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IoT-Based Intelligent Charging System for Kayoola EVs Buses at Kiira Motors Corporation in Uganda
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Abstract
The increasing popularity of Electric Vehicles (EVs) has led to a surge in the need for charging stations in Kayoola EV buses. Most of existing EV charging stations have outdated features which is challenging to be remotely controlled. However, current EV charging systems experience with no remote battery operational charging status, unsafety control if charging station is faulted, and insecure charging RFID card payment. This paper, an IoT-based system was aimed to manage and monitor these EV charging stations. The battery management system (BMS) sends charging voltage and current information to charger via Controller Area Network (CAN) bus. Then, the Raspberry Pi4 receives and decode CAN charging data to be processed, analyzed and transmits to the cloud server. Each charger is equipped with sensors monitoring parameters like charging status, energy consumption, voltage, current, and time. The user can access that decoded charging information via android mobile application and desk remote management system. Additionally, the system server calculates the battery charging levels and commend RFID card transaction payment. The results show that developed IoT-based intelligent charging system provides and outperforms minimum and maximum cell voltages of 2.82V and 4.1V, min. and max. cell temperatures of 37℃ and 40℃ respectively. The charged energy of 10kWh, used energy of 0kWh, charging state indication, low-cell voltage as error state indication, charging price rate of 500Ugx/kWh, and full-latch of 0, pack voltage of 483.9V, pack current of 100.1A, battery health of 97%, battery state of charge (SoC) of 100% and remaining charging time of 38 mins were also detected and remotely monitored. In conclusion, the developed system proves 100% of real-time and remote data access and accuracy, efficiency, security, accessibility, sustainability, safety charging payment, and remote battery status monitoring system of EV charging infrastructure compared to the current charging where it offers only 58.75% of charging rate.
Springer Science and Business Media LLC
Title: IoT-Based Intelligent Charging System for Kayoola EVs Buses at Kiira Motors Corporation in Uganda
Description:
Abstract
The increasing popularity of Electric Vehicles (EVs) has led to a surge in the need for charging stations in Kayoola EV buses.
Most of existing EV charging stations have outdated features which is challenging to be remotely controlled.
However, current EV charging systems experience with no remote battery operational charging status, unsafety control if charging station is faulted, and insecure charging RFID card payment.
This paper, an IoT-based system was aimed to manage and monitor these EV charging stations.
The battery management system (BMS) sends charging voltage and current information to charger via Controller Area Network (CAN) bus.
Then, the Raspberry Pi4 receives and decode CAN charging data to be processed, analyzed and transmits to the cloud server.
Each charger is equipped with sensors monitoring parameters like charging status, energy consumption, voltage, current, and time.
The user can access that decoded charging information via android mobile application and desk remote management system.
Additionally, the system server calculates the battery charging levels and commend RFID card transaction payment.
The results show that developed IoT-based intelligent charging system provides and outperforms minimum and maximum cell voltages of 2.
82V and 4.
1V, min.
and max.
cell temperatures of 37℃ and 40℃ respectively.
The charged energy of 10kWh, used energy of 0kWh, charging state indication, low-cell voltage as error state indication, charging price rate of 500Ugx/kWh, and full-latch of 0, pack voltage of 483.
9V, pack current of 100.
1A, battery health of 97%, battery state of charge (SoC) of 100% and remaining charging time of 38 mins were also detected and remotely monitored.
In conclusion, the developed system proves 100% of real-time and remote data access and accuracy, efficiency, security, accessibility, sustainability, safety charging payment, and remote battery status monitoring system of EV charging infrastructure compared to the current charging where it offers only 58.
75% of charging rate.
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