摘要
基于车载导航系统(GPS/GIS)建立汽车未来一段行驶路线上的汽车运行状态模型,将模型预测控制与动态规划相结合,提出了中度混合动力汽车实时在线滚动优化控制策略;并就如何减少动态规划计算量及系统变量离散化问题进行了研究;建立了中度混合动力汽车燃油经济性预测控制仿真模型,采用C语言与MTALAB\Simulink进行联合仿真,验证了所设计的模型预测控制算法可以满足实时控制的要求,且采用该预测控制策略的中度混合动力汽车具有显著的节油效果。
Combining model predictive control with dynamic programming, a real-time on-line receding horizon optimal control strategy for medium hybrid electric vehicles is proposed, which based on the driving states of vehicles built by GPS/GIS on board in the future predictive route. The problem of how to reduce the dynamic programming computation and the system variable quantization are studied. The simulation model of predictive control for the fuel economy of the medium hybrid electric vehicles is built. It is verified by the simulation combining C code with MTALAB／Simulink, that the predictive control algorithm could meet the need of the real-time control of hybrid electric vehicles, and the fuel economy is increased remarkable compared with the foundational vehicles.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2010年第1期36-41,共6页
Journal of Chongqing University
基金
重庆市自然科学基金资助项目(CSTC2007BB0116)
关键词
混合动力汽车
模型预测控制
动态规划
仿真
hybrid electric vehicle
model predictive control
dynamic programming
simulation
