456789-40802
institution Universiti Teknologi Malaysia
language English
publishDate 2025
publisher Universiti Teknologi Malaysia
record_format DSpace
record_pdf Restricted
spelling utm-123456789-408022025-03-06T18:10:59Z Modeling of lithium-ion battery and state of charge estimation using matlab/simulink Hasan Neamah Abbas Khafaji Mohd. Junaidi Abdul Aziz, supervisor Electrical engineering Not available Due to a lack of sustainable energy sources and the effects of climate change, the development of electric vehicles (EVs) have accelerated during the past years. One of the major technologies used in EVs, the battery, likewise contributes to the growth of EVs being constrained. Due to its high energy density, extended lifespan, high efficiency, quick charging capability, and minimal self-discharge, lithium ferro phosphate (LiFePO4) is among the lithium-ion batteries that is widely utilised. The state of charge (SOC) assessment of the battery is a crucial characteristic that must be carefully taken into account for battery management systems (BMS). To monitor how the battery pack is being charged and discharged, optimise performance, and increase battery life, it is essential that the SOC estimation be accurate. The SOC calculation gets exceedingly complicated because the battery stores energy in a chemical state that cannot be immediately accessed. Additionally, there are several uncertainties and disturbances that make judging the accuracy of a SOC estimation difficult. This project's objectives concentrate on creating a LiFePO4 battery model utilising an Equivalent Circuit Model (ECM) to forecast SOC using the Unscented Kalman Filter (UKF) technique. Two different types of battery ECM modules with two RC pairs and three RC pairs were studied to compare the model's accuracy. Using the dynamic behaviours of a LiFePO4 battery from an experimental data, the battery ECM parameters were calculated using the MATLAB Parameter Estimation Tool. Constant Discharge Test (CDT), Pulse Discharge Test (PDT), and Random Charge and Discharge Test (RCDT) have all been used in experiments to examine the dynamic properties of the LiFePO4 battery. Battery ECMs with two RC pair and three RC pairs were used to achieve the SOC estimation using the UKF block algorithm in MATLAB. Then, using error analysis tools including Mean Square Error (MSE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), the accuracy of the battery ECMs was analysed. The most precise battery ECM was chosen to be used in the UKF method to predict the SOC of a LiFePO4 battery based on the findings of the error analysis. After that, the simulation's result is verified by comparison to the actual SOC using the Coulomb Counting technique. Then, using error analysis like MAE, MSE, and RMSE, the performance of a UKF algorithm was compared to an Extended Kalman Filter (EKF). The most accurate method for estimating value of SOC is chosen depend on the results of the error analysis. fahmimoksen UTM 114 p. Thesis (Master of Engineering (Electrical Power)) - Universiti Teknologi Malaysia, 2022 2025-03-06T10:08:46Z 2025-03-06T10:08:46Z 2022 Master's thesis https://utmik.utm.my/handle/123456789/40802 vital:149906 valet-20230109-100718 ENG Closed Access UTM Complete Unpublished Completion application/pdf Universiti Teknologi Malaysia
spellingShingle Electrical engineering
Hasan Neamah Abbas Khafaji
Modeling of lithium-ion battery and state of charge estimation using matlab/simulink
thesis_level Master
title Modeling of lithium-ion battery and state of charge estimation using matlab/simulink
title_full Modeling of lithium-ion battery and state of charge estimation using matlab/simulink
title_fullStr Modeling of lithium-ion battery and state of charge estimation using matlab/simulink
title_full_unstemmed Modeling of lithium-ion battery and state of charge estimation using matlab/simulink
title_short Modeling of lithium-ion battery and state of charge estimation using matlab/simulink
title_sort modeling of lithium ion battery and state of charge estimation using matlab simulink
topic Electrical engineering
url https://utmik.utm.my/handle/123456789/40802
work_keys_str_mv AT hasanneamahabbaskhafaji modelingoflithiumionbatteryandstateofchargeestimationusingmatlabsimulink