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- W156627669 abstract "Due to various economic, political and environmental reasons, the introduction of electric vehicles (EVs) into the streets is probable. Their introduction will require extra facilities such as the charging stations. In order for EVs to be able to penetrate the market their recharging/ refueling time should be comparable to conventional once. This results in charging stations supplying hundreds of amps to EV batteries. The usual trend in charging EV batteries is that the BMS (Battery Management System) gives various orders and information signals and the charger acts as a slave in the system. But this could result in a dangerous situation if the BMS happens to fail for some reason. Thus in this report a supervisory algorithm is investigated. It is based on modeling the important characteristic of the battery and then identifying suitable model parameters. Then these models are effectively used during decision making in the battery charging process. The results of this report show that: Model based approach to supervision of battery fast charging provides a satisfactory result Battery voltage monitoring through prediction could be used to avoid overvoltage on battery terminals. While SOC models could be used to predict the SOC steps ahead but its use is not that important. Similarly temperature prediction in normal situation is less important as the rate of change of temperature in very low. But temperature prediction could be valuable when the rate of temperature rise is high for some reason. Temperature and state of charge models can effectively be used to validate the corresponding readings from the BMS. At the present state the algorithm is relatively prone to noise levels in the working environment which could be improved in future works." @default.
- W156627669 created "2016-06-24" @default.
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- W156627669 date "2010-01-01" @default.
- W156627669 modified "2023-09-23" @default.
- W156627669 title "Model based approach to supervision of fast charging" @default.
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