Thonthowi, Ahmad (2014) Pengaturan Kecepatan Pada Parallel Hybrid Electric Vehicle Menggunakan Self Tuning Proportional Integral Derivative Berdasarkan Genetic Algorithm. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Hybrid Electric Vehicle (HEV’s) adalah kendaraan yang menggabungkan tenaga mesin pembakaran dalam (ICE) dan motor listrik yang menggunakan energi yang tersimpan dalam baterai. HEVs memberikan manfaat ekonomi bahan bakar yang tinggi dan emisi yang rendah bila dibandingkan dengan kendaraan konvensional. Dengan tipe ini, daya yang dihasilkan menjadi lebih besar untuk mempertahankan kecepatan kendaraan yang disebut masalah regulator, sehingga HEV dianggap lebih baik daripada mesin konvensional yang menggunakan ICE saja. Dalam Tugas Akhir ini, Algoritma Genetika digunakan dalam kontroler Proportional - Integral - Derivatif untuk pengaturan kecepatan yang akan dilakukan pada simulator Paralel Hybrid Electric Vehicle ( PHEV ) . Dengan menggunakan optimasi algoritma genetika pada kontroler PID diharapkan bisa mendapatkan parameter Kp, Ki dan Kd yang optimal serta penggunaan rem mekanik tidak memberikan efek pengurangan kecepatan HEV sehingga dapat mencapai kecepatan yang diinginkan. Dengan metode kontrol ini sinyal kesalahan dapat dikurangi menjadi 98,8 % pada beban yang berlebih pada kisaran 20-60 VDC beban nominal elektromagnetik rem. Kesalahan steady state yang dihasilkan relatif kecil sekitar 2,2 % .
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Hybrid electric vehicles (HEVs) are powered by an internal combustion engine (ICE) and an electric motor that uses energy stored in a battery. HEVs combine the benefits of high fuel economy and low emissions with the power and range of conventional vehicles. With this type, the power could generated larger to maintain the speed of the charging of the vehicle called the regulator problem so that the HEV is considered better than conventional engines that use ICE only. In this thesis, Genetic Algorithm is used in the controller Proportional - Integral - Derivative for the speed setting that will be implemented in the simulator Parallel Hybrid Electric Vehicle (PHEV). By using genetic algorithm optimization of PID controller is expected to get the parameters Kp, Ki and Kd are optimal as well as the imposition of a mechanical brake does not give effect to such reduction in speed on HEV and can achieve the desired speed. With this control method the error signal can be reduced to 98.8 % at excessive load in the range of 20-60 VDC of nominal load electromagnetic brake so that the desired speed is maintained because of DC motors. Error steady state of implementation is relatively small of 2.2%
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Hybrid Electric Vehicle, Proportional Integral Derivative, Genetic Algorithm, Internal Combustion Engine, Motor Listrik. Hybrid Electric Vehicle, Genetic Algorithm, Proportional Integral Derivative, Internal Combustion Engine, Electric Motor |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5102.5 Modulation (Electronics), Demodulation (Electronics) |
| Divisions: | Faculty of Electrical Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Eko Sulistiono |
| Date Deposited: | 22 Sep 2025 06:42 |
| Last Modified: | 22 Sep 2025 06:42 |
| URI: | http://repository.its.ac.id/id/eprint/128343 |
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