AI Summary & Key Takeaways
AI InsightThe results demonstrate a strong correlation for sprung mass and pitch rate responses, with low average relative errors of 0.0828 at 10 km/h, 0.0720 at 20 km/h, and 0.0663 at 30 km/h.
📌 3 Key Takeaways
Abstract
This study presents a comprehensive investigation into the dynamic performance of Internal Combustion Engine (ICE) and Electric Vehicle (EV) configurations through experimental and simulation methods. The study is divided into two (2) core components. The first focuses on validating a developed data acquisition (DAQ) system by comparing experimental results of vehicle dynamics characteristics. The results are through validation with CarSim software. The results demonstrate a strong correlation for sprung mass and pitch rate responses, with low average relative errors of 0.0828 at 10 km/h, 0.0720 at 20 km/h, and 0.0663 at 30 km/h. It confirmed that the DAQ system that was developed performed with high accuracy and fidelity. The second core component involves a comparative dynamic analysis of ICE and EV vehicles under ISO 8727 standard test at specific speed level. The results demonstrated that the EV model consistently exhibits improved damping characteristics, lateral acceleration symmetry, and smoother directional transitions. In contrast, the ICE vehicle displays higher vertical and lateral acceleration peaks, suggesting more aggressive suspension dynamics and possibility to cause discomfort to the passenger. These findings underscore the advantages of EV architectures in delivering enhanced ride comfort, handling stability, and responsiveness. The study not only focuses on validation of DAQ system and simulation framework but also provides valuable insights for the development of advanced vehicle control strategies in future mobility solutions in terms of stability and ride comfort varying with changes of the external disturbance.