Lv, Dongxuan (Tianjin University), Song, Kang (TianJin University), Zhou, Quanyu (TianJin University), Xie, Hui (Tianjin University), Lei, Yuyang (Tianjin University)

Model-Based Gear Shifting Strategy Considering the Impacts of Power Interruption and Prediction Horizon

Scheduled for presentation during the Regular session "Vehcile Control III" (FrA2), Friday, November 1, 2024, 09:30−09:50, Room T2

7th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, Oct 30 - Nov 1, 2024, Dalian, China

This information is tentative and subject to change. Compiled on January 2, 2025

Abstract

This study presents a gear shifting strategy for heavy-duty trucks with automated manual transmission (AMT), addressing frequent gear shifting issues while enhancing overall fuel economy. A dual-horizons prediction approach is used, incorporating a vehicle energy consumption and dynamics model and a acceleration pedal-based future driving condition predictive algorithm. This method achieves a balance between fuel consumption, shifting frequency, and dynamic performance. Simulations on high-precision simulation platform show a 1.96% reduction in fuel consumption and a 23.53% decrease in shifting frequency compared to the MAP-based strategy under the CHTC-S (China heavy-duty commercial vehicle test cycle-semitrailer).