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Automotive Experiences
Published by Universitas Muhammadiyah Magelang
ISSN : 26156202     EISSN : 26156636     DOI : 10.31603/ae
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Mechanical Engineering
Automotive experiences invite researchers to contribute ideas on the main scope of Emerging automotive technology and environmental issues; Efficiency (fuel, thermal and mechanical); Vehicle safety and driving comfort; Automotive industry and supporting materials; Vehicle maintenance and technical skills; and Transportation policies, systems, and road users behavior.
Arjuna Subject : Teknik (semua kategori) - Teknik Otomotif
Articles 262 Documents
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Synthesis of 2-Hidroxyethyl Ester (2-HEE) and 2-Hydroxypropyl Ester (2-HPE) from Castor Oil as Bioadditives to Improve the Cold Flow Characteristic of Biodiesel Yulfi Zetra; Nirmala Puteri Batari; Talitha Fitra Firdausya; Yunita Alfiyati Firdausa; Rizka Berliana Putri; R.Y. Perry Burhan; Yuly Kusumawati
Automotive Experiences Vol. 9 No. 1 (2026)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.15860

Abstract

The utilization of biodiesel continues to increase along with the development of renewable energy. However, biodiesel tends to exhibit poorer cold flow properties compared to petroleum diesel. In this study, castor oil, a non-edible vegetable oil, was modified into 2-hydroxyethyl ester (2-HEE) and 2-hydroxypropyl ester (2-HPE) to improve the cold flow characteristic of biodiesel. The transesterification of 2-HEE and 2-HPE was carried out using fatty acid methyl esters (FAME) derived from castor oil with ethylene glycol (for 2-HEE) and propylene glycol (for 2-HPE), assisted by a K₂CO₃ catalyst at 150 °C, a mixing speed at 500 rpm, under a vacuum system. The optimum molar ratio of FAME to polyol was 1:10, yielding 69.63% for 2-HEE and 56.84% for 2-HPE. GC–MS analysis showed product abundances of 98.17% for 2-HEE (dominated by 2-hydroxyethyl ricinoleate at 77.4%) and 98.97% for 2-HPE (dominated by 2-hydroxypropyl ricinoleate at 77.9%). The addition of 2% v/v 2-HEE to biodiesel reduced the cloud point by 2.2 °C, the pour point by 3 °C, the flash point by 3 °C, and the density by 0.005 g/cm³, while increasing the kinematic viscosity by 0.21 cSt. Meanwhile, the addition of 2% v/v 2-HPE reduced the cloud point by 3.1 °C, the pour point by 4.3 °C, the flash point by 8 °C, and the density by 0.001 g/cm³, with an increase in kinematic viscosity of only 0.01 cSt. The 2-HPE compound showed superior performance as a bioadditive compared to 2-HEE in improving the cold flow characteristic of biodiesel without significantly altering its physical properties.
Activated Carbon as a Functional and Sustainable Filler in Composite Bipolar Plates For Fuel Cell Applications Iswandi; Suherman; Tino Hermanto; Yopan Rahmad Aldori; Muhammad Idris; Abu Bakar Sulong
Automotive Experiences Vol. 9 No. 1 (2026)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.16009

