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- Title
Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks.
- Authors
Chu, Hongqing; Na, Xiaoxiang; Liu, Huan; Wang, Yuhai; Yang, Zhuo; Zhang, Lin; Chen, Hong
- Abstract
Fuel consumption is one of the main concerns for heavy-duty trucks. Predictive cruise control (PCC) provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information. In this study, a real-time implementable PCC, which simultaneously optimizes engine torque and gear shifting, is proposed for heavy-duty trucks. To minimize fuel consumption, the problem of the PCC is formulated as a nonlinear model predictive control (MPC), in which the upcoming road elevation information is used. Finding the solution of the nonlinear MPC is time consuming; thus, a real-time implementable solver is developed based on Pontryagin's maximum principle and indirect shooting method. Dynamic programming (DP) algorithm, as a global optimization algorithm, is used as a performance benchmark for the proposed solver. Simulation, hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller. The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution, with less than 1% deviation for testing roads. Moreover, the proposed co-optimization controller is implementable in a real-truck, and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9% without compromising the truck's travel time.
- Subjects
HEAVY duty trucks; CRUISE control; PONTRYAGIN'S minimum principle; OPTIMIZATION algorithms; TRAVEL time (Traffic engineering); TRUCK fuel consumption
- Publication
Chinese Journal of Mechanical Engineering, 2024, Vol 37, Issue 1, p1
- ISSN
1000-9345
- Publication type
Article
- DOI
10.1186/s10033-024-01015-7