Automotive Experiences

Research Trends of Electric Vehicles (EVs) in Indonesia, Malaysia, and Thailand: A Quick Analysis using Bibliometric

Muji Setiyo — 2025-01-15

The electric vehicles (EVs) market in ASEAN has seen rapid growth in 2024, driven by the global trend towards sustainable transportation and strong government support. Thailand, with strong government policies and extensive charging infrastructure, has emerged as a regional leader. Malaysia and Indonesia are still in the early stages of adoption, grappling with high vehicle costs, limited charging infrastructure, and public acceptance challenges. A bibliometric analysis of research output from 2015–2025 reveals an exponential growth trend in EV-related studies, with Malaysian universities leading the research focus. Despite differences in progress, Indonesia, Malaysia, and Thailand face similar challenges, including limited infrastructure, high cost of ownership, and the need for greater public awareness. Tailored policies, infrastructure improvements, and regional collaboration are critical for ASEAN countries to realize their potential as key players in the global EV transition.

Synthesis of Acetylene Black and Polyvinylidene Difluoride to Improve the Conductivity of Li-ion Nickel Manganese Cobalt Batteries

Totok Dermawan — 2025-01-18

The issue of low cathode conductivity is a significant challenge in battery development, particularly for automotive applications. The cathode plays a crucial role in Li-ion batteries, as it is responsible for transferring lithium ions during both charging and discharging processes. Therefore, this study aims to enhance the conductivity of the cathode by incorporating Acetylene Black (AB) and Polyvinylidene Difluoride (PVDF) additives. In this study, Nickel Manganese Cobalt (NMC) 811 and NMC 111 cathodes were used. These materials were formed into pellets, then made into sheets, with AB and PVDF additives added in a weight composition ratio of 85:10:5, and a coating thickness of 300 µm. The cathode conductivity was characterized using an LCR meter, while surface morphology, cross-section, EDS, and mapping of the cathode surface were analyzed with SEM. The results showed that the addition of additives increased the conductivity of NMC 111 by more than five times, from 23.27x10^-8 S.cm^-1 to 119.34x10^-8 S.cm^-1, and NMC 811 by more than twelve times, from 6.43x10^-8 S.cm^-1 to 81.79x10^-8 S.cm^-1. These findings suggest that higher particle density, improved size distribution, and smaller particle grains contribute to higher conductivity.

Predictive Performance of Anti-Lock Braking System with PID Controller Optimized by Gravitational Search Algorithm for a Quarter Car Model: Simulation Modeling and Control

Mohd Sabirin Rahmat — 2025-03-08

Anti-lock Braking Systems (ABS) are critical safety components in the passenger vehicles. The ABS prevents wheel lock-up during braking and maintains vehicle control. However, conventional braking systems have produced limitations in stopping distance and slip ratio, especially on varying road surfaces. This research addresses these issues by developing an ABS model using a quarter-car framework incorporated with a PID controller optimized by using Gravitational Search Algorithm (GSA). In this study, the mathematical equation of a quarter-car brake model is derived to represent a conventional braking system to provide a basis system for analyzing its performance. Next, a Simulink model is developed in MATLAB to simulate the conventional braking system. To develop an ABS model, a PID controller is developed. The PID parameters are tuned manually using a trial-and-error approach to provide a baseline for comparison. Subsequently, GSA is applied to optimize the PID controller parameters to improve stopping distance and maintain optimal slip ratios. The ABS performance is evaluated by analyzing performance criteria including stopping distance, slip ratio, vehicle speed, and wheel speed. Comparative analysis indicated significant improvements in braking performance against the conventional system. The ABS with PID controller optimized by GSA reduced stopping distances, better slip ratio control, and improved vehicle stability during braking. The expected finding of the proposed ABS with PID optimized by GSA offers considerable advancements in automotive braking technology. These results underscore the potential for real-world applications in enhancing vehicle safety systems, contributing to safer and more reliable passenger vehicle braking performance.

