基于道路工况分析的HEV控制策略优化方法

以某并联式混动公交车为研究对象,建立了四种典型工况模型,采用蚁群算法优化了最小等效燃油消耗控制策略中四种工况的充放电等效因子;分析了路面坡度与电池荷电状态(state of charge,SOC)目标值域调整之间的对应关系,设计了相应坡度自适应模块;提出了基于道路工况分析的混合动力汽车(hybrid electric vehicle,HEV)控制策略优化方法.典型工况下的仿真对比分析表明,该方法具有良好的工况适应能力,燃油经济性明显优于几类典型HEV控制策略.

Control Strategy Optimization Method Based on Driving Cycle Recognition for HEV

Taking a parallel hybrid bus as research object， four kinds of typical working condition models were established， and the ant colony optimization algorithm was used to optimize the charge and discharge equivalent factor for each working condition in minimal equivalent fuel consumption control strategy. The relation between road gradient and adjustment of battery SOC target range was analyzed， and the corresponding gradient adaptive module was designed. A control strategy optimization method was proposed based on driving cycle recognition for HEV. The results of simulation and comparison analysis under typical working conditions showed that the method has very well driving condition adaptability， and its fuel economy is significantly higher than that of other several typical HEV control strategies.