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Multi-objective optimization of a dual mass flywheel with centrifugal pendulum vibration absorbers in a single-shaft parallel hybrid electric vehicle powertrain for torsional vibration reduction

机译:单轴平行混合动力电动汽车动力系中具有离心摆动吸收器的双重批量飞轮的多目标优化,用于扭转减振

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摘要

This research deals with an optimization of a dual mass flywheel (DMF) with centrifugal pendulum vibration absorbers (CPVAs) used in a single-shaft parallel hybrid electric vehicle (HEV) powertrain for the reduction of the torsional vibration at the rotor of the electric motor and the total moment of inertia of the DMF and CPVAs. Unlike the previous studies, this research considers the overall behavior of an entire powertrain with an in-line four-cylinder engine and a five-speed automatic transmission for the optimization of the DMF with CPVAs. For this purpose, the multibody dynamics model of the HEV powertrain is constructed and used to analyze the transient response of the system for a given gas pressure map and acceleration condition of the vehicle. Then, a multi-objective genetic algorithm is applied to determine the Pareto optimal front that yields the design parameter values of the DMF and CPVAs effective in the torsional vibration reduction and inertia minimization. The result of the optimization is compared with the HEV powertrain system with a flywheel only, and shows that the vibrations transmitted to the motor are significantly reduced in all the solutions of the Pareto front. By using the method proposed in this research, various parameter combinations of the DMF and CPVAs can be considered in the early design process.
机译:该研究涉及具有在单轴平行混合动力电动车(HEV)动力系中的离心摆振吸收器(CPVA)的双质量飞轮(DMF)的优化,用于减小电动机转子处的扭转振动以及DMF和CPVA的总惯性矩。与以前的研究不同,该研究考虑了整个动力总成的整体行为,具有在线四缸发动机和五速自动变速器,用于使用CPVA优化DMF。为此目的,构建HEV动力系的多体动力学模型,并用于分析系统的瞬态响应,用于给定的气体压力图和车辆的加速度条件。然后,应用多目标遗传算法来确定Pareto最佳前端,从而产生DMF和CPVA的设计参数值,其有效地在扭转减振和惯性最小化。将优化的结果与仅具有飞轮的HEV动力系系统进行比较,并且表明在帕累托前部的所有解决方案中显着降低了传递到电动机的振动。通过使用本研究中提出的方法,可以在早期设计过程中考虑DMF和CPVA的各种参数组合。

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