Modeling the Dynamics of a Passenger Car Using Experimental Data on Nonlinear Passive Shock Absorbers

Avicenna An-Nizhami — 2025-03-09

This study explores the dynamic response of passenger cars equipped with nonlinear passive shock absorbers, emphasizing the nonlinear damping characteristics over traditional linear models in simulating real-world driving conditions. To capture the nonlinear damping behavior, experimental data from a shock absorber testing apparatus was utilized to derive an empirical formula. The damping force was modeled using a seventh-order polynomial equation, accurately representing the force-velocity relationship. This nonlinear damping model was integrated into a half-car suspension model, which was subjected to simulations involving two road profiles: a bump and an irregular sinusoidal road profile. Simulations demonstrated that the nonlinear model outperformed its linear counterpart, particularly in vibration control. It achieved significant reductions in body displacement, body acceleration, and suspension deflection, with notable improvements at resonance speeds. Root Mean Square (RMS) analysis further corroborated the nonlinear model's superior damping performance, showing lower displacement and acceleration values compared to the linear model. The findings indicate the effectiveness of nonlinear damping models in enhancing ride comfort and vehicle stability, providing a more realistic and effective framework for vehicle dynamic analysis compared to conventional linear approaches.

A Systematic Literature Review of Risk Assessment Methodologies for Battery Electric Vehicles

Ayudhia Pangestu Gusti — 2025-03-09

This systematic literature review investigates risk assessment methodologies for Battery Electric Vehicles (BEVs), highlighting their diversity and effectiveness in addressing emerging safety challenges. With the rapid global adoption of BEVs, there is an increasing need for robust methodologies to assess risks such as thermal runaway (TR), degradation, and operational failures. This review highlights techniques such as fuzzy failure mode and effect analysis (FMEA), hybrid neural networks, bayesian networks (BN), and entropy weight methods. These tools effectively identify and mitigate risks; however, they face challenges in providing holistic, system-level safety assessments and adapting to long-term, real-world conditions. Unlike previous works, this study integrates interdependent BEV subsystems into unified risk models and examines underexplored areas such as maritime transport safety. The transport of BEVs by vessels presents unique risks, including high humidity and confined cargo spaces, which intensify the battery safety challenges. Tools like FMEA and real-time monitoring systems are critical to mitigate these risks. The findings highlight the growing reliance on real-time diagnostics and advanced algorithms for enhancing BEV safety and reliability. By identifying gaps and proposing recommendations, this review aims to support the development of standardized frameworks to ensure BEV safety across various environments and operational scenarios, contributing to their continued global adoption.

Trends, Advances, and Future Directions in Fuel Cell Electric Vehicle Performance: A Bibliometric Analysis Using the PAGER Framework

Yusuf Dewantoro Herlambang — 2025-04-13

The global shift toward sustainable transportation has positioned fuel cell electric vehicles (FCEVs) as a key zero-emission mobility solution. Despite notable technological progress, FCEV adoption faces persistent barriers including high hydrogen production costs, limited infrastructure, and lack of real-world validation. This study employs the Pattern, Advance, Gap, Evidence for Practice, and Research Recommendation (PAGER) framework to conduct a comprehensive bibliometric analysis of 200 peer-reviewed publications from 2005 to 2024, focusing on performance trends, technological advancements, research gaps, practical applications, and future research directions. The analysis uses Scopus data and VOSviewer for visualization and thematic mapping to identify three distinct research phases: early exploration, gradual refinement, and rapid technological maturity. Key findings highlight advancements in energy management strategies, hybrid powertrain integration, and hydrogen storage optimization. However, critical gaps remain in economic modeling, behavioral adoption analysis, and infrastructure scalability. This study offers a structured roadmap for future research and practice, emphasizing the need for dynamic total cost of ownership models, interdisciplinary policy interventions, and real-world pilot projects. The findings serve as a strategic reference for academics, industry stakeholders, and policymakers to accelerate the global transition to sustainable FCEV-based transportation systems.

Computational and Experimental Study of the Dynamic Loading of the Tracked and Wheeled Vehicles Powertrain System in Harsh Climatic Conditions

Alexander Igorevich Taratorkin — 2025-04-13

The article presents the results of a computational and experimental study of the dynamic loading of the powertrain system of the transport vehicles, which include a diesel engine and a hydromechanical transmission. The purpose of the study is a computational and experimental substantiation of the applicability of torsion bar spring between the engine and transmission as a torsional oscillation damper in the powertrain system with diesel engines of increased power and high-density arrangement of the block elements, which makes it difficult to apply traditional measurement methods. The novelty of the research consists in the development of a new method to determine experimentally the dynamic torque in the powertrain system, characterized by the fact that during processing, the signal of the engine shaft speed sensor is digitized and transmitted to the recording and processing device. Based on the direct Fourier transform, the amplitude-frequency response function of the torque is determined, including the main motor harmonics, harmonic components formed by the crankshaft and connecting rod and gas valve timing mechanisms of the engine, the generator drive, oscillations in the transmission, etc. It is established that the reason for the torsion bar springs durability limitation is their operation in off-design powertrain system modes, due to the occurrence of a phenomenon called «collision of tasks». Based on probabilistic calculation methods, it is shown that when such modes occur, the probability of failure of elastic torsion bar increases from 0.0001 to a shocking 0.29. According to the research results, it is concluded that torsion bar springs are applicable as torsional vibration dampers in high-duty powertrain systems.

