Liyou Xu, Yiting Wang, Yanying Li, Jinghui Zhao, Mengnan Liu
{"title":"Research on Control Strategy of APSO-Optimized Fuzzy PID for Series Hybrid Tractors","authors":"Liyou Xu, Yiting Wang, Yanying Li, Jinghui Zhao, Mengnan Liu","doi":"10.3390/wevj14090258","DOIUrl":null,"url":null,"abstract":"Energy management strategies are crucial for improving fuel economy and reducing the exhaust emissions of hybrid tractors. The authors study a series diesel-electric hybrid tractor (SDEHT) and propose a multi-operating point Fuzzy PID control strategy (MOPFPCS) aimed to achieve better fuel economy and improved control. To further improve the vehicle economy, the adaptive particle swarm optimization method is used to optimize the key parameters of the Fuzzy PID controller. A co-simulation model in AVL-Cruise and Matlab/Simulink environment is developed for plowing mode and transportation mode. The simulation results show that under the two operation modes, the equivalent fuel consumption of the adaptive particle swarm optimization multi-operating points Fuzzy PID control strategy (APSO-MOPFPCS) is reduced by 18.3% and 15.0%, respectively, compared to the engine single-operating point control strategy (ESOPCS). Also, it was found to be reduced by 9.5% and 4.6%, respectively, compared to the MOPFPCS.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"20 1","pages":"0"},"PeriodicalIF":2.6000,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Electric Vehicle Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/wevj14090258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Energy management strategies are crucial for improving fuel economy and reducing the exhaust emissions of hybrid tractors. The authors study a series diesel-electric hybrid tractor (SDEHT) and propose a multi-operating point Fuzzy PID control strategy (MOPFPCS) aimed to achieve better fuel economy and improved control. To further improve the vehicle economy, the adaptive particle swarm optimization method is used to optimize the key parameters of the Fuzzy PID controller. A co-simulation model in AVL-Cruise and Matlab/Simulink environment is developed for plowing mode and transportation mode. The simulation results show that under the two operation modes, the equivalent fuel consumption of the adaptive particle swarm optimization multi-operating points Fuzzy PID control strategy (APSO-MOPFPCS) is reduced by 18.3% and 15.0%, respectively, compared to the engine single-operating point control strategy (ESOPCS). Also, it was found to be reduced by 9.5% and 4.6%, respectively, compared to the MOPFPCS.