考虑电驱动系统特性的三维多目标路径规划方法

IF 2.5 4区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Yongpeng Shen, Hongyuan Huang, Xiaofang Yuan, Guoming Huang, Xizheng Zhang, Suna Zhao
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引用次数: 0

摘要

电动汽车的快速发展受到续航里程限制的制约。智能路径规划可以显著提高能源效率,延长行驶里程。针对电驱动系统(EDS-3DM)的特点,提出了一种新的三维多目标路径规划方法。首先,建立了基于能效分析的汽车动力学模型和能耗估算模型。其次,设计了基于欧氏距离和能量消耗的综合路径评价模型。然后应用b样条曲线来平滑最终的路径。在三种不同地图上的实验结果证明了EDS-3DM的有效性,平均能耗降低了12.74%。为解决智能电动汽车的路径规划问题,提出了一种考虑EDS-3DM特性的三维多目标路径规划方法。三张地图上的路径规划结果证明了EDS-3DM的有效性,其平均能耗优化能力为12.74%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Three-Dimensional Multi-Objective Path Planning Method Considering the Characteristics of Electric Drive System

A Three-Dimensional Multi-Objective Path Planning Method Considering the Characteristics of Electric Drive System

A Three-Dimensional Multi-Objective Path Planning Method Considering the Characteristics of Electric Drive System

A Three-Dimensional Multi-Objective Path Planning Method Considering the Characteristics of Electric Drive System

The rapid advancement of electric vehicles (EVs) is hindered by their limited driving range. Intelligent path planning can significantly improve energy efficiency and extend driving range. This paper proposes a novel three-dimensional multi-objective path planning method considering the characteristics of the electric drive system (EDS-3DM). First, vehicle dynamics and energy consumption estimation models are developed based on the efficiency analysis of the EDS. Next, a comprehensive path evaluation model is designed using both Euclidean distance and energy consumption. B-spline curves are then applied to smooth the final paths. Experimental results on three different maps demonstrate the effectiveness of EDS-3DM, achieving an average energy consumption reduction of 12.74%.To address the path planning challenge in intelligent EVs, this paper proposes a novel three-dimensional multi-objective path planning method that considers the characteristics of the EDS-3DM.The path planning results on three maps demonstrate the effectiveness of the EDS-3DM and its ability to achieve an average energy consumption optimization of 12.74%.

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来源期刊
IET Intelligent Transport Systems
IET Intelligent Transport Systems 工程技术-运输科技
CiteScore
6.50
自引率
7.40%
发文量
159
审稿时长
3 months
期刊介绍: IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf
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