基于遗传算法的差速耦合式混合动力系统模糊控制策略优化

Optimization of Fuzzy Control Strategy for Differential Coupling Hybrid Power System Based on Genetic Algorithm

摘要: 为提高混合动力汽车的经济性和排放性能，本文基于对差速耦合式动力系统的结构和工作特征的研究，在ADVISOR仿真软件中对差速耦合式动力系统模型进行再开发，以电池电量和需求转矩为输入、发动机的启停为输出设计双输入单输出的模糊控制策略，并利用遗传算法对25个模糊规则变量进行优化，在UDDS工况下进行整车性能仿真，与逻辑门限策略下的性能进行对比。结果表明，优化后的模糊控制策略能更合理地控制汽车发动机启停，明显提高了经济性，并能有效降低汽车排放。

Abstract: In order to improve the economic performance and emission performance of hybrid vehicles, this paper is based on the study of the structure and working characteristics of the differential coupled power system. The ADVISOR simulation software is used to redevelop the model of the differential coupled power system. Two-input single-output fuzzy control strategy was designed for the input and the demand torque as input, and the engine was started and stopped. The 25 fuzzy rule varia-bles were optimized using the genetic algorithm, and the vehicle performance simulation and logic were performed under UDDS conditions. The performance was compared under the threshold strategy. The results show that the optimized fuzzy control strategy can more reasonably control the start and stop of the engine of the car, and obviously improve the economy under the premise of ensuring the power of the car, and can effectively reduce the car emissions.