Perancangan Sistem Tenaga dan Transmisi pada Sepeda Listrik Hubless Wheel ITS Dengan Metode Optimasi Genetic Algorithm (GA) dan Particle Swarm Optimization (PSO)

Chrisdhito, Timothy Denzel (2023) Perancangan Sistem Tenaga dan Transmisi pada Sepeda Listrik Hubless Wheel ITS Dengan Metode Optimasi Genetic Algorithm (GA) dan Particle Swarm Optimization (PSO). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kebutuhan akan kendaraan listrik yang mampu menggantikan kendaraan konvensial berbahan bakar fosil sebagai alat mobilitas semakin meningkat. Salah satu opsi kendaraan listrik masa kini adalah sepeda listrik. Sepeda listrik memiliki ukuran yang kompak serta konsumsi daya yang rendah. Peneliti tertatrik untuk mengembangkan sepeda listrik yang unik sehingga diminati oleh masyarakat sebagai salah satu alternatif kendaraan untuk mobilitas sehari-hari. Sepeda listrik yang telah dikembangkan berkonsep hubless. Hubless adalah konsep roda sepeda tanpa menggunakan as tengah sehingga tampilan roda sepeda akan terlihat menarik dan futuristik. Mekanisme roda hubless pada sepeda listrik berbeda dengan roda biasa sehingga memerlukan sistem transmisi agar sepeda dapat berjalan dengan kecepatan yang diharapkan. Dari penelitian sebelumnya diperoleh aplikasi penggunaan optimasi yang dijadikan referensi dalam proses penyusunan penelitian ini. Tahap pertama adalah menganalisis gaya hambat yang terjadi pada kendaraan diantaranya drag force, dan rolling resistance, selanjutnya mencari spesifikasi dari motor dan baterai yang digunakan kendaraan serta yang terakhir adalah menentukan pemilihan gear yang memiliki massa dan jarak seminim mungkin menggunakan optimasi Genetic Algorithm (GA) dan Particle Swarm Optimization (PSO). Hasil dari penilitian ini diperoleh bahwa sepeda hubless wheel ITS memiliki kecepatan maksimum 20 km/ jam dan jarak tempuh sebesar 20 km. Kecepatan maksimum tersebut dapat diraih dengan menggunakan sistem transmisi dengan rasio sebesar 1:2. Dengan menggunakan metode optimasi Genetic Algorithm (GA) dan Particle Swarm Optimization (PSO) didapatkan bahwa pilihan gear yang terbaik memiliki spesikasi N pinion, Ngear, ketebalan, dan module sebagai berikut, 18; 36; 34,388 mm dan 2 mm. Optimasi Genetic Algorithm (GA) dan Particle Swarm Optimization (PSO) menghasilkan nilai fitness sebesar 0,6858. Nilai fitness tersebut mewakili bobot dan jarak minimum gear sebesar 1,6493 kg dan 54 mm.
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The need for electric vehicles that can replace conventional fossil fuel vehicles as a means of mobility is increasing. One of today's electric vehicle options is an electric bicycle. Electric bicycles have a compact size and low power consumption. Researchers are interested in developing unique electric bicycles so that they are in demand by the public as an alternative vehicle for everyday mobility. The electric bicycle that will be developed has a hubless concept. Hubless is the concept of bicycle wheels without using a central axle so that the appearance of bicycle wheels will look attractive and futuristic. The hubless wheel mechanism on electric bicycles is different from ordinary wheels, so it requires a transmission system so that the bicycle can run at the expected speed. From previous research, it was obtained that the application of optimization used was used as a reference in the process of compiling this research. The first stage is to analyze the drag force that occurs on the vehicle including drag force and rolling resistance, then look for the specifications of the motor and battery used by the vehicle and the last is to determine the selection of gear that has the minimum mass and distance using Genetic Algorithm (GA) optimization and Particle Swarm Optimization (PSO). The results of this research showed that ITS hubless wheel bikes have a maximum speed of 20 km/hour and a distance of 20 km. The maximum speed can be achieved by using a transmission system with a ratio of 1:2. By using the optimization method Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) it was found that the best choice of gear has the specifications of N pinion, Ngear, thickness, and module as follows, 18; 36; 34.388mm and 2mm. Genetic Algorithm Optimization (GA) and Particle Swarm Optimization (PSO) resulted in a fitness value of 0.6858. The fitness value represents the weight and minimum gear distance of 1.645 kg and 27 mm

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Hubless wheel, Genetic Algorithm, Particle Swarm Optimization, Sepeda Listrik, Hubless wheel, Genetic Algorithm, Particle Swarm Optimization, Electric Bicycle
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL152.8 Vehicles, Remotely piloted. Autonomous vehicles. T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL410 Bicycles and bicycling--Design and construction T Technology > TS Manufactures > TS171 Product design
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Mechanical Engineering > 21201-(S1) Undergraduate Thesis
Depositing User:	Timothy Denzel Chrisdhito
Date Deposited:	05 Aug 2023 08:37
Last Modified:	05 Aug 2023 08:37
URI:	http://repository.its.ac.id/id/eprint/102943

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