0

Full Content is available to subscribers

Subscribe/Learn More  >

Uncertain Parameter Estimation Approaches for Increasing the Effectiveness of Command-Shaped Engine Restart Strategies

[+] Author Affiliations
J. Justin Wilbanks, Michael J. Leamy

Georgia Institute of Technology, Atlanta, GA

Paper No. DETC2017-67548, pp. V008T12A011; 13 pages
doi:10.1115/DETC2017-67548
From:
  • ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 8: 29th Conference on Mechanical Vibration and Noise
  • Cleveland, Ohio, USA, August 6–9, 2017
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5822-6
  • Copyright © 2017 by ASME

abstract

This paper develops recursive least-squares (RLS) and extended Kalman filtering (EKF) approaches for estimating uncertain engine friction (and other) parameters necessary for successful implementation of a two-scale command shaping (TSCS) engine restart strategy. The TSCS strategy has been developed for mitigating vibrations in conventional and hybrid electric vehicle (HEV) powertrains during internal combustion engine (ICE) restart. Implementing the TSCS strategy increases the drivability of a HEV by reducing noise, vibration, and harshness (NVH) issues associated with ICE restart during a powertrain mode transition. This is accomplished primarily, by modifying the electric machine (EM) torque profile with linear and time-varying components over multiple time scales. For full implementation, the TSCS strategy requires input parameters characterizing the ICE which may be a) difficult to quantify, and/or b) uncertain due to their dependence on engine operating temperature and other environmental considerations. RLS and EKF algorithms tailored to TSCS are presented herein for estimating these parameters. It is shown that both the RLS and EKF algorithms can be used to estimate the necessary ICE parameters and increase effectiveness of the TSCS strategy. The EKF algorithm, in particular, estimates uncertain ICE parameters with minimal measurement requirements, giving it an advantage over the presented RLS algorithm.

Copyright © 2017 by ASME

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In