Calibration of HDM-4 Model for Fuel Consumption in Heavy-Duty Trucks: Integration of Telematics, Engine Speed, and Aerodynamics

Pradhana Wahyu Nariendra — 2025-04-13

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.

Vehicle Trajectory Analysis on the Effect of Additional Load Distribution Disturbance at Different Speeds for Collision Avoidance Systems

Abdullah bin Zulkifli — 2025-04-13

Collision avoidance (CA) systems have become a requirement in vehicles due to their ability to prevent collisions. Despite the implementation of these systems on the road, accidents still happen due to the lack of adaptability of CA systems corresponding to road environment nonlinearities and external disturbances. Hence, this research focuses on the effect of external disturbances, such as additional load distribution on the vehicle while avoiding obstacles. The deployment of the CA scenario, considering the presence of disturbance, was simulated in MATLAB Simulink, with the reference trajectory for the system obtained from a skilled driver in real-time experiments at different speeds. The objective of this study is to observe and analyse the effect of additional load disturbances on vehicle stability, especially when the driver countersteers to avoid an obstacle. An increase in the additional load percentage at each side of the vehicle produces excessive lateral force opposite to the direction of the vehicle. This scenario creates a significant load transfer phenomenon and directly causes the vehicle to oversteer and understeer while avoiding obstacles. It has been observed that human cognition plays a huge role in defining a reference trajectory at different speeds while avoiding an obstacle. The pattern of the reference trajectory also affects the magnitude of the load transfer phenomena, especially when the driver manoeuvres the vehicle aggressively.

Alternative Way to Electric Vehicle Battery Technologies as Sustainable Hydrogen Production System without Storage Vessel for Hydrogen Motors and Engine Test

Hasan Köten — 2025-04-13

Although electric vehicles are becoming more widespread today, the electric batteries used as power sources still have many issues. The main problems include short driving range, long charging times, safety and security concerns, the lack of environmentally friendly electricity production, recycling challenges, high costs, and sustainability issues. In particular, lithium-based electric vehicle batteries are gradually being replaced by alternative battery technologies due to their high cost and limited availability. In this study, we introduce a novel hydrogen production method that can serve as both a fuel for internal combustion engines and an energy source through fuel cells for electric cars. Unlike conventional approaches, this method enables the on-demand production of hydrogen fuel without requiring a hydrogen storage tank, allowing direct use in engines. This study not only eliminates hydrogen storage issues but also presents a new alternative power source to lithium-ion, lithium-air, lithium polymer, magnesium-based and sodium-based electric batteries. As a result, the study describes an environmentally friendly alternative energy source for the automotive industry, a sustainable hydrogen production system, and a solution that enhances safety and security while reducing associated risks.

A Simulation Based Metaheuristics for Capacitated Vehicle Routing Problem

Tamara Latifah Jasmine — 2025-04-23

Waste collection and transportation are essential elements of effective waste management. However, despite their importance, previous studies have highlighted several challenges, such as routing inefficiencies and environmental concerns. This study seeks to develop an optimized approach for waste collection and transportation under conditions of demand uncertainty, capacity limitations, and traffic constraints, through the application of a simheuristics-based method. The methodology utilizes a simheuristics approach, integrating a Genetic Algorithm (GA) to determine optimal routing solutions, while employing Discrete Event Simulation (DES) to incorporate key economic, environmental, and social variables. Data were obtained from field experiments and Google Maps, and assumptions regarding capacity requirements, distances and collection points, transportation cost components, and road conditions were established to ensure the reliability of the simulation results. The application of the simheuristics approach effectively reduces total transportation costs by approximately 51%, while also significantly minimizing environmental impacts. This research contributes to the academic literature by presenting an innovative method that strengthens existing waste collection strategies with an emphasis on sustainability. Additionally, it offers valuable insights for waste management policy, enabling the optimization of waste collection without exceeding capacity limits.