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增程式混合动力洗扫车控制与仿真分析

Control and simulation analysis of extended-range hybrid sweeper truck
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摘要 针对目前国内传统双发动机洗扫车在作业工况下带来的高排放、高油耗、高噪音问题,以现有的洗扫车为原型,采用增程式混合动力系统结构,实现驱动系统与上装作业系统完全解耦,对动力系统主要部件的参数进行选型。通过AVL-Cruise软件对增程式混合动力洗扫车与传统双发动机洗扫车进行参照对比,在Matlab/Simulink平台搭建功率跟随控制策略进行联合仿真。仿真结果表明:APU能在电池SOC下降到设定的最低值开启,APU在设定的SOC上限值关闭,保证车辆的续航,使电池SOC维持在一定区间内,防止电池过充过放,延长电池寿命。在能耗方面,通过与传统双发动机洗扫车对比,增程式混合动力洗扫车在市区转场工况下节油51.5%,作业工况下节油22.2%,验证了混合动力洗扫车的燃油经济性。 Aiming at the problems of high emissions,high fuel consumption and high noise caused by the current traditional domestic dual-engine sweeper truck under operating conditions,the existing sweeper truck wre used as the prototype and the extended-range hybrid power system structure was adopted to realize the complete decoupling of the driving system and the loading operation system.The parameters of the main components of the power system were selected.The extended-range hybrid sweeper truck was built by AVL-Cruise software and compared with the traditional dual-engine sweeper truck vehicle.A power following control strategy was built on the Matlab/Simulink platform for joint simulation.Simulation results show that the APU can be turned on when the battery SOC drops to the set minimum value,and the APU can be turned off at the set SOC upper limit to ensure the endurance of the vehicle,so as keep the battery SOC within a certain range,and prevent the battery from overcharging,thereby extending battery life.In terms of energy consumption,compared with the traditional dual-engine sweeper truck,the extended-range hybrid sweeper truck can save fuel by 51.5%under urban transition conditions and 22.2%under operating conditions.Such results verified the fuel economy of the hybrid sweeper.
作者 钟勇 林宁 魏忠彬 ZHONG Yong;LIN Ning;WEI Zhongbin(Fujian Key Laboratory of Automotive Electrics and Electric Drive, Fujian University of Technology, Fuzhou 350118, China)
出处 《福建工程学院学报》 CAS 2021年第1期7-11,50,共6页 Journal of Fujian University of Technology
关键词 增程式 混合动力洗扫车 功率跟随 联合仿真 extended-range hybrid sweeper truck power following strategy joint simulation
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