Abstract

Bipolar plate is a key component that determines a fuel cell's performance and service life. Carbon-based polymer composite materials were developed as lightweight, easy-to-process alternatives to metal. The use of carbon-based fillers in polymer composites has grown rapidly as an alternative to bipolar plate materials in fuel cell applications, especially to meet performance targets set by the U.S. Department of Energy (DOE). DOE requires high electrical conductivity (≥100 S/cm in the in-plane direction and ≥10 S/cm in the through-plane direction), low density, adequate mechanical strength, and good corrosion resistance and chemical stability. Recent studies have shown that the addition of carbon fillers, such as graphite, carbon black, graphene, and activated carbon (AC), can increase electrical conductivity by forming conductive percolation networks in polymer matrices. This study evaluates the potential of AC from household waste in the form of coconut shells as fillers in polypropylene (PP) composites for bipolar plate applications. AC is synthesized through carbonization and activation processes, then mixed into a PP matrix with PP/AC compositions of 100/0, 90/10, 80/20, and 70/30 percent by weight. The focus of the study is the effect of composition variation on density and bending strength. The test results show that increasing the AC fraction tends to decrease the composite density. The maximum density was obtained at a 90/10 (by weight) PP/AC composition of 0.9 g/cm³, indicating more effective filling of the pore matrix by AC particles. On the other hand, bending strength shows a downward trend. The maximum flexural strength is achieved at an AC composition of 34.58 MPa at 10% weight, indicating optimal dispersion and stress transfer between the matrix and the filler. The addition of AC above the composition causes a decrease in bending strength due to potential particle agglomeration, cavities, and the limited mobility of polymer chains. Electrical conductivity tends to increase with the addition of AC due to the formation of a network of electrical currents between carbon particles within cavities, reaching a maximum of 5 S/cm at 30% by weight of AC. The electrical conductivity obtained showed better improvement than several research results on polymeric materials using the hot-press method, with a value of 1.7 S/cm, using graphite filler materials up to 60% by weight. These findings confirm that AC from coconut shells has the potential to serve as a sustainable filler for fuel cell bipolar plates, with an optimal composition that balances density and mechanical properties.
Experimental Assessment of Performance, Emissions, and Short-Term Wear of a Heavy-Duty Diesel Engine Fueled with High-Blending FAME and HVO (B40–B70) Catur Hardiyanto; Supriyono; Nur Aklis
Automotive Experiences Vol. 9 No. 1 (2026)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.16033

Abstract

High-blend biodiesel and renewable diesel are increasingly recognized as viable drop-in fuels for heavy-duty diesel engines to meet stringent emission reduction targets. This study experimentally investigates the effects of conventional diesel (B0), diesel–FAME blends (B40F–B70F), and diesel–HVO blends (B40H–B70H) on engine performance, exhaust emissions, and short-term wear characteristics. Tests were conducted on a production heavy-duty Komatsu SAA12V140E-3 engine under controlled operating conditions over a wide range of engine speeds. Engine performance was evaluated in terms of brake torque, brake power, brake thermal efficiency, and brake-specific fuel consumption, while emissions of CO, NOx, O₂, and CO₂ were measured. The results show that increasing the FAME blending ratio leads to noticeable performance deterioration. At higher blend levels (B60F–B70F), brake power and thermal efficiency decrease by approximately 5–10%, whereas fuel consumption increases by 12–25% relative to B0, primarily due to the lower heating value and higher viscosity of FAME. In contrast, diesel–HVO blends exhibit performance comparable to conventional diesel, with reductions in power and efficiency generally below 5%. All biofuel blends reduce CO emissions by approximately 8–20%; however, FAME blends show a more pronounced increase in NOx emissions at higher blending ratios, whereas HVO blends provide a more balanced emission profile. Wear metal concentrations in used lubricating oil remain below critical limits for all tested fuels. Overall, the results indicate that HVO offers superior compatibility as a high-blend renewable fuel for heavy-duty diesel engines, achieving favorable performance–emission trade-offs without requiring engine hardware modifications.
Addressing National Needs: Design Thinking-Driven Engineering of a Multi-Purpose Logistics Vehicle for Indonesia's Free Nutritious Meals (MBG) Program Indra Candra Setiawan; Muji Setiyo; Muhammad Latifur Rochman
Automotive Experiences Vol. 9 No. 1 (2026)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.16146

