【作者】 李斌；

【导师】 肖仁鑫； 赵聪；

【作者基本信息】 昆明理工大学 ， 交通运输工程（专业学位）， 2021， 硕士

【摘要】 近些年由于能源危机的压力,以及环境污染的影响,各国政府加大对新能源汽车研发的力度,并且制定一系列政策促进新能源汽车市场的发展。插电式混合动力汽车结合了纯电动汽车和传统燃油车的优点,增程式电动汽车作为插电式电动汽车的一种,成为当前极具市场前景和发展潜力的新能源车型。为克服增程式电动汽车高速工况效率较低,充分利用发动机和驱动电机,本文以一款新型增程式电动汽车为研究对象,对其动力系统进行参数匹配,提出发动机三工作点控制策略和前后轴独立驱动控制策略,根据工况的不同、动力电池SOC的高低、需求功率的大小,汽车可以在不同的工作模式当中自由切换;在仿真软件中对整车进行建模和仿真,并使用多目标遗传算法对整车性能进行优化,具体的研究内容包括:(1)详细介绍了一种新型增程式电动汽车动力系统的构型,该动力系统所设计的结构包括发动机,ISG(Integrated Starter Generator)电机,驱动电机,动力电池,电机控制器,外接插头,平行轴齿轮副,第一离合器,第二离合器,第一减速器,第二减速器;平行轴齿轮副包括:输入轴、第一输出轴和第二输出轴;因此通过离合器的分离和结合,该新型增程式电动汽车可以实现前后轴独立驱动,对其动力系统结构和整车性能要求进行分析后,为了满足整车动力性,对动力系统进行参数匹配和关键零部件的选型研究,得出驱动电机、动力电池、增程器、前后轴传动比、ISG电机的参数值,为整车能量管理策略和动力系统建模奠定基础。(2)研究了基于规则的能量管理策略的基本原则,提出发动机三工作点控制策略,在发动机燃油经济性最优工作区选取三个高效的工作点,且根据需求功率的大小选择低负荷工作点、高负荷工作点以及中等负荷工作点;对动力系统结构进行优化,通过增加平行轴齿轮副和离合器,发动机在高速工况下可经过机械连接,对后轴进行直接驱动;提出了基于确定规则的能量管理策略,基于需求功率和SOC的大小来决定发动机的启停,并基于所提出车速的四个阈值大小来决定发动机工作点;按照不同的工况需求和整车动力系统的状态可将工作模式分为纯电动驱动模式、发动机直驱模式、发动机与ISG电机增程模式、发动机后驱增程模式、驱动电机前驱发动机增程模式、发动机后驱行车充电模式、混合四驱模式;最后对不同工作模式的能量流进行分析。(3)在确定能量管理策略的基本原则之后,为了降低整车开发成本,加快研究进度,在matlab/Simulink仿真平台中建立了本文所提出的前后轴独立驱动的动力系统仿真模型,设计和实现控制策略的切换阈值判断和模式选择;建立了包括动力电池、发动机、主驱动电机、驾驶员驾驶、车辆动力学、能量管理、前后驱动桥以及ISG电机动力系统模型;基于NEDC工况对本文提出的控制策略进行了仿真研究,从而验证动力系统参数匹配的准确性,验证发动机三工作点的可行性,检验控制策略的合理性,为控制策略和动力系统参数的优化提供参考。仿真结果表明,仿真车速可以很好的跟随目标车速的的变化,说明动力系统的参数能够满足动力性需求,本文所提出的控制策略能够响应工况的变化。(4)基于多目标遗传算法对动力系统参数和能量管理策略进行优化,以车辆百公里综合能耗为目标函数,将汽车的电耗等效为油耗,在NEDC工况下,以车速的第一阈值、车速的第二阈值、车速的第三阈值、车速的第四阈值、发动机工作点一的发动机功率、发动机工作点二的发动机功率、发动机工作点三的发动机功率、第一减速器的减速比、第二减速器的减速比为优化变量,通过理论计算求出优化变量的范围,并将优化变量的范围作为约束条件,得到优化之后的油耗值及参数的最优组合,优化之前的百公里综合油耗为5.6279L/100KM,优化之后的百公里综合油耗为4.0236L/100KM,油耗水平和优化之前相比降低了28.51%;对发动机工作点、驱动电机工作点进行分析,可得其工作性能均得到提升,在高效区的工作点和优化之前进行对比,可得优化后在高效区的工作点较多,较优化之前提高了15.13%,对动力电池SOC的变化曲线进行分析,可得优化后的SOC下降曲线更缓慢,通过这些仿真结果验证了优化方法的可行性,进一步得出本文提出的前后轴独立驱动的增程式电动汽车具有良好的动力性和燃油经济性。更多还原

