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Power distribution strategy of a dual-engine system for heavy-duty hybrid electric vehicles using dynamic programming

机译：使用动态编程的重型混合动力电动汽车双发动机系统配电策略

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摘要

In order to enhance the power and bring additional energy-saving possibilities of heavy-duty vehicles, a novel dual-engine system is utilized in a series hybrid electric vehicle. However, the minimum fuel consumption of this configuration is still unclear, and the effective online energy management strategy for this system is absent. The studied vehicle adopts the dual-engine configuration, which is powered by Li-ion batteries and two auxiliary power units. This paper presents a two-step framework to address the energy management problem. A map-based strategy is adopted to distribute power between engines. The dynamic programming (DP) algorithm is incorporated to distribute power between engines and batteries and find the minimum fuel consumption. Simulation results show that the DP algorithm can save 7.3% fuel compared to the charge depleting and charge sustaining strategy. The dual-engine system achieves a 1.9% lower fuel consumption compared with the conventional hybrid system with one engine. The operation points of engines and the power profiles of batteries derived from the DP are analyzed, and a rule-based strategy is designed correspondingly. The proposed rule-based algorithm can reduce 2.2% -6.0% fuel consumption and is not sensitive to the variations of battery size, parameters of the rule-based strategy, and driving cycles.
机译：为了提高功率并带来重型车辆的额外节能可能性，在串联混合动力电动车辆中使用了一种新型双发动机系统。然而，这种配置的最低燃料消耗仍然不明确，并且缺席该系统的有效在线能源管理策略。研究的车辆采用双发动机配置，由锂离子电池和两个辅助动力单元提供动力。本文介绍了一个两步的框架，以解决能源管理问题。采用基于地图的策略在发动机之间分配电力。流动编程（DP）算法被融入，以在发动机和电池之间分配电力，并找到最小的燃料消耗。仿真结果表明，与电荷耗尽和电荷持续策略相比，DP算法可以节省7.3％的燃料。与具有一个发动机的传统混合系统相比，双发动机系统达到了1.9％的燃料消耗。分析了从DP导出的电池的发动机的操作点，并且相应地设计了基于规则的策略。所提出的规则算法可以减少2.2％-6.0％的燃油消耗，对电池尺寸的变化，基于规则的策略的参数以及驱动周期的燃料量不敏感。

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  • 来源
    《Energy》 |2021年第1期|118851.1-118851.15|共15页
  • 作者

    Jiayi Hu; Jianqiu Li; Zunyan Hu; Liangfei Xu; Minggao Ouyang;

  • 作者单位

    State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 PR China;

    State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 PR China;

    State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 PR China;

    State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 PR China;

    State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 PR China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hybrid electric vehicle; Energy management strategy; Dual-engine system; Heavy-duty vehicle; Dynamic programming;

    机译：混合动力电动车;能源管理战略;双发动机系统;重型车辆;动态编程;
  • 入库时间 2022-08-18 23:01:17

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