清扫车动力系统控制策略与鸟群博弈联合优化

Joint Optimization of Sweeper Power System Control Strategy and Bird Swarm Game

构建基于加速踏板开度及其变化率、驾驶员意图、行驶车速以及SOC值等条件作用的行驶驱动系统、作业装置动力系统模糊控制模型,将清扫效率和整车能耗作为博弈双方,以满足清扫效率不低于90%和能耗最低为目标,采用鸟群-博弈多目标联合优化方法对其优化,并于NSGA-Ⅱ优化方法对比分析并求解电动清扫车多目标博弈优化模型满足目标的全局最优解,将行驶车速、盘刷转速和风机风量作为优化变量,确定电动清扫车多电机动力系统的参数匹配均衡和优化控制策略。结果表明,这两种优化方法都能提高整车节能性水平,其中,在道路垃圾量为中等水平且清扫车处于减速工况、道路垃圾量为较低水平时,鸟群-博弈多目标联合优化方法相比NSGA-Ⅱ优化方法对提高电动清扫车SOC值效果明显。

The fuzzy control model of driving system and power system of operation device is constructed based on accelerator pedal opening and its change rate,driver's intention,driving speed and SOC value.The cleaning efficiency and vehicle energy consumption are taken as the two sides of the game,and the cleaning efficiency is not less than 90%and the energy consumption is the lowest as the goal.The bird swarm game multi-objective joint optimization method is used to optimize it,and the results are analyzed Compared with NSGA-Ⅱoptimization method,the multi-objective game optimization model of electric sweeper is ana-lyzed and solved to meet the global optimal solution of the objective.Taking the driving speed,brush speed and fan air volume as optimization variables,the parameter matching equilibrium and optimization control strategy of multi motor power system of elec-tric sweeper are determined.The results show that the two optimization methods can improve the energy-saving level of the whole vehicle.When the amount of road garbage is medium,the sweeper is in deceleration condition and the amount of road garbage is low,the bird group game multi-objective joint optimization method is more effective than NSGA-Ⅱoptimization method in im-proving the SOC value of the electric sweeper.