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

Hyung Joon Lee, Jae Kyung Shim

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number108152
JournalMechanical Systems and Signal Processing
Volume163
DOIs
Publication statusPublished - 2022 Jan 15

Keywords

  • Centrifugal pendulum vibration absorber (CPVA)
  • Dual mass flywheel (DMF)
  • Multi-objective Genetic Algorithm
  • Multibody dynamics
  • Single-shaft parallel hybrid electric vehicle (HEV) powertrain
  • Transient analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications

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