Abstract

Indonesia's Free Nutritious Meals Program (MBG), launched in January 2025, aims to deliver daily meals to up to 80 million beneficiaries but faces persistent logistical challenges related to geographic dispersion, vehicle limitations, and food safety risks. Conventional delivery vehicles are often incompatible with Indonesia's diverse terrain, resulting in inefficiencies, food spoilage, and service delays. Therefore, this article advances an evidence-based design argument that positions Design Thinking, augmented by Kansei Engineering principles, as a practical design logic for addressing these nationally significant challenges through real-world vehicle adaptation. Grounded in stakeholder engagement, field observation, and iterative prototyping, a Toyota GUN125-based multi-purpose logistics vehicle was developed to support end-to-end MBG meal distribution. Key design interventions include a reconfigurable rear cabin with a three-way door system, a dedicated food trolley, reinforced suspension, and ergonomically optimized loading and unloading mechanisms. These features were derived from operational pain points and translated into engineering solutions through an iterative Design Thinking process. Field validation along a 25 km distribution route provides empirical support for the proposed design. Performance evidence indicates 98.7% operational uptime, zero thermal breaches, food waste reduced to 2% from a 28% baseline, and a 42% reduction in delivery cycle time from 5.5 hours to 3.2 hours. The vehicle configuration supports a distribution capacity of up to 612 meals per school and achieved Kansei post-test scores averaging 4.6 out of 5 for reliability and user-friendliness. The integrated evidence demonstrates how user-centered automotive engineering, grounded in operational realities, can enhance public service logistics performance. The proposed vehicle concept offers a scalable and locally adaptable platform aligned with MBG objectives and provides a transferable design perspective for other perishable goods distribution systems.
Effect of Anti-lock Braking System Modulation Frequency on Flywheel-Based Energy Harvesting During Panic Braking Agung Prijo Budijono; I Nyoman Sutantra; Agus Sigit Pramono; Aris Purwanto; Po-Hung Lin
Automotive Experiences Vol. 9 No. 1 (2026)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.16210

Abstract

A considerable portion of braking energy in electric vehicles is dissipated as heat, especially during severe or panic braking. This study experimentally investigates the effect of anti-lock braking system (ABS) modulation frequency on flywheel-based energy harvesting during panic braking using a laboratory-scale Flywheel Regenerative Capture System (FRCS). The proposed setup integrates an ABS braking unit, a magnetic clutch, a flywheel, and an electrical generator to recover part of the braking energy while maintaining braking stability. Experiments were conducted at ABS modulation frequencies of 10, 20, 30, 40, and 50 Hz. Braking performance was evaluated using wheel-speed response, slip ratio, braking time, braking distance, flywheel rotational response, and generated electrical power. At an initial braking speed of 1000 rpm, the ABS braking process operated within a slip-ratio range of approximately 0.17–0.38, while the shortest braking distance under regenerative braking reached about 15.83 m at 40 Hz, compared with about 19.58 m at 10 Hz without regenerative braking. The 10 Hz setting produced the most stable deceleration pattern, the highest flywheel rotational response, and the highest electrical output, whereas higher frequencies increased fluctuation and reduced effective torque transfer to the generator. These findings indicate that ABS modulation frequency strongly influences both braking stability and flywheel-based energy harvesting performance. The study demonstrates the feasibility of integrating a flywheel regenerative capture system with ABS-controlled panic braking, providing a basis for further vehicle-scale development.
A Comprehensive Review of Red-Light Violation warnings and Green Light Optimal-Speed Advisory Systems in V2X-Enabled CAVs Santhosh Krishnan Venkata; Sandesh Raghupathyrao Sreesha
Automotive Experiences Vol. 9 No. 2 (2026): Issue in Progress
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.14868

