Automotive Experiences

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

2025-01-16T06:05:22+00:00

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

2025-01-18T06:05:24+00:00

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

2025-03-09T06:09:43+00:00

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

2025-03-09T06:09:42+00:00

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

2025-03-09T06:09:41+00:00

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.