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- W3048997718 abstract "Battery is a device that contains electrical cells. It can store energy which is later converted into power. Conventionally to find out the power stored in the battery using an open circuit voltage test. This causes the battery cannot be monitored continuously during the charging state. In this proposal the design of artificial neural network systems was conveyed. This artificial neural network is designed to estimate the value of State of Charge (SOC) on the battery and equipped with a bluetooth feature. The estimation system consists of a voltage sensor and ACS 712 current sensor to send information about the condition of the battery to the STM32F1 microcontroller as the control center. This estimator has functions, namely estimation of SOC. So it is expected that if the battery is connected to this system, then the SOC battery will always be monitored accurately." @default.
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- W3048997718 date "2020-07-01" @default.
- W3048997718 modified "2023-09-28" @default.
- W3048997718 title "Real Time State of Charge Estimation for Lead Acid Battery Using Artificial Neural Network" @default.
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- W3048997718 doi "https://doi.org/10.1109/isitia49792.2020.9163692" @default.
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