By Topic

Optimal energy management for a hybrid energy storage system for electric vehicles based on Stochastic Dynamic Programming

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Romaus, C. ; Dept. of Power Electron. & Electr. Drives, Univ. of Paderborn, Paderborn, Germany ; Gathmann, K. ; Böcker, J.

For electric and hybrid electric cars, commonly nickel-metal hydride and lithium-ion batteries are used as energy storage. The size of the battery depends not only on the driving range, but also on the power demands for accelerating and braking and life-time considerations. This becomes even more apparent with short driving ranges, e.g. in commuter traffic. By hybridization of the storage, adding double layer capacitors, the battery can be relieved from the stress of peak power and even downsized to the energy demands instead of power demands. The dimensioning of the storage is performed by a parametric study via Deterministic Dynamic Programming. To determine an energy management to control the power flows to the storage online during operation which considers the stochastic influences of traffic and the driver, Stochastic Dynamic Programming is investigated and compared to the optimal strategy found during the dimensioning.

Published in:

Vehicle Power and Propulsion Conference (VPPC), 2010 IEEE

Date of Conference:

1-3 Sept. 2010