Analisis Performa dan Studi Konsumsi Energi Kendaraan Listrik Sepeda Motor Listrik SEMOLI

  • Nur Akhlis Sarihidaya Laksana Politeknik Negeri Cilacap
  • Radhi Ariawan Politeknik Negeri Cilacap
  • Bayu Aji Girawan Politeknik Negeri Cilacap
  • Akhlis Rahman Sari Nurhidayat Universitas Jendral Soedirman
Abstract views: 132 , PDF downloads: 136
Keywords: continuously variable transmission, energy consumption, electric motorbike

Abstract

In this article the author conducts research related to energy consumption studies on electric motorbike vehicles (SEMOLI) made and developed by the author. The purpose of the energy consumption study is to determine the energy consumption of electric motorbike vehicles that have been made for further improvement and development. The method used is experimentation with the first phase testing on a straight flat road for one kilometer with flat road conditions, this phase of experimental results shows an average energy consumption of 30 Wh, for an average uphill road consumption of 40 km / h and for the second phase of experimental data using experimental methods with speed parameters 30 - 35 km energy consumption has an average of 30 Wh, at speeds of 40 - 45 km / h energy consumption has an average of 28 Wh, and 50-55 km / h average energy consumption of 27 Wh. The test results show that on flat road conditions and the increasing speed, the energy consumption will decrease.

 

References

C. M. Usharani and B. A. Sujathakumari, “Routing an electric vehicle for optimum energy consumption with EE-MAODV Using NS3,” 2019 Int. Conf. Intell. Comput. Control Syst. ICCS 2019, no. Iciccs, pp. 895–901, 2019, doi: 10.1109/ICCS45141.2019.9065557.

S. El Amrani, M. Chennani, and D. Belkhayat, “Comparative Study of Electric Vehicle Energy Consumption between Trunk Roads and Highways,” Proc. 2019 7th Int. Renew. Sustain. Energy Conf. IRSEC 2019, pp. 0–6, 2019, doi: 10.1109/IRSEC48032.2019.9078169.

D. Drungilas et al., “Deep reinforcement learning based optimization of automated guided vehicle time and energy consumption in a container terminal,” Alexandria Eng. J., vol. 67, pp. 397–407, 2023, doi: 10.1016/j.aej.2022.12.057.

R. Barrero, X. Tackoen, and J. Van Mierlo, “Quasi-static simulation method for evaluation of energy consumption in hybrid light rail vehicles,” 2008 IEEE Veh. Power Propuls. Conf. VPPC 2008, 2008, doi: 10.1109/VPPC.2008.4677763.

K. Ruangjirakit, Y. Laoonual, A. Charadsuksawat, V. Kiattikomol, and S. Sridan, “A Study of Grid-to-Wheel Energy Consumption of Electric Vehicle on Real Road Tests in Bangkok,” ITEC Asia-Pacific 2018 - 2018 IEEE Transp. Electrif. Conf. Expo, Asia-Pacific E-Mobility A Journey from Now Beyond, vol. 2015, no. Eep 2015, pp. 1–5, 2018, doi: 10.1109/ITEC-AP.2018.8432596.

P. Rajan and C. V. Ravishankar, “The phase abstraction for estimating energy consumption and travel times for electric vehicle route planning,” GIS Proc. ACM Int. Symp. Adv. Geogr. Inf. Syst., pp. 556–559, 2019, doi: 10.1145/3347146.3359383.

L. Guo, H. Xu, J. Zou, H. Jie, and G. Zheng, “Torque Distribution Strategy of Four-Wheel Independent Drive Electric Vehicle Based on Optimal Energy Consumption,” 2020 IEEE 3rd Int. Conf. Electron. Technol. ICET 2020, pp. 252–256, 2020, doi: 10.1109/ICET49382.2020.9119677.

J. Wurm, M. Fitl, M. Gumpesberger, E. Väisänen, and C. Hochenauer, “Advanced heat transfer analysis of continuously variable transmissions (CVT),” Appl. Therm. Eng., vol. 114, pp. 545–553, 2017, doi: 10.1016/j.applthermaleng.2016.12.007.

F. J. Morales and F. G. Benitez, “Considerations on the operation of inertial continuous variable transmissions,” Mech. Mach. Theory, vol. 144, p. 103672, 2020, doi: 10.1016/j.mechmachtheory.2019.103672.

M. Tomaselli, P. Lino, and G. Carbone, “Modelling and efficiency formulation of a planetary traction drive CVT,” IFAC-PapersOnLine, vol. 52, no. 5, pp. 411–416, 2019, doi: 10.1016/j.ifacol.2019.09.066.

M. Gao, J. Hu, and Z. Peng, “Study on Optimization for Transmission System of Electric Drive Tracked Vehicles,” Energy Procedia, vol. 105, pp. 2971–2976, 2017, doi: 10.1016/j.egypro.2017.03.707.

C. Fiori et al., “The effect of electrified mobility on the relationship between traffic conditions and energy consumption,” Transp. Res. Part D Transp. Environ., vol. 67, pp. 275–290, 2019, doi: 10.1016/j.trd.2018.11.018.

O. Ammari, K. El Majdoub, and F. Giri, “Modeling and control of a half electric vehicle including an inverter, an in-wheel BLDC motor and Pacejka’s tire model,” IFAC-PapersOnLine, vol. 55, no. 12, pp. 604–609, 2022, doi: 10.1016/j.ifacol.2022.07.378.

R. Baz, K. El Majdoub, F. Giri, and A. Taouni, “Self-tuning fuzzy PID speed controller for quarter electric vehicle driven by In-wheel BLDC motor and Pacejka’s tire model,” IFAC-PapersOnLine, vol. 55, no. 12, pp. 598–603, 2022, doi: 10.1016/j.ifacol.2022.07.377.

S. Gupte, “Experimental analysis and feasibility study of 1400 CC diesel engine car converted into hybrid electric vehicle by using BLDC Hub Motors,” Energy Procedia, vol. 54, pp. 177–184, 2014, doi: 10.1016/j.egypro.2014.07.261.

J. Ruan, N. Zhang, and P. Walker, “Comparing of single reduction and CVT based transmissions on battery electric vehicle,” 2015 IFToMM World Congr. Proceedings, IFToMM 2015, no. October, 2015, doi: 10.6567/IFToMM.14TH.WC.OS17.010.

D. Kumpanya, S. Thaiparnat, and D. Puangdownreong, “Parameter Identification of BLDC Motor Model Via Metaheuristic Optimization Techniques,” Procedia Manuf., vol. 4, no. Iess, pp. 322–327, 2015, doi: 10.1016/j.promfg.2015.11.047.

P. Ubare, D. Ingole, and D. N. Sonawane, “Nonlinear model predictive control of BLDC motor with state estimation,” IFAC-PapersOnLine, vol. 54, no. 6, pp. 107–112, 2021, doi: 10.1016/j.ifacol.2021.08.531.

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Published
2024-01-22