摘要
近年来,燃料电池汽车发展迅速,能量管理策略对提高燃料电池客车能量经济性具有重要意义。通过构建整车实时能量管理策略,对燃料电池客车的能量经济性进行了研究。首先基于某示范运行的燃料电池客车运行数据,使用径向基神经网络算法预测不同时域未来行驶车速;然后结合模型预测控制理论与凸优化算法构建了以预测时域内能量消耗最小为目标的分层预测能量管理策略;最后在实车工况下进行仿真验证,并分析比较了两种初始荷电状态下的百公里等效氢耗。仿真结果表明:与实车控制策略相比,所构建的分层预测能量管理策略能够降低9.6%~16.9%的百公里等效氢耗,有效地提高了整车的能量经济性。
Fuel cell vehicles have developed rapidly in recent years.Energy management strategy plays an important role in improving energy economy of fuel cell bus.The energy efficiency of the fuel cell bus was studied by developing a real-time energy management strategy.Firstly,the radial basis function neural network algorithm was used to predict the future vehicle speed in different time domains based on the real data of a fuel cell bus.Then,a hierarchical predictive energy management strategy was proposed by combining model predictive control theory and convex optimization algorithm with constraints on optimization objectives,aiming at minimizing energy consumption in a predicted time domain.Finally,the equivalent hydrogen consumption of the power battery under charge and discharge conditions was analyzed and compared.The simulation results show that compared with the real vehicle control strategy,the proposed hierarchical predictive energy management strategy can reduce the equivalent hydrogen consumption by 9.6%~16.9%,and thus improve the energy efficiency of the vehicle effectively.
作者
高新梅
徐鑫
余忠伟
武小花
GAO Xin-mei;XU Xin;YU Zhong-wei;WU Xiao-hua(Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province, Xihua University, Chengdu 610039, China)
出处
《科学技术与工程》
北大核心
2022年第15期6325-6330,共6页
Science Technology and Engineering
基金
四川省科技计划项目(2020YFQ0037,2019ZDZX0002,2021YFG0071)
四川省西华大学研究生创新基金(YCJJ2020073)。
关键词
车速预测
燃料电池客车
凸优化
能量管理策略
speed prediction
fuel cell bus
convex optimization
energy management strategy
