基于模糊在线识别的并联混合动力客车自适应控制策略

针对一款并联混合动力客车提出了一种基于模糊在线识别的自适应控制策略.基于自主研发的混合动力车数据采集监控系统构建符合本地车辆实际行驶道路特点的典型工况,设计模糊工况识别算法对车辆实际行驶的工况类型进行在线识别.根据最小等效燃油消耗控制算法和电池电量平衡控制方法,结合工况识别的结果调用相应最优控制参数,对发动机和电池的功率分配进行实时优化计算,实现对整车的控制.实验结果表明,所设计的模糊识别方法能够较好地完成行驶工况类型的识别.基于此所提出的自适应控制方法能够在满足车辆需求功率和电池SOC维持在有效工作区间内的前提下完成发动机和电池的最优功率分配,显著提高整车的燃油经济性. 

Adaptive Control Strategy Based on Online Fuzzy Recognition for Parallel Hybrid Electric Vehicle

An adaptive control strategy based on online fuzzy recognition was put forward for a parallel hybrid vehicle. A typical driving cycle in line with the local actual vehicle driving road conditions was constructed based on the independent research and development of the hybrid data acquisition and monitoring system. And then a fuzzy recognition algorithm was designed to carry on the on-line identification of the vehicle real driving cycle type, some corresponding optimal control parameters were taken for the real-time optimization calculation of the motor and battery power allocation based on the minimal equivalent fuel consumption control algorithm and the battery balance control method, combining with the results of condition recognition to realize the control of the whole vehicle finally. The experiment results show that the designed fuzzy recognition method can fulfill the recognition of the working condition type well, and the proposed adaptive control strategy based on this method can complete the optimal power allocation between the engine and the battery under the premise of meeting the demand of vehicle power and battery SOC maintaining within the effective working range, and can significantly improve the fuel economy of the vehicle.