Methodology for optimal sizing of hybrid power system using particle swarm optimization and dynamic programming
发表时间:2021-01-20     阅读次数:     字体:【


摘要

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.


部分图片:

图1 The proposed flowchart of the optimization process.

图2 The output current of the battery and the ultracapacitor(from 3063 to 4119 seconds).

引文信息

Rui Xiong, Hongwen He, Fengchun Sun. Methodology for Optimal Sizing of Hybrid Power System Usingparticle Swarm Optimization and Dynamic Programming. 2015, 75:1895-1900. (下载链接)

其他相关论文

1. R. Xiong, H. Chen, C .Wang and F. Sun, “Towards a smarter hybrid energy storage system based on battery and ultracapacitor - a critical review on topology and energy management”, Journal of Cleaner Production, vol. 202, pp. 1228-1240, Nov 2018.(下载链接

2. R. Xiong, JY. Cao, Q.Q Yu, “Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle,” Appl Energy, vol. 211, pp. 538-548, Feb 2018. (下载链接)

3. S. Zhang, R. Xiong, JY. Cao. Battery durability and longevity based power management for plug-in hybrid electric vehicle with hybrid energy storage system. Appl Energy, vol. 179, pp. 316-328, Oct 2016. (下载链接)



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