Development of a representative transient cycle for evaluating real driving emissions of heavy-duty diesel engines

Abstract

Accurately assessing real driving emissions is crucial for effectively controlling vehicle exhaust pollution. However, significant discrepancies exist between the World Harmonized Transient Cycle (WHTC) used for emission certification and real driving conditions of heavy-duty diesel engines in China. To address this issue, this study introduces a two-step method for developing representative transient cycles. In the first step, short strokes are classified using the k-means clustering algorithm with adaptive particle swarm optimization to identify key kinematic scenarios for heavy-duty diesel vehicles. The Markov Chain Monte Carlo method is then applied to simulate driving patterns for these scenarios, thereby constructing the heavy-duty real driving cycle (HRDC). In the second step, the heavy-duty real transient cycle (HRTC) for diesel engines is generated by integrating typical transmission system and gear matching rules based on the HRDC. The emission test results indicate that compared to WHTC, NOx, PM, and PN emissions under HRTC increased by 36.69 %, 4.57 %, and 78.73 %, respectively. Additionally, transient soot emissions under HRTC are 155.74 % higher than those predicted by steady-state interpolation. The primary factor leading to transient soot emission deterioration is a sudden torque increase exceeding 40 %/s, observed during idle or motoring conditions. These findings provide a solid foundation for reliably evaluating the road emission performance of heavy-duty diesel vehicles.