 Car-following speed collaborative energy management strategy for connected PHEVFeng Wang, Yihang Chen, Yuanjian Zhang, Xiaoyuan Zhu and Yi-Qing Ni Energy, 2025, vol. 329, issue C Abstract: Sequential vehicle speed planning and energy management design is widely employed in plug-in hybrid electric vehicle (PHEV). However, this hierarchical strategy is difficult to achieve comprehensive performance optimization, as vehicle speed and energy management are inherently coupled. This paper proposes a new real-time optimization car-following speed collaborative energy management strategy (RTO-SC-EMS) for connected PHEV in the context of V2X environment, Firstly, a gated recurrent unit neural network is utilized to predict the short-term speed of the lead-vehicle based on collected representative urban driving cycles incorporating traffic information. Then, the solution section of real-time optimization car-following speed collaborative energy management strategy is used to generate host-vehicle's optimal acceleration and corresponding control sequence. Finally, the effectiveness of the proposed RTO-SC-EMS was validated by Hardware-in-the-Loop (HIL) platform. Keywords: Electric vehicle; Car-following speed collaborative energy management strategy; Coordinated control; Traffic information; Hardware-in-the-loop (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:329:y:2025:i:c:s036054422502359x DOI: 10.1016/j.energy.2025.136717 Access Statistics for this article Energy is currently edited by Henrik Lund and Mark J. Kaiser More articles in Energy from Elsevier |
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