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Design of an Intelligent Cooling System for the E-Inobus Battery Box
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The battery Pack is an important component used as a source of electrical energy in E-Inobus. Therefore, an effective cooling system is required to ensure optimal conditions. So, to maintain the performance and safety of the battery pack, a system that can control the air in the battery box is needed. The purpose of this final project is to design a tool known as functional and performance testing. This research uses the R&D method that refers to the ADDIE model. The object of this research is the optimization of the cooling system in the battery box. Data collection and testing of this tool are carried out functionally, and the performance of the tool is tested. Testing the performance of the tool. The result of this research is to successfully make a cooling system optimization tool that is made using a reconditioned box and cooling system optimization tool made using a reconditioned box and Wemos Mega 2560 as a microcontroller, with testing and functional testing on DHT22 has an average difference of 0.65°C. Average difference of 0.65 ° C on the DHT22 sensor (1) and 0.32 ° C on the DHT sensor (2), then the performance test of the device. DHT sensor (2) then tests the performance when working optimally at a fan speed of 6000 Rpm with a temperature of 25 ° C, and getting optimal results can reduce the temperature by 5 ° C.
Universitas Negeri Yogyakarta
Title: Design of an Intelligent Cooling System for the E-Inobus Battery Box
Description:
The battery Pack is an important component used as a source of electrical energy in E-Inobus.
Therefore, an effective cooling system is required to ensure optimal conditions.
So, to maintain the performance and safety of the battery pack, a system that can control the air in the battery box is needed.
The purpose of this final project is to design a tool known as functional and performance testing.
This research uses the R&D method that refers to the ADDIE model.
The object of this research is the optimization of the cooling system in the battery box.
Data collection and testing of this tool are carried out functionally, and the performance of the tool is tested.
Testing the performance of the tool.
The result of this research is to successfully make a cooling system optimization tool that is made using a reconditioned box and cooling system optimization tool made using a reconditioned box and Wemos Mega 2560 as a microcontroller, with testing and functional testing on DHT22 has an average difference of 0.
65°C.
Average difference of 0.
65 ° C on the DHT22 sensor (1) and 0.
32 ° C on the DHT sensor (2), then the performance test of the device.
DHT sensor (2) then tests the performance when working optimally at a fan speed of 6000 Rpm with a temperature of 25 ° C, and getting optimal results can reduce the temperature by 5 ° C.
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