摘要
针对某新型双电机行星耦合插电式混合动力汽车(PHEV)中发动机在起停及怠速运行状态下会导致油耗增加的问题,基于等效燃油消耗最小能量管理策略,加入发动机起停优化控制模块,以进一步改善整车燃油经济性。建立了整车动力学和传动模型并加入发动机起停优化控制模块,对ECMS能量管理策略输出的发动机及电机最优目标转矩进行重新优化分配后,再输出给发动机及电机控制器以控制其工作状态。针对起停优化控制中影响起停频次的关键时间参数,采用粒子群优化算法对其进行优化。仿真结果表明,相比优化前,所提出的能量管理优化策略能够实现对发动机起停或怠速状态的有效控制,减少发动机的起停频次,减少恶化油耗,验证了本文所提出的能量管理优化策略能够进一步优化整车燃油经济性。
In order to solve the problem of fuel consumption increase of the engine in a new type of dual motors planetary coupling PHEV under start-and-stop and idle conditions,based on the minimum energy management strategy of equivalent fuel consumption,an optimization module of engine start-and-stop control is added to improve the fuel economy of the vehicle.The whole vehicle dynamics and transmission model is established,and the engine start-and-stop optimization control module is added to redistribute the optimal target torque distribution of the engine and motor output by the ECMS energy management strategy,which is then output to the engine and motor controller to control their working state.Particle swarm optimization algorithm is used to optimize the key time parameters which affect the frequency in the optimal control of start and stop.The simulation results show that the proposed energy management optimization strategy can effectively control the start-and-stop or idle state of the engine,reduce the start-and-stop frequency of the engine,and reduce fuel consumption,which verifies that the proposed energy management optimization strategy can further optimize the vehicle fuel economy.
作者
陈龙
陈智星
徐兴
王峰
蔡英凤
张涛
Chen Long;Chen Zhixing;Xu Xing;Wang Feng;Cai Yingfeng;Zhang Tao(Automotive Engineering Research Institute,Jiangsu University,Zhenjiang 212013;Bosch Innovation and Software Development Co.,Ltd.,Wuxi 214000)
出处
《汽车工程》
EI
CSCD
北大核心
2021年第3期313-322,共10页
Automotive Engineering
基金
国家重点研发计划新能源汽车专项(2017YFB0103200)
国家自然科学基金(51705204)资助。
关键词
双电机PHEV
能量管理策略
ECMS
发动机起停优化
粒子群优化算法
dual-motor planetary coupling PHEV
energy management strategy
equivalent fuel consumption minimization strategy
optimization of start-and-stop control of vehicle engine
partical swarm optimization
