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All Journal International Journal of Innovation in Mechanical Engineering and Advanced Materials Journal of Novel Engineering Science and Technology
Mumtaz, Mega Maulida
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Engineering Environmental Science Materials Science & Nanotechnology Mechanical Engineering

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Simulation and Analysis of Hatchback Car Driving Comfort and Handling Performance Yamin, Mohamad; Mahandari, Cokorda Prapti; Mumtaz, Mega Maulida
Journal of Novel Engineering Science and Technology Vol. 2 No. 03 (2023): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v2i03.399

Abstract

Hatchback cars are one type of car that is widely used in Indonesia. Indonesia has various road conditions. What is essential for a vehicle is its driving comfort and handling performance. These aspects are not only to fulfil individual interests but also to increase safety while driving.   The driving comfort can be tested through the chassis twisted road test, and the handling performance is tested through the double lane change test. Both tests are carried out by simulation with the CarSim software that applies mathematical modelling. The driving comfort is tested with a speed variation of 8 km/h to 16 km/h. Handling performance was tested with variations in loading of 1 passenger, four passengers, and four passengers + luggage. The parameters used to measure driving comfort are vertical acceleration, pitch, and roll angle. The parameters for handling performance are lateral acceleration, yaw and roll angle, and sheer force. The results show that the best driving comfort is obtained at 8 km/h. The handling performance value will improve if the vehicle load decreases.
Handling and Stability Analysis of an Autonomous Vehicle Using Model Predictive Control in a CarSim–Simulink Co-Simulation Environment Yamin, Mohamad; Mumtaz, Mega Maulida; Firmansyah, Riyan
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 7, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v7i2.31812

Abstract

Cars are a prevalent mode of transportation for both people and goods, with B-class hatchbacks being particularly popular in Indonesia. However, road traffic crashes remain a major concern, contributing millions of deaths annually, primarily due to human error. Autonomous vehicles offer a promising solution to mitigate these issues by reducing reliance on human control. In particular, Level 3 autonomous vehicles enhance road safety, enable independent mobility, reduce traffic congestion, and allow drivers to engage in non-driving tasks. This study proposes an autonomous vehicle model that employs a trajectory tracking approach using Model Predictive Control (MPC), a robust and widely adopted control strategy in autonomous systems. A three-degree-of-freedom (3-DOF) vehicle dynamic model was developed and analyzed through co-simulation using CarSim and Simulink to evaluate its performance during a double-lane change maneuver. The simulation results demonstrate that the vehicle accurately follows the reference trajectory and exhibits excellent dynamic performance. The roll angle remained consistently low, ranging between 0.024 and 0.026 radians—well below the rollover threshold of 0.14 radians—demonstrating strong roll stability. The slip angle varied between –0.013 and 0.0135 radians, nearly 12 times lower than the critical limit, indicating optimal traction and directional control. Lateral acceleration ranged from –3.59 m/s² to 3.41 m/s², and yaw rate remained within –7.78°/s to 7.25°/s, both well within safe operational bounds. These findings confirm that the proposed MPC-based control framework enables precise path tracking, robust stability, and reliable handling performance in dynamic driving scenarios.
Co-Authors Cokorda Prapti Mahandari Firmansyah, Riyan Mohamad Yamin