燃料电池电动汽车的能量管理

doi:10.13229/j.cnki.jdxbgxb20210773

摘要/Abstract

摘要：

为了研究一类以超级电容和燃料电池作为能量来源的电动汽车能量管理的问题，首先建立了燃料电池和超级电容模型，其中，包括燃料电池性能衰退模型；其次，提出了一种改进的功率跟随能量管理控制策略，通过对二次型效用函数进行偏微分并结合Karush-Kuhn-Tucker（KKT）条件将需求功率分解为燃料电池和超级电容各自的目标功率；最后，采用多目标人工蜂群算法和Pareto解集迭代求解算法内部的最佳平衡系数，同时提升了整车经济性及燃料电池的耐久性。仿真结果表明：与传统功率跟随策略相比，本文改进功率跟随策略可以降低2%的等效氢气消耗，并降低92.66%的燃料电池性能衰退，车辆只需要消耗1.2 kg氢气即可行驶88.52 km。

关键词: 燃料电池, 能量管理, Karush-Kuhn-Tucker条件, 多目标人工蜂群算法

Abstract:

In order to solve the energy management problems of an electric vehicle based on fuel cell and ultracapacitor. Firstly， the models of fuel cell and ultracapacitor are established， including the performance degradation model of fuel cell. Secondly， an optimal energy management control strategy based on power following strategy is proposed. The required power is decomposed into the target power of fuel cell and ultracapacitor by partial differentiation of quadratic utility function and combined with Karush-Kuhn-Tucker conditions. Finally， the multi-objective artificial bee colony algorithm and Pareto solution set iterative algorithm are used to solve the internal optimal balance coefficient， and the vehicle economy and fuel cell durability are both improved. The simulation results show that compared with the traditional power following strategy， the proposed optimal-power following strategy can reduce the equivalent hydrogen consumption by 2%， reduce the fuel cell degradation by 92.66%， the vehicle can travel 88.52 km and only 1.2 kg hydrogen is consumed.

Key words: fuel cell, energy management, Karush-Kuhn-Tucker conditions, multi-objective artificial bee colony algorithm

中图分类号:

U469.72

孙闫,夏长高,尹必峰,韩江义,高海宇,刘静. 燃料电池电动汽车的能量管理[J]. 吉林大学学报(工学版), 2022, 52(9): 2130-2138.

Yan SUN,Chang-gao XIA,Bi-feng YIN,Jiang-yi HAN,Hai-yu GAO,Jing LIU. Energy management strategy of fuel cell electric vehicles[J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2130-2138.

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控制策略	等效氢耗/g	燃料电池衰退/（10^-4%）
PF	342.287	27.15
OP_PF	335.415	1.993