Automotive Science and Engineering
Iran University of Science & Technology
Sat, Nov 23, 2024
[Archive]
Volume 3, Issue 3 (9-2013)
ASE 2013, 3(3): 482-495 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Bostanian, Barakati M, Najjari, Mohebi Kalhori. A Genetic-Fuzzy Control Strategy for Parallel Hybrid Electric Vehicle. ASE 2013; 3 (3) :482-495
URL: http://www.iust.ac.ir/ijae/article-1-218-en.html
URL: http://www.iust.ac.ir/ijae/article-1-218-en.html
Abstract: (29775 Views)
Hybrid Electric Vehicles (HEVs) are driven by two energy convertors, i.e., an Internal Combustion (IC) engine and an electric machine. To make powertrain of HEV as efficient as possible, proper management of the energy elements is essential. This task is completed by HEV controller, which splits power between the IC engine and Electric Motor (EM). In this paper, a Genetic-Fuzzy control strategy is employed to control the powertrain. Genetic-Fuzzy algorithm is a method in which parameters of a Fuzzy Logic Controller (FLC) are tuned by Genetic algorithm. The main target of control is to minimize two competing objectives, consisting of energy cost and emissions, simultaneously. In addition, a new method to consider variations of Battery State of Charge (SOC) in the optimization algorithm is proposed. The controller performances are verified over Urban Dinamometer Driving Cycle (UDDS) and New Europian Driving Cycle (NEDC). The results demonstrate the effectiveness of the proposed method in reducing energy cost and emissions without sacrificing vehicle performance.
Type of Study: Research |
Subject:
Internal Combustion Engines (ICE, ...)
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
