Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and Aerodynamics
Fuel efficiency in heavy-duty trucks in Indonesia faces significant challenges, while the current HDM-4 fuel consumption model has limitations in reflecting local conditions. This study calibrates the HDM-4 model using telematics data, engine speed modeling, aerodynamic simulations, and calibration...
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| Format: | Article |
| Language: | English |
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Universitas Muhammadiyah Magelang
2025-04-01
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| Series: | Automotive Experiences |
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| Online Access: | https://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/12862 |
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| author | Pradhana Wahyu Nariendra Melia Eka Lestiani |
| author_facet | Pradhana Wahyu Nariendra Melia Eka Lestiani |
| author_sort | Pradhana Wahyu Nariendra |
| collection | DOAJ |
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Fuel efficiency in heavy-duty trucks in Indonesia faces significant challenges, while the current HDM-4 fuel consumption model has limitations in reflecting local conditions. This study calibrates the HDM-4 model using telematics data, engine speed modeling, aerodynamic simulations, and calibration factors. The novelty lies in updating parameters such as engine speed, vehicle frontal area, and calibration factors for engine power efficiency (Kpea) and rolling resistance (Kcr2) to account for tire-road interaction in Indonesian conditions. Data were collected from 5-axle trucks on the Tanjung Priok–Bandung toll road, analyzed using regression, Computational Fluid Dynamics (CFD) simulations, and non-parametric paired tests. Results show updated engine speed parameters (RPM_a0 = 680.11, RPM_a1 = -4.9031, RPM_a2 = 0.3858, RPM_a3 = -0.0028), a drag coefficient of 1.0556, and a frontal area of 8.2 m². Calibrating Kpea and Kcr2 (both 0.6) improved prediction accuracy, with no significant difference between predicted and observed data (p = 0.186). The enhanced HDM-4 model supports operational decisions, infrastructure planning, and sustainable transport policies, improving energy efficiency, reducing emissions, and boosting national logistics competitiveness.
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| format | Article |
| id | doaj-art-623bdd0ec460498a9adf4686cd3eace9 |
| institution | OA Journals |
| issn | 2615-6202 2615-6636 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Universitas Muhammadiyah Magelang |
| record_format | Article |
| series | Automotive Experiences |
| spelling | doaj-art-623bdd0ec460498a9adf4686cd3eace92025-08-20T02:16:06ZengUniversitas Muhammadiyah MagelangAutomotive Experiences2615-62022615-66362025-04-018110.31603/ae.12862Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and AerodynamicsPradhana Wahyu Nariendra0Melia Eka Lestiani1Universitas Logistik dan Bisnis Internasional, IndonesiaUniversitas Logistik dan Bisnis Internasional, Indonesia Fuel efficiency in heavy-duty trucks in Indonesia faces significant challenges, while the current HDM-4 fuel consumption model has limitations in reflecting local conditions. This study calibrates the HDM-4 model using telematics data, engine speed modeling, aerodynamic simulations, and calibration factors. The novelty lies in updating parameters such as engine speed, vehicle frontal area, and calibration factors for engine power efficiency (Kpea) and rolling resistance (Kcr2) to account for tire-road interaction in Indonesian conditions. Data were collected from 5-axle trucks on the Tanjung Priok–Bandung toll road, analyzed using regression, Computational Fluid Dynamics (CFD) simulations, and non-parametric paired tests. Results show updated engine speed parameters (RPM_a0 = 680.11, RPM_a1 = -4.9031, RPM_a2 = 0.3858, RPM_a3 = -0.0028), a drag coefficient of 1.0556, and a frontal area of 8.2 m². Calibrating Kpea and Kcr2 (both 0.6) improved prediction accuracy, with no significant difference between predicted and observed data (p = 0.186). The enhanced HDM-4 model supports operational decisions, infrastructure planning, and sustainable transport policies, improving energy efficiency, reducing emissions, and boosting national logistics competitiveness. https://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/12862Fuel consumptionHDM-4TelematicsHeavy-duty trucksAerodynamics |
| spellingShingle | Pradhana Wahyu Nariendra Melia Eka Lestiani Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and Aerodynamics Automotive Experiences Fuel consumption HDM-4 Telematics Heavy-duty trucks Aerodynamics |
| title | Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and Aerodynamics |
| title_full | Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and Aerodynamics |
| title_fullStr | Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and Aerodynamics |
| title_full_unstemmed | Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and Aerodynamics |
| title_short | Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and Aerodynamics |
| title_sort | calibration of hdm 4 model for fuel consumption in heavy duty trucks integration of telematics engine speed and aerodynamics |
| topic | Fuel consumption HDM-4 Telematics Heavy-duty trucks Aerodynamics |
| url | https://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/12862 |
| work_keys_str_mv | AT pradhanawahyunariendra calibrationofhdm4modelforfuelconsumptioninheavydutytrucksintegrationoftelematicsenginespeedandaerodynamics AT meliaekalestiani calibrationofhdm4modelforfuelconsumptioninheavydutytrucksintegrationoftelematicsenginespeedandaerodynamics |