Extending the maximum driving distance of an electric vehicle would be beneficial given these vehicles’ long charging time and limited battery capacity and to improve electricity consumption. Research on the optimal development of the powertrain is essential because the efficiency of an electric motor varies according to the operating point. In this study, we developed a simulation analysis model with a continuously variable transmission. based on the commercial electric vehicle (Company B) model and using actual vehicle driving data supplied by the Argonne National Laboratory. The shift pattern of the continuously variable transmission was then optimized by considering the change in the operating point, constant motor output area, and transmission response speed. In addition, a performance comparison was made using the model with a single reducer. The results obtained by this study showed that electronic economy improved by approximately 5% when the continuously variable transmission was applied through the combined driving simulation. Furthermore, the time taken to accelerate 0–100 km/h and 80–120 km/h reduced by 15% and 6%, respectively. The maximum driving distance on a single charge improved by 7 km. It was confirmed that the driving performance of an EV with continuously variable transmission could be improved by downsizing the electric motor to reduce manufacturing costs.

A diesel particulate filter (DPF) is an exhaust after-treatment device designed to capture and store exhaust particulate matter, such as soot and ash, to reduce emissions from diesel-powered vehicles. A DPF has a finite capacity and typically uses a substrate made of ceramic material that is formed into a honeycomb structure. Diesel particulate filters play an important role in diesel-fueled vehicles. Failure to maintain these filters can have significant consequences for vehicles. In this study, we investigated the failure type in cordierite DPF substrates. In addition, we experimentally characterized the particle number (PN) emission and on-board diagnostics (OBD) signal of a 2.0 L diesel-fueled vehicle generated by three types of DPF failure (crack, melting, and hollow). Specifically, X-ray photography analysis of the cordierite DPF was performed. The PN and OBD signals were assessed via the KD-147 vehicle driving mode and measured using a DMS-500 (PN measurement device) and global diagnosis tool (GDS) scanner (OBD diagnostic device), respectively. X-ray photography was used to characterize the internal structure of the three DPF-failure samples. A key result was that the maximum value of the OBD data, including airflow mass, boost pressure, and VGT actuator, was distinctly different for each DPF sample. The exhaust temperature gradient for the normal DPF and crack-damaged DPF followed the KD-147 driving pattern. This was because there was no volume damage inside the cordierite DPF substrates. However, in the case of the hollow and melting-damaged DPF, the volume inside the cordierite DPF substrates was reduced or the time for the exhaust gas to stay in the DPF substrates was decreased. The melting-damaged DPF continuously emitted the largest number of nanoparticles (of the order of 109 #/cc). This was regardless of the vehicle driving speed in the KD-147 driving mode. Eventually, an OBD-based algorithm to determine whether a DPF is damaged was derived in this study.