Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter

被引：7
|
作者：
Feng, Na [1 ,2 ]
Ma, Tiehua [1 ,2 ]
Chen, Changxin [1 ,2 ]
机构：
[1] North Univ China, State Key Lab Dynam Testing Technol, Taiyuan 030051, Peoples R China
[2] North Univ China, Sch Elect & Control Engn, Taiyuan 030051, Peoples R China
来源：
SN APPLIED SCIENCES | 2022年 / 4卷 / 10期
关键词：
Hybrid electric vehicle (HEV); SOC estimation; Energy management strategy; Fuzzy controller; Particle filter algorithm; PONTRYAGINS MINIMUM PRINCIPLE; ION BATTERIES; OPTIMIZATION;
D O I：
10.1007/s42452-022-05131-8
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm's effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles.
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收藏
页数：11
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