4.6 Article

Performance Benefits of Using Inerter in Semiactive Suspensions

Journal

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 23, Issue 4, Pages 1571-1577

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2014.2364954

Keywords

Full car model; inerter; quarter car model; semiactive suspension; suboptimal control

Funding

  1. National Natural Science Foundation of China [61374053, 61203067]
  2. Hong Kong University Committee on Research and Conference Grants [201211159112]
  3. Research Grants Council, Hong Kong, through the General Research Fund [CityU 1120/14]

Ask authors/readers for more resources

This brief investigates the performance benefits of using inerter in semiactive suspensions. A novel structure for semiactive suspensions with inerter, which consists of a passive part and a semiactive part, is proposed. Six semiactive suspension struts, each of which employs an inerter in the passive part and a semiactive damper in the semiactive part, are introduced. Two suboptimal control laws named clipped optimal control and steepest gradient control laws are derived to control the damping coefficient in the semiactive part. Extensive simulations with respect to different choices of weighting factors and suspension static stiffnesses are conducted based on both a quarter car model and a full car model. The results show that, compared with the conventional semiactive suspension strut, the overall suspension performance can be significantly improved using inerters, including ride comfort, suspension deflection, and road holding. Comparative studies between these two suboptimal control laws and between these semiactive struts are also carried out to facilitate future practical application of the proposed semiactive suspensions with inerter.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available