智能混合动力汽车经济性自适应巡航控制策略研究

Research on Control Strategy for Hybrid Electric Vehicle's Economy-Oriented Adaptive Cruise

  • 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.

     

    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.

     

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