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为进一步改善插电式混合动力汽车(plug-in hybrid electric vehicle, PHEV)的能量经济性，提出了一种考虑市区道路交通信息的经济车速规划方法及基于模型预测控制(model predictive control, MPC)的能量优化管理策略。以某款P2构型的PHEV为研究对象，基于市区路口信号灯配时状态信息，分别采用动态规划与高斯伪普法优化求解经济车速。根据规划出的经济车速，提出了基于MPC的优化能量管理策略，其利用Dijkstra算法求解最优转矩分配。结果表明：对比基于规则的分段三角函数法，2种经济车速规划算法分别可降低6.31%、7.03%的PHEV等效油耗。基于MPC的优化能量管理策略相比于基于规则的能量管理策略可进一步提升4.98%的能量经济性。
Abstract：In order to further improve the energy economy of plug-in hybrid electric vehicles( PHEV),an economical speed planning method considering urban traffic information and an energy optimization management strategy based on model predictive control were proposed. Taking a PHEV with a P2 configuration as the research object,based on the timing information of traffic lights,the dynamic programming and Gaussian pseudo-generalization were used to optimize the economic speed of PHEV passing through the signal light intersection. According to the planned economic speed,an optimal energy management strategy based on model predictive control( MPC) was proposed,which used the Dijkstra algorithm to solve the optimal torque distribution. The results show that compared with the rule-based piecewise trigonometric function method,the two economic speed planning algorithms can reduce PHEV equivalent fuel consumption by 6.31% and 7.03%respectively. The MPC-based optimal energy management strategy can further improve the energy economy by4.98% compared with the rule-based energy management strategy.
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基本信息:
DOI：10.15926/j.cnki.issn1672-6871.2023.02.006
中图分类号:U469.7
引用信息:
[1]陈慧勇,李涛,杨学青,等.车路协同的插电式汽车预测能量管理策略研究[J].河南科技大学学报(自然科学版),2023,44(02):41-50+6-7.DOI:10.15926/j.cnki.issn1672-6871.2023.02.006.
基金信息:
国家重点研发计划项目(2018YFB0105900); 国家自然科学基金项目(51675381)
2022-12-28
2022-12-28