Mode control strategy for autonomous driving PHVs
LIU Qi-xing
WU Yu-hu
Abstract：This article addresses a mode-switching optimization challenge for plug-in hybrid vehicles(PHVs)oper-ating in dual configurations:pure electric(EV)and hybrid electric(HEV)modes.Focusing on autonomous PHVs with predefined route speed profiles,we develop an optimal mode selection strategy to minimize fuel consumption while sat-isfying battery energy constraints.The problem is formulated as a mixed-integer linear programming(MILP)model to simultaneously optimize driving mode transitions and battery energy allocation across road segments.We propose a collab-orative neurodynamic optimization(CNO)algorithm to solve the problem.Comparative testing on real-world road network instances and the case study validate the effectiveness of the CNO algorithm.
Keywords：plug-in hybrid vehiclesmode controlmixed integer programming problemcollaborative neurodynamic optimization
Publication Date：2025-08-30
Online Publishing Date：2025-10-10(First online date of this platform, not the publication date of the document)
Pages：8( 1553-1560 )