Driving behavior-adaptive particle emissions in plug-in hybrid electric vehicles: cumulative-transient characteristics and clustered patterns for real- world monitoring

Regulatory gaps in restart and cold/hot start emissions overlooked by current periodic technical inspection (PTI), and driving behaviors significantly impact plug-in hybrid electric vehicle (PHEV) particle number (PN) emissions under real driving conditions. Using portable emissions measurement systems (PEMS), this study building cumulative PN emissions across key segments (cold-start, restart) and instantaneous high-emission events across four distinct behaviors. Key findings reveal that calm and normal driving elevate cold-start PN (up to 6.2×10¹¹ #/km) due to prolonged engine-off intervals and slow warm-up. Aggressive driving’s frequent restarts yield lower per-event emissions owing to thermal advantages. Adaptive cruise control (ACC) minimizes total PN by combining thermally efficient engine operation with extended zero-emission phases (16–17% duration). Crucially, instantaneous high-emission analysis shows > 80% of PN concentrates in < 10% of driving duration, with emission thresholds varying dramatically (82-1366%) across behaviors—primarily due to divergent dominant modes favored by each behavior. To quantify these behavior-specific modes and their parametric signatures, k-means clustering was applied, and found distinct behavioral associations: aggressive driving predominantly linked to high-load/high-rpm operation (> 2800 rpm or > 80% load), while calm/normal driving elevates cold-start and restart contributions. Consequently, real-world emission monitoring necessitates behavior-adaptive dynamic scenarios, tailoring test focus and parametric design informed by clustered thresholds.