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作 者:邢峰[1] 邓国红 XING Feng;DENG Guohong(Institute of Intelligent Manufacturing and Automotive,Chongqing Technology and Business Institute,Chongqing 401520,China;Vehicle Engineering Institute,Chongqing University of Technology,Chongqing 401135,China)
机构地区:[1]重庆工商职业学院智能制造与汽车学院,重庆401520 [2]重庆理工大学车辆工程学院,重庆401135
出 处:《机床与液压》2018年第16期36-40,47,共6页Machine Tool & Hydraulics
基 金:重庆市基础与前沿研究计划项目(cstc2015jcyj A60003);重庆市教委科研项目(kj1403804)
摘 要:为了满足电动汽车对电源系统功率和能量的需求,解决电动汽车复合电源匹配问题,以动力电池-超级电容复合电源结构的纯电动汽车为研究对象,研究基于模型预测控制理论的能量管理策略。搭建马尔科夫模型预测车辆未来状态,在预测时域内利用动态规划算法求解优化问题,针对动力电池及超级电容之间的功率分配问题实现实时在线管理。选择NEDC循环工况对控制策略进行仿真,结果表明:基于模型预测控制的能量管理策略不仅具有良好的控制效果,还具有实时控制的潜力。In order to solve the matching problem of the composite power supply of electric vehicle to satisfy the demand to power and energy,the energy management strategy of pure electric vehicle with battery-super capacitor hybrid energy storage structure was studied based on the model predictive control theory.The Markov model was established to predict the future state of the vehicle.Dynamic programming algorithm was used to solve the optimization problem within the predictive horizon and the real-time online management of the power distribution between the battery and the super capacitor was realized.Finally,the proposed control strategy was simulated under the NEDC cycle condition.The simulation results show that the energy management strategy based on the model predictive control has a good control effect,and potential of the real-time control.
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