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      Radar sharing energy-saving control strategy for intelligent hybrid electric vehicle

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          Abstract

          A radar sharing based energy-saving control method was developed for intelligent hybrid electric vehicles to reduce energy loss caused by designs for fixed working conditions that disregard the actual running environment. Four scenarios were developed base on the relative motion of the vehicle in front of this vehicle. The motor drive torque was optimized with regenerative braking by the motor added for some scenarios. These control strategies reduce the hybrid electric vehicle energy use without adding extra hardware cost. Tests on different road conditions show that this intelligent energy-saving control strategy provides large energy savings especially on congested urban roads.

          Abstract

          摘要 为解决现有混合动力汽车能量管理常依赖固定循环工况设计, 未考虑车辆实际运行环境所造成的节能潜力挖掘不足的问题, 该文运用结构共用思想, 提出共用雷达信号的智能混合动力汽车能量管理优化控制方法。依托雷达对前车运动信息的感知, 划分4种不同场景和工作模式, 通过动态优化汽车电机的驱动转矩并增加电机再生制动, 从而在不增加额外硬件成本的前提下, 提升智能混合动力汽车的节能性能。并以某混合动力客车为应用对象进行了实车道路试验, 结果表明所提出的节能控制策略在城市拥堵路况下节能效果明显。

          Author and article information

          Journal
          J Tsinghua Univ (Sci & Technol)
          Journal of Tsinghua University (Science and Technology)
          Tsinghua University Press
          1000-0054
          15 March 2018
          14 March 2018
          : 58
          : 3
          : 286-291,297
          Affiliations
          [1] 1State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
          [2] 2Army Research Institute of PLA, Beijing 100012, China
          Author notes
          *Corresponding author: LI Keqiang, E-mail: likq@ 123456tsinghua.edu.cn
          Article
          j.cnki.qhdxxb.2018.21.004
          10.16511/j.cnki.qhdxxb.2018.21.004
          14464495-c3d8-41cc-8083-b59e6107c219
          Copyright © Journal of Tsinghua University

          This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License (CC BY-NC 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc/4.0/.

          History
          : 20 September 2017

          Software engineering,Data structures & Algorithms,Applied computer science,Computer science,Artificial intelligence,Hardware architecture
          radar information,structure sharing,intelligent hybrid electric vehicle,energy-saving control strategy

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