Analisis Tegangan Output Alternator Pada Variasi Beban Listrik Engine Diesel 4V21 Euro 4
DOI:
https://doi.org/10.30588/jeemm.v10i1.2683Keywords:
alternator output voltage, electrical load variation, electrical systemAbstract
The stability of alternator output voltage is important for maintaining modern diesel vehicle electrical systems, because additional loads such as headlights, cabin cooling, and audio systems can increase current demand and affect charging voltage. This study aims to analyze alternator output voltage under variations of electrical load on a vehicle with a 4V21 Euro 4 diesel engine. A field experiment was conducted on a vehicle with a 24-volt electrical system and the engine operating at idle speed. Data were collected using a scanner under three load conditions: no load at 0 W, medium load at 150 W, and full load with a reference power of 1,110 W. Each condition was tested five times, with a data collection duration of 20 minutes per test, conducted once per day for five days. The main parameter observed was alternator output voltage, while engine RPM and coolant temperature were recorded as supporting data. The results showed that the average alternator output voltage was 28.3 V under no-load conditions, 27.8 V under medium-load conditions, and 27.7 V under full-load conditions. The total voltage drop from no load to full load was 0.6 V. Engine RPM remained at an average of 651 rpm, and coolant temperature remained at 83.1°C. These results indicate that increasing electrical load reduces alternator output voltage; however, the decrease was relatively small, and the lowest voltage still met the operating range of the 24-volt charging system, indicating that the charging system operated properly under the tested load variations.
References
Bedretchuk, J. P., Arribas García, S., Nogiri Igarashi, T., Canal, R., Wedderhoff Spengler, A., & Gracioli, G. (2023). Low-cost data acquisition system for automotive electronic control units. Sensors, 23(4), 2319. https://doi.org/10.3390/s23042319
Conradt, R., Schröer, P., Dazer, M., Wirth, J., Jöris, F., Schulte, D., & Birke, K. P. (2023). Comprehensive study of failure mechanisms of field-aged automotive lead batteries. Batteries, 9(11), 553. https://doi.org/10.3390/batteries9110553
Delco Remy International Inc. (1998). 21-SI Heavy Duty Brush Alternator Service Manual. Anderson, IN: Delco Remy International Inc.
Ginting, M., Arrayan, M., Ramadhan, A., Denis, D., & Setiawan, I. (2024). Perancangan dan analisis pengujian efektivitas sistem monitoring tegangan pada battery management system dengan baterai lithium iron phosphate pada purwarupa mobil listrik. Transient: Jurnal Ilmiah Teknik Elektro, 13(2), 65–74. https://doi.org/10.14710/transient.v13i2.65-74
Kökden, D., Egi, A., Bulut, E., Albak, E. İ., Korkmaz, İ., & Öztürk, F. (2024). Prevention of the fracture problem occurring in automotive alternator heatsink blocks using artificial intelligence. Applied Sciences, 14(24), 11758. https://doi.org/10.3390/app142411758
Kortenbruck, G., Jakubczyk, L., & Nowak, D. F. (2023). Voltage signals measured directly at the battery and via on-board diagnostics: A comparison. Vehicles, 5(2), 637-655. https://doi.org/10.3390/vehicles5020035
Kumar, R., & Jain, A. (2023). Driving behavior analysis and classification by vehicle OBD data using machine learning. The Journal of Supercomputing, 79, 18800–18819. https://doi.org/10.1007/s11227-023-05364-3
Lakatos, I. (2025). Economic and ecological aspects of vehicle diagnostics. Sustainability, 17(4), 1662. https://doi.org/10.3390/su17041662
Liao, C.-J., & Juang, C.-F. (2025). Automatic voltage regulation of vehicle alternators using a fuzzy neural network regulator. International Journal of Fuzzy Systems, 27(7), 2377–2391. https://doi.org/10.1007/s40815-025-02019-8
Mahmood, O. T., Wan Hasan, W. Z., Ismail, L. I., Shafie, S., Azis, N., & Norsahperi, N. M. H. (2022). Optimization approaches and techniques for automotive alternators: Review study. Machines, 10(6), 478. https://doi.org/10.3390/machines10060478
Michailidis, E. T., Panagiotopoulou, A., & Papadakis, A. (2025). A review of OBD-II-based machine learning applications for sustainable, efficient, secure, and safe vehicle driving. Sensors, 25(13), 4057. https://doi.org/10.3390/s25134057
Murari, T. B., Costa, R. C. da, Pereira, H. B. de B., Monteiro, R. L. S., & Moret, M. A. (2025). Early detection of failing lead-acid automotive batteries using the detrended cross-correlation analysis coefficient. Applied System Innovation, 8(2), 29. https://doi.org/10.3390/asi8020029
Ramai, C., Ramnarine, V., Ramharack, S., Bahadoorsingh, S., & Sharma, C. (2022). Framework for building low-cost OBD-II data-logging systems for battery electric vehicles. Vehicles, 4(4), 1209–1222. https://doi.org/10.3390/vehicles4040064
Soeiro, L. G. G., & Filho, B. J. C. (2023). Vehicle power system modeling and integration in hardware-in-the-loop (HIL) simulations. Machines, 11(6), 605. https://doi.org/10.3390/machines11060605
Tan, Ö., Jerouschek, D., Kennel, R., & Taskiran, A. (2022). Energy management strategy in 12-volt electrical system based on deep reinforcement learning. Vehicles, 4(2), 621–638. https://doi.org/10.3390/vehicles4020036
Yen, M.-H., Tian, S.-L., Lin, Y.-T., Yang, C.-W., & Chen, C.-C. (2021). Combining a universal OBD-II module with deep learning to develop an eco-driving analysis system. Applied Sciences, 11(10), 4481. https://doi.org/10.3390/app11104481
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