Abstract

The advancement of connected autonomous vehicle (CAV) technologies has significantly accelerated the development and deployment of vehicle-to-everything (V2X) communication systems, which are essential for enhancing traffic connectivity and safety. Among the prominent applications, red-light violation warning (RLVW) and green light optimal speed advisory (GLOSA) systems have emerged as key innovations, drawing interdisciplinary interest from computer science, intelligent transport systems (ITS), civil engineering, and electronics. The RLVW system uses CAV capabilities to monitor and analyse driver braking behavior in response to traffic signal changes, aiming to reduce red-light violations and improve intersection safety. In contrast, the GLOSA system offers speed recommendations and estimates time to the next green signal, thereby contributing to reduced fuel consumption, lower CO₂ emissions, and enhanced driving efficiency. Both systems rely on signal phase and timing (SPaT) and map data message (MAP) protocols to transmit real-time traffic signal information and intersection geometry from roadside units (RSUs) to on-board units (OBUs). This paper presents a comprehensive review of the operational principles, benefits, and limitations of RLVW and GLOSA systems and identifies key research gaps that warrant further investigation to support the future evolution of V2X-enabled traffic management solutions.
Effect of Curvature on the Thermal-Hydraulic Performance of Serpentine Battery Cooling Channels Teguh Hady Ariwibowo; Lucky Pradigta Setiya Raharja; Satworo Adiwidodo; Fengky Adie Perdana; Nila Alia; Burniadi Moballa; Muh. Anis Mustaghfirin; Arya Rafi Abrari; Muhammad Aghist Fitrony; Charitsma Tsani; Probo Yekti Salsabilla Adelwise; Putri Dwi Imandini
Automotive Experiences Vol. 9 No. 2 (2026): Issue in Progress
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.15222

Abstract

Efficient battery thermal management systems (BTMS) are essential for ensuring the safety and performance of lithium-ion batteries in electric vehicles. This study numerically investigates the influence of serpentine channel curvature on the thermal and hydraulic characteristics of a liquid-cooled prismatic battery module. Four channel designs were evaluated: a base case and three serpentine configurations with curvature values of 0.075 mm⁻¹, 0.1 mm⁻¹, and 0.15 mm⁻¹. Simulations were conducted under steady-state and transient conditions with discharge rates of 0.5C–2C and mass flow rates of 2.41 × 10⁻³ – 3.61 × 10⁻² kg/s. The results show that higher curvature and mass flow rates reduce maximum battery temperature and improve temperature uniformity, but at the expense of increased pressure drop and pumping power. At 3.61 × 10⁻² kg/s, the base-case channel exhibited a 28% increase in pressure drop compared to 2.41 × 10⁻² kg/s, while the 0.15 mm⁻¹ channel recorded up to a 60% rise under the same condition. Transient analysis revealed that curved channels enhanced heat dissipation, achieving up to 8.56% higher cooling performance than the base case. These findings highlight the trade-off between thermal improvement and hydraulic penalty, providing valuable guidance for optimizing liquid-cooled BTMS in electric vehicle applications.
Simulation of a Multi-Source Hybrid Electric Vehicle Integrating Battery, Fuel Cell, Photovoltaic, and Compressed-Air Systems Zeedan Taha; Kadir Aydin
Automotive Experiences Vol. 9 No. 2 (2026): Issue in Progress
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.15654

Abstract

This paper presents a simulation-based system-level evaluation of a four-source hybrid electric vehicle integrating a LiFePO4 battery, a PEMFC, a VIPV, and a compressed-air energy storage subsystem. A detailed MATLAB/Simulink model is developed using a common DC-bus architecture and four independent in-wheel hub motors with a total rated power of 12 kW. A rule-based energy management system is used to control how power is shared among different sources, maintain the battery's charge, and regulate the DC-bus voltage. The vehicle's performance is evaluated using the WLTP Class 2 driving cycle, and seven hybrid configurations are systematically compared under the same operating conditions. Simulation results confirm accurate tracking of the reference velocity profile and stable DC-bus regulation at 225 ± 3 V across all configurations. The measured specific energy consumption is approximately 5.05 kWh/100 km, including regenerative braking. Energy flow analysis shows that the battery provides short bursts of power and recovers energy from braking. In contrast, the fuel cell offers a consistent power source, which is especially useful for long-distance travel. With a 50 L hydrogen tank at 350 bar, the fuel cell extends the estimated driving range from about 95 km in battery-only operation to approximately 513 km. The integration of VIPV and compressed-air subsystems provides additional auxiliary contributions, increasing the total achievable range to roughly 606 km under full battery utilization, while improving current smoothing and transient load support. Parametric assessment of hydrogen and compressed-air storage systems reveals that hydrogen storage capacity is the principal determinant of operational duration, while compressed air provides only a modest increase in range, though it is useful for short-term support. These findings validate the technical viability of four-source hybridization and elucidate the complementary functions of electrochemical, photovoltaic, and pneumatic energy sources within a practical multi-motor vehicle framework.
Optimized Flux-Weakening Strategy in Field-Oriented Control for High-Speed IPMSM Drives Ho Minh Khoa Le; Thanh Phuc Le
Automotive Experiences Vol. 9 No. 2 (2026): Issue in Progress
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.16198

