Methodology for Optimal Sizing of Hybrid Power System Usingparticle Swarm Optimization and Dynamic Programming

Rui Xiong*, Hongwen He, Fengchun Sun

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

13 Citations (Scopus)

Abstract

A methodology for optimal sizing of hybrid battery-ultracapacitor power system (HPS) is presented. The purpose of the proposed methodology is to locate the optimal voltage levelfor HPS used in a plug-in hybrid electric vehicle (PHEV). A combined optimization framework for a HPS is proposed and the optimization problem is solved in a bi-level manner. The framework contains two nested optimization loops. The outer loop evaluates the selected parameters throughparticle swarm optimization (PSO) algorithm, while the inner loop generates the optimal control strategy and calculates the costs through dynamic programming (DP) algorithm. The Chinese Typical City Bus Drive Cycle (CTCBDC) has beenused to verify and evaluate the performance of the proposed methodology. The optimization result shows that higher voltage degree usually means better performance and the battery tends to provide a constant power for the HPS. It is noted that the constant powercloses to the high efficiency district of the battery and DC/DC convertor. After that the optimal result is further analyzed undervarious optimization goals andbattery charge/discharge current constrains.

Original languageEnglish
Pages (from-to)1895-1900
Number of pages6
JournalEnergy Procedia
Volume75
DOIs
Publication statusPublished - 2015
Event7th International Conference on Applied Energy, ICAE 2015 - Abu Dhabi, United Arab Emirates
Duration: 28 Mar 201531 Mar 2015

Keywords

  • HPS
  • combined optimization
  • dynamic programming
  • particle swarm optimization
  • plug-in hybrid electric vehicle

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