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智能混合动力汽车经济性自适应巡航控制策略研究
引用本文:安全,王翔宇,李亮.智能混合动力汽车经济性自适应巡航控制策略研究[J].北京理工大学学报,2018,38(S1):133-136.
作者姓名:安全  王翔宇  李亮
作者单位:清华大学 汽车安全与节能国家重点实验室, 北京 100084,清华大学 汽车安全与节能国家重点实验室, 北京 100084,清华大学 汽车安全与节能国家重点实验室, 北京 100084
摘    要:针对智能混合动力汽车自适应巡航过程中的能量控制策略问题,结合模型预测控制在处理多目标、多约束优化问题方面的优势和粒子群算法运算量小、收敛快的特点,将粒子群算法作为模型预测控制的滚动优化方法,构造基于模型预测控制的粒子群算法.仿真结果表明,文中算法能够使绝大部分工况点落在较低燃油消耗率区域,只有少部分工况点落在非经济区域,虽然多消耗了1.06%的燃油,但在运算速度上却获得了60.3%的提升.

关 键 词:粒子群算法  模型预测控制  混合动力汽车  自适应巡航控制  能量控制策略
收稿时间:2018/6/15 0:00:00

Research on Control Strategy for Hybrid Electric Vehicle's Economy-Oriented Adaptive Cruise
AN Quan,WANG Xiang-yu and LI Liang.Research on Control Strategy for Hybrid Electric Vehicle's Economy-Oriented Adaptive Cruise[J].Journal of Beijing Institute of Technology(Natural Science Edition),2018,38(S1):133-136.
Authors:AN Quan  WANG Xiang-yu and LI Liang
Institution:State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, 100084, China,State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, 100084, China and State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, 100084, China
Abstract:Energy management strategy was studied for intelligent hybrid electric vehicle during adaptive cruise. A particle swarm optimization (PSO) algorithm based nonlinear model predictive control (MPC) was proposed. Combining the advantage of MPC in solving multi-object and multi-restriction optimization problem with the characteristic of PSO in small operand and high efficiency, the PSO was taken as the roll optimization method to form a PSO based MPC algorithm. Simulation results show that, the algorithm can make most car operation focus in low fuel consumption and can speed up the calculation process.
Keywords:particle swarm optimization(PSO)  model predictive control(MPC)  hybrid electric vehicle(HEV)  adaptive cruise control(ACC)  energy management strategy(EMS)
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