Ride Comfort Optimization of In-Wheel-Motor Electric Vehicles with In-Wheel Vibration Absorbers

Mingchun Liu, Feihong Gu and Yuanzhi Zhang
Additional contact information
Mingchun Liu: School of Mechatronics Engineering, Nanchang University, Nanchang 330031, China
Feihong Gu: School of Automotive Engineering, Jilin University, Jilin 130022, China
Yuanzhi Zhang: School of Mechatronics Engineering, Nanchang University, Nanchang 330031, China

Energies, 2017, vol. 10, issue 10, 1-21

Abstract: This paper presents an in-wheel vibration absorber for in-wheel-motor electric vehicles (IWM EVs), and a corresponding control strategy to improve vehicle ride comfort. The proposed in-wheel vibration absorber, designed for suppressing the motor vibrations, is composed of a spring, an annular rubber bushing, and a controllable damper. The parameters of the in-wheel spring and rubber bushing are determined by an improved particle swarm optimization (IPSO) algorithm, which is executed under the typical driving conditions and can absorb vibration passively. To deal with negative interaction effects between vehicle suspension and in-wheel absorber, a linear quadratic regulator (LQR) algorithm is developed to control suspension damper, and meanwhile a fuzzy proportional-integral-derivative (PID) method is developed to control in-wheel damper as well. Through four evaluation indexes, i.e., vehicle body vertical acceleration, suspension dynamic deflection, wheel dynamic load, and motor wallop, simulation results show that, compared to the conventional electric wheel, the proposed suspension LQR control effectively improves vehicle ride comfort, and the in-wheel absorber exhibits excellent performance in terms of wheel and motor vibration suppression.

Keywords: in-wheel-motor electric vehicle; ride comfort; improved particle swarm optimization; linear quadratic regulator; fuzzy PID control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/10/1647/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/10/1647/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:10:y:2017:i:10:p:1647-:d:115613

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().