混合电力汽车动力能耗优化控制研究  

Research on power consumption optimization control of hybrid electric vehicle

作　　者：凌滨[1] 刘文川 李超[1] LING Bin;LIU Wenchuan;LI Chao(College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China)

机构地区：[1]东北林业大学机电工程学院,哈尔滨150040

出　　处：《黑龙江大学自然科学学报》2019年第2期247-252,共6页Journal of Natural Science of Heilongjiang University

基　　金：国家自然科学基金资助项目(31700643)

摘　　要：混合电力汽车的驱动功率可以分配给电机或者发动机,因此,在运行过程中获得最优的能量分配,提高整车的燃油经济性,是混合电力汽车能量控制的难点。本文以并联式混合电力汽车为研究对象,针对复杂的行车工况,提出了基于粒子群算法(Equivalent consumption minimization strategy, PSO)优化的等效燃油消耗最小策略(Particle swarm optimization, ECMS)。利用粒子群算法离线优化等效系数,建立基于PSO优化等效系数的等效燃油消耗最小的策略,实现了并联式混合电力汽车的能量实时优化控制。高级车辆仿真器软件(Advanced vehicle simulator, ADVISOR)仿真结果表明,该方法选取的等效系数合理,有效地提高了汽车燃油的经济性。The driving power of hybrid cars can be assigned to motor or engine. How to obtain the optimal energy distribution in the operation process so as to reduce the fuel economy of the vehicle is the difficult point in energy control, aiming at which, the parallel hybrid electric vehicle is studied. Facing the complex driving conditions, an equivalent fuel consumption minimization strategy is proposed based on particle swarm optimization. The equivalent consumption minimization strategy (ECMS) based on the equivalent coefficient optimization is established by using particle swarm optimization (PSO) to optimize the equivalent coefficient offline, and the real-time control strategy of parallel hybrid electric vehicle is realized. Simulating results based on Advanced Vehicle Simulator (ADVISOR) software show that the equivalent coefficient is reasonable, and the fuel economy performance can be improved.

关 键 词：混合动力汽车 ECMS 控制策略 PSO 

分 类 号：TP202[自动化与计算机技术—检测技术与自动化装置]