Longitudinal Train Dynamics Model for CC203/CC206 Locomotive Simulator

Hilwadi Hindersah; Arief Syaichu Rohman; Anggera Bayuwindra; Pranoto H. Rusmin; Fabiola M.T.R. Kinasih; Carmadi Machbub

doi:10.5614/j.eng.technol.sci.2024.56.3.10

Authors

Hilwadi Hindersah School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jalan Ganesa No. 10, Bandung 40132, Indonesia, Indonesia
Arief Syaichu Rohman
arief.rohman@itb.ac.id
School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jalan Ganesa No. 10, Bandung 40132, Indonesia, Indonesia
Anggera Bayuwindra School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jalan Ganesa No. 10, Bandung 40132, Indonesia, Indonesia
Pranoto H. Rusmin School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jalan Ganesa No. 10, Bandung 40132, Indonesia, Indonesia
Fabiola M.T.R. Kinasih School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jalan Ganesa No. 10, Bandung 40132, Indonesia, Indonesia
Carmadi Machbub Institut Teknologi Sains Bandung, Jalan Ganesha Boulevard LOT A1 CBD Kota Deltamas Tol Jakarta-Cikampek KM 37, Cikarang Pusat, Kabupaten Bekasi, Indonesia, Indonesia

Vol. 56 No. 3 (2024)

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Published June 30, 2024

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This paper presents train modeling used in a simulator platform for driver training. It was developed for the CC203/CC204 locomotive. The driver will gain experience as in a real locomotive from the perceived platform movements if the movements match real conditions as accurately as possible, including the distance travelled. To this aim, a longitudinal model of the train was developed based on measurement data obtained from the Argo Parahyangan train traveling from Bandung to Jakarta. A second-order linear time invariant model was obtained by a black box identification approach, in which the input and the output of the model are the resultant force (a traction and a slope-friction force) and the train’s position, respectively. While the speed is directly obtained from measurement data, the traction force of the locomotive is predicted using the traction characteristic of the locomotive, train’s measured speed, and latitude time history during a train trip. The model is then validated by running a simulation for one complete trip of the train. In the simulation, the same input as in the model identification is applied and the mileage obtained from simulation result is compared to data of the real train trip with a fitness level of 94.09%.

Hindersah, H., Rohman, A. S., Bayuwindra, A., Rusmin, P. H., Kinasih, F. M., & Machbub, C. (2024). Longitudinal Train Dynamics Model for CC203/CC206 Locomotive Simulator. Journal of Engineering and Technological Sciences, 56(3), 425–438. https://doi.org/10.5614/j.eng.technol.sci.2024.56.3.10

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