Research on Control Strategy of APSO-Optimized Fuzzy PID for Series Hybrid Tractors

IF 2.6 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Liyou Xu, Yiting Wang, Yanying Li, Jinghui Zhao, Mengnan Liu
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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.
串联混合动力拖拉机模糊PID优化控制策略研究
能源管理策略对于提高混合动力拖拉机的燃油经济性和减少废气排放至关重要。以系列柴油-电动混合动力拖拉机为研究对象,提出了一种多工作点模糊PID控制策略,以达到更好的燃油经济性和更好的控制性。为了进一步提高车辆的经济性,采用自适应粒子群优化方法对模糊PID控制器的关键参数进行优化。在AVL-Cruise和Matlab/Simulink环境下建立了耕作方式和运输方式的联合仿真模型。仿真结果表明,在两种运行模式下,自适应粒子群优化多工作点模糊PID控制策略(APSO-MOPFPCS)的等效油耗比发动机单工作点控制策略(ESOPCS)分别降低18.3%和15.0%。与建交部相比,分别减少了9.5%和4.6%。
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来源期刊
World Electric Vehicle Journal
World Electric Vehicle Journal Engineering-Automotive Engineering
CiteScore
4.50
自引率
8.70%
发文量
196
审稿时长
8 weeks
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