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Estimation of state of charge and health by developed method EKF model RC battery in battery management system for electric vehicles
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SEYED SAEED ABDOLLAHI KHOU   , JAVAD Olamaee * , S. Mohammad Hassan Hosseini |
| Department of Power Electrical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran |
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Abstract: (59 Views) |
accurate estimation of the state of charge of a battery not only for optimal energy management (OEM) in electric vehicles (EVs) and smart power grids, but also necessary to protect the battery from going into deep discharge or overcharge conditions and thus reducing battery life. These conditions may even create potentially dangerous conditions in terms of battery explosion. Despite the great importance of the state of charge parameter, this parameter cannot be measured directly from the battery terminals. Among many functions, the battery management system (BMS) needs a method to estimate the state of charge and determine the health status of the electric vehicle battery. In this research, first, the electric equivalent circuit model is simulated in MATLAB environment with RC network. This model has the advantage of providing a quick test to extract the parameters and dynamic characteristics of the battery model. Using the extended Kalman filter (EKF) to estimate the state of charge and several methods to estimate the state of health of the battery of the considered electric vehicle, it has been investigated and the simulation results have been shown.
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| Keywords: lithiumion battery, battery charging mode, battery health mode, battery management system, electric vehicle |
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Full-Text [PDF 814 kb]
(48 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2024/01/2 | Accepted: 2024/02/28 | Published: 2024/02/29
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