Rahman, Hafid (2023) Analisa Performa Sistem Kendali Cerdas Electric Power Steering (EPS) dengan Simulasi Matlab Simulink pada Mobil Plug-In Hybrid Electric Vehicle (PHEV) ITS. Diploma thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Penelitian ini bertujuan untuk mendapatkan perbandingan performa sistem kemudi manual, sistem kemudi EPS berbasis PID dan sistem kemudi cerdas EPS berbasis Back Propagation Neural Network (BPNN) Fuzzy Logic pada kendaraan mobil Plug-In Hybrid Electric Vehicle (PHEV) ITS menggunakan software Matlab Simulink. Model EPS dikembangkan menggunakan persamaan matematika, subsistem mekanik unit kemudi dimodelkan menggunakan persamaan dinamis unit kemudi. Tujuan dari sistem EPS adalah untuk memberikan bantuan torsi ke setir untuk menggerakkan kendaraan, motor akan memberikan torsi bantuan tambahan bersama dengan input dari pengemudi untuk mengarahkan kendaraan. Logika kontrol yang diterapkan mempertimbangkan input torsi dari kemudi dan kecepatan kendaraan. Untuk mengatasi masalah power steering yang nonlinier pada sistem EPS, sebuah kemajuan algoritma kontrol diperlukan untuk sistem yang lebih praktis. Pada penelitian ini akan menggunakan algoritma kontrol berdasarkan Back Propagation Neural Network – Fuzzy Logic untuk mengatur parameter PID secara otomatis sendiri (self-tuning). Dengan error yang terjadi antara arus yang diharapkan dan arus motor yang sebenarnya, Algoritma Back Propagation Neural Network –Fuzzy Logic digunakan untuk mempelajari dan mewujudkan penyesuaian parameter PID yang adaptif. BPNN dapat menangani masalah nonliner pada sistem dan dapat secara otomatis menyesuaikan parameter PID nya. Sehingga, secara efektif dapat meningkatkan kinerja sistem EPS.
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This research aims to obtain a performance comparison of the manual steering system, PID-based EPS steering system, and intelligent EPS steering system based on Back Propagation Neural Network (BPNN) Fuzzy Logic in the Plug-In Hybrid Electric Vehicle (PHEV) at ITS using Matlab Simulink software. The EPS model is developed using mathematical equations, and the mechanical subsystem of the steering unit is modeled using dynamic equations of the steering unit. The purpose of the EPS system is to provide steering torque assistance to the steering wheel to maneuver the vehicle, where the motor will provide additional assistance torque along with the input from the driver to steer the vehicle. The control logic applied takes into account the steering torque input and the vehicle speed. To overcome the nonlinear power steering issue in the EPS system, an advanced control algorithm is required for a more practical system. In this research, a control algorithm based on Back Propagation Neural Network - Fuzzy Logic will be used to automatically self-tune the PID parameters. With the error between the desired current and the actual motor current, the Back Propagation Neural Network - Fuzzy Logic algorithm is used to learn and achieve adaptive PID parameter adjustments. BPNN can handle nonlinear problems in the system and automatically adjust its PID parameters, effectively improving the performance of the EPS system.
| Item Type: | Thesis (Diploma) |
|---|---|
| Uncontrolled Keywords: | Electric Power Steering, PHEV, Back Propagation Neural Network, Matlab Simulink, PID, Fuzzy Logic, Self-tuning |
| Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T57.62 Simulation T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL221.5 Hybrid Vehicles. Hybrid cars |
| Divisions: | Faculty of Vocational > Mechanical Industrial Engineering |
| Depositing User: | Hafid Rahman |
| Date Deposited: | 11 Dec 2023 01:40 |
| Last Modified: | 11 Dec 2023 01:40 |
| URI: | http://repository.its.ac.id/id/eprint/103908 |
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