TY  - EJOU
AU  - Yu, Yixuan 
AU  - Wang, Yulin 
AU  - Li, Qingcheng 
AU  - Jiao, Bowen 

TI  - A Predictive Energy Management Strategies for Mining Dump Trucks
T2  - Energy Engineering

PY  - 2024
VL  - 121
IS  - 3
SN  - 1546-0118

AB  - The plug-in hybrid vehicles (PHEV) technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks. Meanwhile, plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies (EMS). Therefore, a series hybrid system is constructed based on a 100-ton mining dump truck in this paper. And inspired by the dynamic programming (DP) algorithm, a predictive equivalent consumption minimization strategy (P-ECMS) based on the DP optimization result is proposed. Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm, the P-ECMS strategy performs real-time stage parameter optimization to obtain the optimal equivalent factor (EF). Finally, applying the equivalent consumption minimization strategy (ECMS) realizes real-time control. The simulation results show that the equivalent fuel consumption of the P-ECMS strategy under the experimentally collected mining cycle conditions is 150.8 L/100 km, which is 10.9% less than that of the common CDCS strategy (169.3 L/100 km), and achieves 99.47% of the fuel saving effect of the DP strategy(150 L/100 km).
KW  - Mining dump truck; energy management strategy; plug-in hybrid electric vehicle; equivalent consumption minimization strategy; dynamic programming

DO  - 10.32604/ee.2023.044042