Real-time Optimization Control Algorithm of Energy Management Strategy for Hybrid Electric Vehicles
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摘要: 依据最优控制理论得到的混合动力汽车能量管理策略与未来的驾驶需求相关联,无法解决算法的实时性问题.本文另辟蹊径,结合规则构造二次型性能指标来限制发动机功率的大幅度频繁波动,间接地降低油耗.为此,在对混合动力系统近似线性处理的基础上,利用二次型最优跟踪理论推导出定常的反馈控制律,将发动机和电机功率表示成系统当前状态和车速指令的线性函数并应用于非线性实车系统.仿真结果表明,本文提出的能量管理实时控制算法可以达到良好的节油效果, 对不同的道路工况和电池初始荷电状态有良好的适应性.Abstract: Energy management strategies of hybrid electric vehicles (HEVs) based on the optimal control theory are strongly related to future driving conditions and can not solve the real-time problems of algorithms. This paper finds a new way to construct a quadratic performance index combined with rules to restrict frequent large fluctuations of the engine power, so as to indirectly reduce the fuel consumption. On the basis of the approximate linearization of HEV systems, the quadratic optimal tracking theory is utilized to derive a constant feedback control law. The control power of the engine and the motor are expressed as linear functions of current system states and commands, and then applied to the nonlinear HEV. Simulation results show that this real-time control algorithm can achieve a good oil-saving effect,and can adapt to various typical driving cycles and initial battery state of charge values.
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