摘要
利用车载全球定位系统(Global Position System,GPS)和地理信息系统(Geographic Information System,GIS)所提供的混合动力汽车未来一段预测路线上的道路交通信息、以及汽车当前运行状态模型,建立混合动力汽车在未来一段预测路线上的运行状态模型;以蓄电池荷电状态为系统状态变量,电动机/发电机转矩为决策变量,混合动力汽车等效燃油消耗量最低为优化控制目标函数,运用动态规划逆序算法,建立了中度混合动力汽车预测控制数学模型;研究了混合动力汽车转矩分配的最优控制方法,并就如何减少动态规划法的计算量进行了研究。文中给出了某混合动力汽车的最优控制计算实例结果。
Applying the information of mad and traffic in the future predictive route provided by Global Position System and Geographic Information System on board, and current driving states of HEVs, the driving state model in the future predictive route was set up. A predictive control model of medium HEVs was established by applying dynamic programming reverse algorithm, which the battery state of charge was chosen as state variable, motor/ generator torque was chosen as decision variable, and the minimal equivalent fuel consumption was chosen as the optimal control target. The optimal control method for the torque distribution of HEVs was studied, and some methods were offered to reduce the dynamic programming computation. Finally the calculation results of a HEV for the optimal control was presented.
出处
《公路交通科技》
CAS
CSCD
北大核心
2009年第1期149-153,158,共6页
Journal of Highway and Transportation Research and Development
基金
重庆市自然科学基金资助项目(CSTC
2007BB0116)
关键词
汽车工程
混合动力汽车
预测控制
动态规划
最优控制
automobile engineering
hybrid electric vehicle （HEV）
predictive control
dynamic programming
optimal control
