Putra, Alvyn Pramana Kartika (2024) Rancang Bangun Sistem Suspensi Sepeda Motor Trail Listrik 2x2 Dengan Metode Algoritma Genetik. Other thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 5007201204-Undergraduate_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5007201204-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 October 2026. Download (4MB) | Request a copy |
Abstract
Kebutuhan akan sepeda motor khususnya tipe trail yang mampu digunakan dalam segala medan dengan kontur jalan yang tidak rata semakin tinggi. Sepeda motor trail listrik dapat diandalkan sebagai alat transportasi utama untuk memasok barang – barang ke daerah terpencil yang sulit dilalui kendaraan besar karena kontur jalan yang ekstrim dan sulit untuk mendapatkan bahan bakar minyak. Performa sepeda motor trail listrik selain dari motor listriknya juga bergantung pada sistem suspensi yang dipakai oleh sepeda motor tersebut. Sistem suspensi haruslah kuat menahan beban barang hingga ratusan kilogram dalam melewati medan yang ekstrim dan tidak rata. Kekuatan dan kenyamanan suspensi berkaitan erat dengan nilai koefisien kekakuan dan redaman dari pegas suspensi. Perancangan sistem suspensi dilakukan dengan menggunakan pemodelan sistem satu kendaraan dengan 5 derajat kebebasan, dengan jenis suspensi dualshock yang disimulasikan menggunakan MATLAB Simulink dengan input jalan sinusoidal dan white gaussian noise untuk mensimulasikan jalanan yang tidak rata. Parameter yang digunakan diambil dari beberapa referensi dan pengamatan lapangan, lalu akan dilakukan perancangan menggunakan metode optimasi algoritma genetik. Hasil akhir dari metode ini adalah nilai koefisien kekakuan dan redaman suspensi depan dan belakang dengan variasi amplitudo 0.1 meter, 0.15 meter, dan 0.2 meter, dengan panjang lintasan 1.5 meter. Berdasarkan analisis dan simulasi, serta metode optimasi algoritma genetik yang telah dilakukan, didapatkan nilai koefisien kekakuan dan redaman suspensi depan sepeda motor trail listrik 2x2 ini sebesar 41109 N/m dan 1913 Ns/m, sedangkan untuk nilai koefisien kekakuan dan redaman suspensi belakang sepeda motor ini adalah 58389 N/m dan 3460 Ns/m. Berdasarkan perhitungan defleksi statis, didapat nilai defleksi untuk suspensi depan telescopic adalah sebesar 3,9 cm dan untuk suspensi belakang dualshock sebesar 6,7 cm. Berdasarkan fungsi objektif yang menunjukkan batasan dari percepatan dari bodi sepeda motor tidak lebih dari 9,8 m/s2, perpindahan pitch sepeda motor tidak lebih dari 6,28 rad/s2, maksimum defleksi suspensi depan telescopic sebesar 13,5 cm, dan maksimum defleksi suspensi belakang dualshock sebesar 15 cm, dari hasil simulasi didapat untuk tiap variasi amplitudo, dengan parameter suspensi hasil optimasi nilai perpindahan dan percepatan yang didapat telah memenuhi fungsi objektif tersebut.
==============================================================================================================================
The need for motorcycles, especially trail types that can be used in all terrains with uneven road contours, is getting higher. Electric dirt bikes can be relied upon as the main means of transportation to supply goods to remote areas that are difficult for large vehicles to pass due to extreme road contours and difficult to obtain fuel oil. The performance of an electric dirt bike apart from the electric motor also depends on the suspension system used by the motorcycle. The suspension system must be strong enough to withstand the weight of goods up to hundreds of kilograms in passing through extreme and uneven terrain. The strength and comfort of the suspension are closely related to the stiffness and damping coefficient values of the suspension springs.
The design of the suspension system is carried out using a single vehicle system modeling with 5 degrees of freedom, with a dualshock suspension type simulated using MATLAB Simulink with sinusoidal road input and white gaussian noise to simulate uneven roads. The parameters used are taken from several references and field observations, then the design will be carried out using the genetic algorithm optimization method. The final result of this method is the value of the stiffness and damping coefficients of the front and rear suspensions with amplitude variations of 0.1 meters, 0.15 meters, and 0.2 meters, with a track length of 1.5 meters.
Based on the analysis and simulation, as well as the genetic algorithm optimization method that has been carried out, the value of the stiffness and damping coefficient of the front suspension of this 2x2 electric dirt bike is 41109 N/m and 1913 Ns/m, while the value of the stiffness and damping coefficient of the rear suspension of this motorcycle is 58389 N/m and 3460 Ns/m. Based on the static deflection calculation, the deflection value for the front suspension is 3,9 cm and for the rear suspension is 6,7 cm. Based on the objective function that shows the limits of the acceleration of the motorcycle body of no more than 9.8 m/s2, the pitch displacement of the motorcycle is no more than 6.28 rad/s2, the maximum deflection of the telescopic front suspension is 13.5 cm, and the maximum deflection of the dualshock rear suspension is 15 cm, from the simulation results obtained for each amplitude variation, with the suspension parameters of the results of the optimization of the displacement and acceleration values obtained have met the objective function.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Algoritma Genetik, Dualshock, Kekakuan, Redaman, Damping, Genethic Algorithm, Stiffness |
| Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL257 Springs and suspension T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL440 Motorcycles. T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL448 Electric motorcycles |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Mechanical Engineering > 21201-(S1) Undergraduate Thesis |
| Depositing User: | Alvyn Pramana Kartika Putra |
| Date Deposited: | 12 Aug 2024 01:17 |
| Last Modified: | 28 Aug 2024 03:46 |
| URI: | http://repository.its.ac.id/id/eprint/113823 |
Actions (login required)
 |
View Item |