Hierarchical predictive energy management strategy for fuel cell buses entering bus stops scenario

Mei Yan , Hongyang Xu , Menglin Li , Hongwen He , Yunfei Bai
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引用次数: 2

Abstract

This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment. For the buses entering the bus stops scenario, this paper proposes a hierarchical energy management strategy for fuel cell buses, which considers the traffic information near the bus stops. In the upper-level trajectory planning stage, the optimal SOC trajectory under various historical traffic conditions is solved through dynamic planning. The traffic information and the best SOC trajectory are mapped through BiLSTM, which can achieve fast, real-time long-term SOC reference. In the lower-level real-time predictive energy management strategy, the optimal SOC is used as the state reference to guide the predictive energy management of fuel cell buses when entering the bus stops. Simulation results show that compared with the strategy without SOC trajectory reference, the life cost of the proposed strategy is reduced by 13.8%, and the total cost is reduced by 3.61%. The SOC of the proposed strategy is closer to the DP optimal solution.

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燃料电池客车进站场景的分层预测能量管理策略
本文旨在回答如何利用交通信息设计网络环境下燃料电池公交车的能源管理策略。针对进入公交站点场景的公交车,本文提出了一种考虑公交站点附近交通信息的燃料电池公交车分级能源管理策略。在上层轨迹规划阶段,通过动态规划求解各种历史交通条件下的最优SOC轨迹。通过BiLSTM映射交通信息和最佳SOC轨迹,可以实现快速、实时的长期SOC参考。在较低级别的实时预测能量管理策略中,最佳SOC作为状态参考,指导燃料电池公交车在进入公交车站时的预测能量管理。仿真结果表明,与没有SOC轨迹参考的策略相比,该策略的寿命成本降低了13.8%,总成本降低了3.61%。该策略的SOC更接近DP最优解。
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