Research on Control Strategy of Hybrid Vehicle Based on ANFIS

Wen Wei, Pengcheng Liao, Jinzhan Xie, Bo Yu
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Abstract

This paper takes hybrid vehicles as the research object, research on the fuel economy of hybrid vehicles and their control strategies, train the data collected by the hybrid vehicle through the ANFIS toolbox, Takagi-Sugeno fuzzy inference algorithm was established, Fuzzy inference rules for torque allocation are generated. The optimized model of the ANFIS algorithm is imported into the vehicle model for simulation. Compared with the control strategy based on logic threshold, the simulation results show that the torque distribution of hybrid vehicles can be reasonably performed by ANFIS, and the hybrid vehicles optimized based on ANFIS algorithm can significantly improve the fuel economy of the whole vehicle, which verifies the effectiveness and practicability of the proposed control strategy.
基于ANFIS的混合动力汽车控制策略研究
本文以混合动力汽车为研究对象,研究混合动力汽车的燃油经济性及其控制策略,通过ANFIS工具箱对混合动力汽车采集的数据进行训练,建立Takagi-Sugeno模糊推理算法,生成扭矩分配的模糊推理规则。将ANFIS算法优化后的模型导入到整车模型中进行仿真。仿真结果表明,与基于逻辑阈值的控制策略相比,ANFIS可以合理地执行混合动力汽车的转矩分配,基于ANFIS算法优化的混合动力汽车可以显著提高整车的燃油经济性,验证了所提控制策略的有效性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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