Design Cooling Load on Economy Passenger Train Type K3-438 using Thermodynamic Physics


  • Diyajeng Luluk Karlina Universitas Sultan Ageng Tirtayasa, Indonesia
  • Choirul Mufit Universitas 17 Agustus 1945, Jakarta, Indonesia



Abstract— Factors that influence comfort on trains are thermal comfort factors. Thermal comfort is a thermal interaction between humans and their surroundings that satisfies the human mind. The principle of thermal comfort itself is related to the surrounding body temperature. Because if the human body temperature and the environment have a significant temperature difference, discomfort will occur. Research aims to design an effective air conditioning system to produce a better air supply so that it can overcome the problem of thermal comfort in trains. The first methodology for this research was collecting primary and secondary data. Primary data includes data on train size, construction, type of equipment, and number of passengers. While secondary data is data on design conditions. To determine the value of the cooling load, it is necessary to analyze the heat load in the train which includes sensible heat load and latent heat load. The results of this research obtained a total sensible heat value of 86371.19 Btu/hr. And the total latent heat is 73855.839 Btu/hr. Based on the results of research that has been carried out, it can be Conclusions were drawn from the calculation of the cooling load on the Type K3-438 Passenger Train with a capacity of 94 passengers. It was concluded that the minimum cooling load required was 40412.48 kcal/hr.


Keywords: Cooling Load, Thermal Comfort, Passenger Train, Thermodynamic Physics

Author Biographies

Diyajeng Luluk Karlina, Universitas Sultan Ageng Tirtayasa, Indonesia

Department of Electrical Engineering Vocational Education, Faculty of Teacher Training and Education, Universitas Sultan Ageng Tirtayasa, Serang, Indonesia

Choirul Mufit, Universitas 17 Agustus 1945, Jakarta, Indonesia

Department of Electrical Engineering, Universitas 17 Agustus 1945, Jakarta, Indonesia


Z. zhi, D. Peng, and Z. Pei, “Performance analysis and simulation of automotive air conditioning systems,” Appl. Mech. Mater., vol. 261–262, pp. 357–361, 2013, doi: 10.4028/

Q. Zhao, Z. Lian, and D. Lai, “Thermal comfort models and their developments: A review,” Energy Built Environ., vol. 2, no. 1, pp. 21–33, 2021, doi: 10.1016/j.enbenv.2020.05.007.

D. L. Karlina and K. Indriawati, “Fault Tolerant Control for Speed Sensorless of DC Motor,” Proceeding - ICoSTA 2020 2020 Int. Conf. Smart Technol. Appl. Empower. Ind. IoT by Implement. Green Technol. Sustain. Dev., 2020, doi: 10.1109/ICoSTA48221.2020.1570615272.

A. E. Ben-Nakhi and M. A. Mahmoud, “Cooling load prediction for buildings using general regression neural networks,” Energy Convers. Manag., vol. 45, no. 13–14, pp. 2127–2141, 2004, doi: 10.1016/j.enconman.2003.10.009.

S. Yasunobu, S. Miyamoto, and H. Ihara, “Fuzzy Control for Automatic Train Operation System,” IFAC Proc. Vol., vol. 16, no. 4, pp. 33–39, 1983, doi: 10.1016/s1474-6670(17)62539-4.

V. K. Venkiteswaran, J. Liman, and S. A. Alkaff, “Comparative Study of Passive Methods for Reducing Cooling Load,” Energy Procedia, vol. 142, pp. 2689–2697, 2017, doi: 10.1016/j.egypro.2017.12.212.

Y. Ding, Q. Zhang, and T. Yuan, Research on short-term and ultra-short-term cooling load prediction models for office buildings, vol. 154. Elsevier B.V., 2017. doi: 10.1016/j.enbuild.2017.08.077.

P. Howlett, “Optimal strategies for the control of a train,” Automatica, vol. 32, no. 4, pp. 519–532, 1996, doi: 10.1016/0005-1098(95)00184-0.

M. Carey and D. Lockwood, “A model, algorithms and strategy for train pathing,” J. Oper. Res. Soc., vol. 46, no. 8, pp. 988–1005, 1995, doi: 10.1057/jors.1995.136.

I. Snow, P. Track, R. Slopes, C. Worldwide, S. D. Heaters, and C. Heaters, “Thermal Comfort Thermal Comfort,” pp. 1–7, 2012.

F. Domínguez-Muñoz, J. M. Cejudo-López, and A. Carrillo-Andrés, “Uncertainty in peak cooling load calculations,” Energy Build., vol. 42, no. 7, pp. 1010–1018, 2010, doi: 10.1016/j.enbuild.2010.01.013.

W. Gang, S. Wang, F. Xiao, and D. C. Gao, “Robust optimal design of building cooling systems considering cooling load uncertainty and equipment reliability,” Appl. Energy, vol. 159, pp. 265–275, 2015, doi: 10.1016/j.apenergy.2015.08.070.

E. D. Rogdakis and G. K. Alexis, “Design and parametric investigation of an ejector in an air-conditioning system,” Appl. Therm. Eng., vol. 20, no. 2, pp. 213–226, 2000, doi: 10.1016/S1359-4311(99)00013-7.

H. M. Hashim, E. Sokolova, O. Derevianko, and D. B. Solovev, “Cooling Load Calculations,” IOP Conf. Ser. Mater. Sci. Eng., vol. 463, no. 3, 2018, doi: 10.1088/1757-899X/463/3/032030.

B. Prasartkaew and S. Kumar, “Design of a renewable energy based air-conditioning system,” Energy Build., vol. 68, no. PARTA, pp. 156–164, 2014, doi: 10.1016/j.enbuild.2013.09.001.




How to Cite

Karlina, D. L., & Mufit, C. (2024). Design Cooling Load on Economy Passenger Train Type K3-438 using Thermodynamic Physics. Andalasian International Journal of Applied Science, Engineering and Technology, 4(1), 31-36.