共查询到19条相似文献,搜索用时 171 毫秒
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基于对机电控制无级变速器工作原理的分析,提出电动汽车搭载机电控制无级变速器的结构方案,并相应地建立了电机数值模型、电池充电数学模型和机电控制无级变速器速比控制模型。综合考虑电机效率、机电控制无级变速器效率、电池荷电状态和整车特性,提出了再生制动时机电控制无级变速器的变速策略。在MATLAB/Simulink仿真平台上,搭建了系统再生制动性能仿真模型,并对搭载机电控制无级变速器的电动汽车再生制动性能进行了仿真。结果表明,采用所提出的变速策略与传统两挡变速策略相比,能更好地发挥电动汽车性能,提高再生制动过程中的能量回收率。通过台架试验,验证了仿真结果的有效性。 相似文献
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采用自然坐标系下的整车动力学模型,模拟变速或转向过程中可能存在的变化情况,进行了四电动轮独立驱动的电动汽车仿真。仿真试验表明,在变速或转向的过程中,各轮的输出转矩可能会有较大差异。因此在此类电动汽车的设计中应当充分考虑对变速或转向时各轮的转矩加以控制,以提高操控性能。 相似文献
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介绍轮毂式电动汽车的发展现状及结构特点,说明了轮毂式电动汽车的转向控制模型,并对其动力性能进行了仿真。仿真研究表明,轮毂式电动汽车各项性能指标均优于传统电动汽车。 相似文献
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基于CarSim/Simulink平台,搭建四轮驱动电动汽车联合仿真控制模型,在双移线工况下,验证所建立的四轮驱动电动汽车控制仿真模型的准确性,结果显示,所建立的四轮驱动电动汽车整车模型与CarSim里B级车模型性能具有高度一致性,这说明所搭建的四轮驱动电动汽车模型具有较高精确度,同时该模型的搭建也为后续的四轮独立驱动电动汽车稳定性控制奠定研究基础。 相似文献
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针对智能驾驶车辆纵向速度跟随问题,为提高智能驾驶车辆在速度变化时的跟踪控制精度,设计了一种分层控制策略。上层控制器设计了一种基于遗传算法的PID控制器,在期望车速为恒速或变速的情况下得到最优的加速度,下层控制通过对加速踏板和制动踏板的标定,得到不同速度和加速度下节气门的开度和制动压力。建立CarSim/Simulink联合仿真模型,完成不同速度工况下的仿真验证,验证结果表明所设计的控制器有效地提高了速度跟踪精度。 相似文献
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矿区环境复杂,电传动矿用汽车的轮边电机传动系统对整车动力性、制动性及平顺性有极大影响,为了综合路面激励和电机自身激励综合分析驱动系统动态特性,采用数值仿真软件建立轮边电机传动系统模型,分析其在启动加速、平稳运行及制动时的动态特性,为了验证模型的准确性进行了实车实验。结果表明该轮边电机传动系统的输出转矩发生考虑波动转矩后会较大影响整车加速和制动性能,常见车速的加速和减速性能会减弱5%,稳定行驶阶段差别不大。刚柔耦合模型能更准确地描述驱动系统及整车动力特性,对整车的设计有指导意义。 相似文献
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S. Y. Ko J. W. Ko S. M. Lee J. S. Cheon H. S. Kim 《International Journal of Automotive Technology》2014,15(5):815-821
In this study, a vehicle velocity estimation algorithm for an in-wheel electric vehicle is proposed. This algorithm estimates the vehicle velocity using the concept of effective inertia, which is based on the motor torque, the angular velocity of each wheel and vehicle acceleration. Effective inertia is a virtual mass that changes according to the state of a vehicle, such as acceleration, deceleration, turning or driving on a low friction road. The performance of the proposed vehicle velocity estimation algorithm was verified in various conditions that included straight driving, circle driving and low friction road driving using the in-wheel electric vehicle that was equipped with an in-wheel system in each of its rear wheels. 相似文献
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《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(5):704-732
A fault classification method is proposed which has been applied to an electric vehicle. Potential faults in the different subsystems that can affect the vehicle directional stability were collected in a failure mode and effect analysis. Similar driveline faults were grouped together if they resembled each other with respect to their influence on the vehicle dynamic behaviour. The faults were physically modelled in a simulation environment before they were induced in a detailed vehicle model under normal driving conditions. A special focus was placed on faults in the driveline of electric vehicles employing in-wheel motors of the permanent magnet type. Several failures caused by mechanical and other faults were analysed as well. The fault classification method consists of a controllability ranking developed according to the functional safety standard ISO 26262. The controllability of a fault was determined with three parameters covering the influence of the longitudinal, lateral and yaw motion of the vehicle. The simulation results were analysed and the faults were classified according to their controllability using the proposed method. It was shown that the controllability decreased specifically with increasing lateral acceleration and increasing speed. The results for the electric driveline faults show that this trend cannot be generalised for all the faults, as the controllability deteriorated for some faults during manoeuvres with low lateral acceleration and low speed. The proposed method is generic and can be applied to various other types of road vehicles and faults. 相似文献
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《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(11):1555-1579
In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment. 相似文献