Emireswara, Naufal (2026) Optimasi Parameter Fungsi Kekakuan Dan Koefisien Redaman Pada Suspensi Progresif Sepeda Motor Listrik Kupprum Nomad Dengan Metode Genetic Algorithm Berdasarkan Standar Kenyamanan ISO 2631. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Penelitian ini membahas optimasi parameter fungsi kekakuan dan koefisien redaman pada sistem suspensi progresif sepeda motor listrik Kupprum Nomad menggunakan metode Genetic Algorithm berdasarkan standar kenyamanan ISO 2631. Berbeda dengan suspensi linear yang memiliki nilai kekakuan tetap, suspensi progresif memiliki nilai kekakuan yang berubah terhadap defleksi suspensi. Oleh karena itu, sistem suspensi pada penelitian ini dimodelkan sebagai sistem nonlinear dengan fungsi kekakuan k(δ)=k_0+αδ. Model kendaraan yang digunakan adalah model full body sepeda motor dengan variasi tanpa penumpang dan dengan penumpang. Respon dinamis yang dianalisis meliputi percepatan pengendara, percepatan penumpang, perpindahan body, serta gerak pitching kendaraan. Input jalan yang digunakan berupa permukaan tidak rata ISO 8608 kelas C, bump kecil, dan bump besar pada variasi kecepatan 40 km/jam, 50 km/jam, dan 60 km/jam. Optimasi dilakukan untuk memperoleh parameter kekakuan awal, koefisien progresivitas, dan redaman suspensi depan serta belakang yang mampu meminimalkan nilai RMS percepatan vertikal pengendara. Hasil penelitian diharapkan mampu menghasilkan konfigurasi suspensi progresif yang lebih optimal dibandingkan suspensi existing, sehingga dapat meningkatkan kenyamanan berkendara berdasarkan klasifikasi ISO 2631.
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This study discusses the optimization of stiffness function parameters and damping coefficients for the progressive suspension system of the Kupprum Nomad electric motorcycle using the Genetic Algorithm method based on the ISO 2631 comfort standard. Unlike linear suspensions, which have a fixed stiffness value, progressive suspensions have a stiffness value that changes with suspension deflection. Therefore, the suspension system in this study is modeled as a nonlinear system with a stiffness function k(δ)=k_0+aδ.
The vehicle model used is a full-body motorcycle with passenger and unoccupied variations. The dynamic responses analyzed include rider acceleration, passenger acceleration, body displacement, and vehicle pitching. The road inputs used were ISO 8608 Class C uneven surfaces, small bumps, and large bumps at speeds of 40 km/h, 50 km/h, and 60 km/h. Optimization was performed to obtain initial stiffness parameters, progressiveness coefficients, and front and rear suspension damping that minimize the RMS value of the rider's vertical acceleration. The research results are expected to be able to produce a more optimal progressive suspension configuration compared to the existing suspension, so that it can improve driving comfort based on the ISO 2631 classification
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