| 引用本文: | 刘起兴,吴玉虎.面向自动驾驶PHVs的模态控制策略[J].控制理论与应用,2025,42(8):1553~1560.[点击复制] |
| LIU Qi-xing,WU Yu-hu.Mode control strategy for autonomous driving PHVs[J].Control Theory & Applications,2025,42(8):1553~1560.[点击复制] |
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| 面向自动驾驶PHVs的模态控制策略 |
| Mode control strategy for autonomous driving PHVs |
| 摘要点击 2495 全文点击 186 投稿时间：2024-07-25 修订日期：2025-09-05 |
| 查看全文 查看/发表评论 下载PDF阅读器 HTML |
| DOI编号 10.7641/CTA.2025.40396 |
| 2025,42(8):1553-1560 |
| 中文关键词 插电式混合动力汽车 模态控制 混合整数优化问题 协作神经动力学优化 |
| 英文关键词 plug-in hybrid vehicles mode control mixed integer programming problem collaborative neurodynamic optimization |
| 基金项目 国家自然科学基金项目(62173062,U24A20263)资助. |
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| 中文摘要 |
| 针对具有纯电动和混合动力两个工作模态的插电式混合动力汽车(PHVs),本文研究了用电量受限的情况
下如何根据路段选择动力模态实现最小化油耗的问题.对于按照给定的行驶路径和行驶速度的自动驾驶PHVs,当
行驶该路程的可用电量不足以纯电动模态行驶全程的情景,本文将动力链模态控制问题描述为一个混合整数线性
优化问题,以确定不同路段车的工作模态以及用电量分布.进而,设计了一种协作神经动力学优化(CNO)算法来求
解该问题.通过在实际算例上的对比以及案例研究验证了CNO算法的有效性. |
| 英文摘要 |
| 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. |