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

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.

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.