Abstract

Unlocking the dynamic performance of electric vehicles is often limited by the voltage constraints of the battery system. This study proposes an optimized control strategy for Interior Permanent Magnet Synchronous Motors based on an analytical formulation of direct-axis current trajectories to maximize speed extension while maintaining torque smoothness under strict battery voltage constraints, utilizing parameters characteristic of commercial C-segment electric vehicles (e.g., VinFast VF e34). Through a comprehensive simulation framework, the research investigates a coordinated Field-Oriented Control scheme integrated with a Flux-Weakening strategy through direct-axis current adjustment to reconcile the conflict between high-speed operation (up to 6 times the base speed of 100 rad/s) and power quality. The analysis identifies a critical operating point at a direct-axis current of -25 A, which effectively prevents voltage saturation while maintaining torque smoothness. The results demonstrate that, when evaluated against the baseline Field-Oriented Control without flux-weakening at 600 rad/s, this specific trajectory significantly reduces torque ripple by 8.6 Nm and suppresses Total Harmonic Distortion to a negligible 0.19%. This combined mitigation contributes to the high-speed operating capability by preventing system oscillations and preserving linear voltage modulation at this upper speed limit. These findings provide a validated guideline for enhancing powertrain stability and mechanical lifespan in modern electric mobility.
Hybrid Statistical and ANN-Based Prediction of Lithium-Ion Battery Degradation under UDDS-Based Simulated Urban Driving Profiles Muhannad M. Mrah; Luttfi A. Al-Haddad; Taymoor Husham Nussrat; Ahmed Ali Farhan Ogaili; Hala Husham Nussrat; Mustafa I. Al-Karkhi
Automotive Experiences Vol. 9 No. 2 (2026): Issue in Progress
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.16287

Abstract

The research will enhance the forecasting of the lithium-ion battery degradation to facilitate more secure and sustainable energy storage in the electric vehicle. An analytical ‎framework that is hybrid in nature, incorporating both statistical analysis and artificial neural network (ANN) modeling, was developed and verified using a long time dataset of INR21700- M50T cells being cycled in realistic urban driving profiles according to the Urban Dynamometer Driving Schedule ‎(UDDS). The indicators of key degradation were first described using statistical analysis where it was found that there were strong negative relationships between capacity retention and capacity C-rate (Pearson r = -0.83) and internal resistance (r = -0.71). Based on these findings, a feedforward neural network, whose features were selected using ReliefF algorithm, was built which was used to model nonlinear aging behavior at lower input dimensionality. ANN inputs were chosen as the 2 most powerful features low-frequency impedance at 0.01 Hz and internal resistance. The resulting model had a high predictive performance of a root mean squared error (RMSE) less than 1.2% and a ‎coefficient of determination (R2) greater than 0.97 on the original data. These results underscore the fact that combining data-based feature relevance analysis with machine learning is useful in improving the accuracy of prediction as well as the interpretability of the model. The obtained results demonstrate that combining statistically supported feature relevance analysis with reduced-input ANN modeling can improve both predictive capability and model interpretability for battery degradation estimation. The proposed hybrid framework provides a computationally efficient approach for lithium-ion battery state-of-health prediction under the investigated dataset conditions and may support future development of simplified battery management system strategies.‎

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