Next Article in Journal
On the Use of Causality Inference in Designing Tariffs to Implement More Effective Behavioral Demand Response Programs
Next Article in Special Issue
Hybrid Nonlinear MPC of a Solar Cooling Plant
Previous Article in Journal
Distributed LQR Design for a Class of Large-Scale Multi-Area Power Systems
Article Menu

Export Article

Open AccessArticle

A Firefly Algorithm Optimization-Based Equivalent Consumption Minimization Strategy for Fuel Cell Hybrid Light Rail Vehicle

1,2, 3,4, 1,2,*, 1,5 and 3,4
1
State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China
2
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China
3
Key Laboratory of Fluid and Power Machinery, Ministry of Education, Xihua University, Chengdu 610039, China
4
Key Laboratory of Automobile Measurement and Control & Safety, School of Automobile & Transportation, Xihua University, Chengdu 610039, China
5
College of Electrical and Information Engineering, Southwest Minzu University, Chengdu 610041, China
*
Author to whom correspondence should be addressed.
Energies 2019, 12(14), 2665; https://doi.org/10.3390/en12142665
Received: 3 June 2019 / Revised: 29 June 2019 / Accepted: 9 July 2019 / Published: 11 July 2019
(This article belongs to the Special Issue Optimal Control of Hybrid Systems and Renewable Energies)
  |  
PDF [4516 KB, uploaded 11 July 2019]
  |  

Abstract

To coordinate multiple power sources properly, this paper presents an optimal control strategy for a fuel cell/battery/supercapacitor light rail vehicle. The proposed strategy, which uses the firefly algorithm to optimize the equivalent consumption minimization strategy, improves the drawback that the conventional equivalent consumption minimization strategy takes insufficient account of the global performance for the vehicle. Moreover, the strategy considers the difference between the two sets of optimized variables. The optimization objective is to minimize the daily operating cost of the vehicle, which includes the total fuel consumption, initial investment, and cycling costs of power sources. The selected case study is a 100% low-floor light rail vehicle. The advantages of the proposed strategy are investigated by comparison with the operating mode control, firefly algorithm-based operating mode control, and equivalent consumption minimization strategy. In contrast to other methods, the proposed strategy shows cost reductions of up to 39.62% (from operating mode control), 18.28% (from firefly algorithm-based operating mode control), and 13.81% (from equivalent consumption minimization strategy). In addition, the proposed strategy can reduce fuel consumption and increase the efficiency of the fuel cell system. View Full-Text
Keywords: fuel cell; power control; multi-objective optimization; equivalent consumption minimization strategy; firefly algorithm; hybrid light rail vehicle fuel cell; power control; multi-objective optimization; equivalent consumption minimization strategy; firefly algorithm; hybrid light rail vehicle
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Zhang, H.; Yang, J.; Zhang, J.; Song, P.; Xu, X. A Firefly Algorithm Optimization-Based Equivalent Consumption Minimization Strategy for Fuel Cell Hybrid Light Rail Vehicle. Energies 2019, 12, 2665.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top