【Abstract】 In recent years,due to the pressure of the energy crisis and the impact of environmental pollution,governments of various countries have increased their research and development of new energy vehicles and formulated a series of policies to promote the development of the new energy vehicle market.Plug-in hybrid electric vehicles combine the advantages of pure electric vehicles and traditional fuel vehicles.As a plugin electric vehicle,the extended-range electric vehicle has become a new energy vehicle with great market prospects and development potential.In order to overcome the low efficiency of the extended-range electric vehicle under high-speed conditions and make full use of the engine and drive motor,this paper takes a new range-extended electric vehicle as the research object,matches its power system parameters,and proposes the engine three operating point control strategy and front and rear control strategies.Axleindependent drive control strategy.According to different working conditions,the level of power battery SOC,and the size of the required power,the car can freely switch between different working modes;the whole vehicle is modeled and simulated in the simulation software,and used The target genetic algorithm optimizes the performance of the whole vehicle.The specific research content includes:(1)The configuration of a new extended-range electric vehicle power system is introduced in detail.The power system is designed to include an engine,an ISG(Integrated Starter Generator)motor,a drive motor,a power battery,a motor controller,an external plug,and parallel shaft gears.Pair,the first clutch,the second clutch,the first reducer,the second reducer;the parallel shaft gear pair includes: input shaft,first output shaft and second output shaft;therefore,through the separation and coupling of the clutch,the new type increases Programmable electric vehicles can achieve independent driving of the front and rear axles.After analyzing the structure of the power system and the performance requirements of the vehicle,in order to meet the dynamics of the vehicle,the power system is matched with the parameters and the key components are selected,and the drive motor,Power battery,range extender,front and rear axle transmission ratio,ISG motor parameter values,lay the foundation for vehicle energy management strategy and power system modeling.(2)The basic principle of rule-based energy management strategy was studied,and the three-point control strategy was proposed.Three efficient working points were selected from the engine fuel economy optimal working area,and the low-load working point,high-load working point and medium-load working point were selected according to the required power.The structure of the power system is optimized.By adding parallel shaft gear pair and clutch,the engine can be mechanically connected at high speed to drive the rear shaft directly.An energy management strategy based on the deterministic rule is proposed,which determines the start and stop of the engine based on the required power and the size of the SOC,and determines the operating point of the engine based on the four threshold values of the proposed speed.According to different working conditions and the status of the vehicle power system,the working modes can be divided into pure electric drive mode,engine direct drive mode,engine and ISG motor range extension mode,engine rear drive range extension mode,drive motor front drive engine range extension mode,engine rear drive vehicle charging mode,hybrid four-wheel drive mode.Finally,the energy flow of different working modes is analyzed.(3)After determining the basic principles of the energy management strategy,in order to reduce the development cost of the vehicle and speed up the research progress,the proposed dynamic system simulation model of the front and rear axle independent drive was established on the Matlab /Simulink simulation platform,and the switching threshold and mode selection of the control strategy were realized by the function function.The model includes power battery model,engine model,main drive motor model,driver driving model,vehicle dynamics model,energy management model,front and rear drive axle model and ISG motor model.The control strategy proposed in this paper is simulated based on the NEDC working condition,so as to verify the accuracy of the power system parameter matching,verify the feasibility of the three operating points of the engine,and verify the rationality of the control strategy,which provides a reference for the optimization of control strategy and power system parameters.The simulation results show that the simulation speed can well follow the change of the target speed,which indicates that the parameters of the power system can meet the demand of dynamic performance,and the control strategy proposed in this paper can respond to the change of working conditions.(4)The power system parameters and energy management strategies are optimized based on multi-objective genetic algorithm.Taking the comprehensive energy consumption of the vehicle per 100 kilometers as the objective function,the power consumption of the vehicle is equivalent to the fuel consumption.Under NEDC operating conditions,the first threshold of vehicle speed,The second threshold of vehicle speed,the third threshold of vehicle speed,the fourth threshold of vehicle speed,the engine power at engine operating point one,the engine power at engine operating point two,the engine power at engine operating point three,the reduction ratio of the first reducer,The reduction ratio of the second reducer is an optimized variable.The range of the optimized variable is calculated through theoretical calculations,and the range of the optimized variable is used as a constraint condition to obtain the optimized fuel consumption value and the optimal combination of parameters,and optimize the previous 100-kilometer integration The fuel consumption is 5.6279L/100 KM.After optimization,the comprehensive fuel consumption per 100 kilometers is4.0236L/100 KM.Compared with the optimization before,the fuel consumption level is reduced by 28.51%.Analyzing the operating point of the engine and the driving motor,it can be found that its working performance is average.After the optimization,the operating points in the high-efficiency zone are compared with those before the optimization.After optimization,there are more operating points in the high-efficiency zone,which is an increase of 15% compared to before the optimization.The change curve of the power battery SOC is analyzed,and the optimization can be obtained.The SOC decline curve of SOC is slower.These simulation results verify the feasibility of the optimization method,and further conclude that the extended-range electric vehicle with independent driving of the front and rear axles proposed in this paper has good power performance and fuel economy.更多还原