Optimization of Power and Control Parameters for PHEV Based on System Efficiency

被引：0
|
作者：
Qin D. [1 ]
Lin Y. [1 ,2 ]
Liu X. [1 ]
Luo S. [1 ]
机构：
[1] State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing
[2] School of Electronic and Information Engineering, Southwest University, Chongqing
来源：
Qin, Datong (dtqin@cqu.edu.cn) | 2018年 / Hunan University卷 / 45期
关键词：
Comprehensive driving cycle; Efficiency model; Genetic algorithm; Mode switch; Parameters optimization; PHEV;
D O I：
10.16339/j.cnki.hdxbzkb.2018.02.08
中图分类号：
学科分类号：
摘要：
According to single-motor plug-in hybrid electric vehicle with Continuous Variable Transmission (CVT), a novel design method of power and control parameters was proposed. The system efficiency model for each mode of Plug-in Hybrid Electric Vehicl (PHEV) was built, the mode switching rules based on system efficiency was then obtained, and the adjustment of the mode switching rules through multiplying the mode switching curve with control parameters was realized. Fully considering the influencing factors of fuel economy, the power source, battery number and final drive ratio were regarded as the power parameters. By using Matlab/Simulink, the vehicle economy simulation model was built, and "City-Suburban-Highway-Suburban-City" comprehensive driving conditions were constructed taking the reduction of the equivalent fuel consumption as the optimization target. The PHEV dynamic parameters and controlling parameters of mode switching rules were optimized under the comprehensive driving cycle by using Genetic Algorithm (GA). The result demonstrates that, by using the method proposed in this paper, a set of reasonable power and control system parameters can be optimized to lower the vehicle equivalent fuel consumption, where the equivalent fuel consumption per 100 km can be reduced by 7.2% when compared with that of non-optimization cases. © 2018, Editorial Department of Journal of Hunan University. All right reserved.
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页码：62 / 68
页数：6
相关论文
共 13 条
  • [1] Zhou Y.S., Jia J.F., Li H.Y., Et al., Economical control strategy for a plug-in hybrid electric vehicle equipped with CVT, Journal of Hunan University(Natural Sciences), 43, 8, pp. 25-31, (2016)
  • [2] Wang Q.N., Wang G.P., Wang P.Y., Et al., Parameter matching for plug-in hybrid electric vehicle based on cost optimization, Journal of Jilin University(Engineering and Technology Edition), 46, 2, pp. 340-347, (2016)
  • [3] Tan G., Lin C., Bai Y., Et al., Multi-objective optimization of HEV transmission system parameters based on immune genetic algorithm, IEEE International Conference on Communication Problem-Solving, (2015)
  • [4] Li J., Zhu Y.Z., Xu Y.J., Et al., Research on control strategy optimization in power train transmission system of hybrid electric vehicle, Machinery Design and Manufacture, 3, pp. 138-141, (2014)
  • [5] Deng Y.W., Wang B.J., Zhang S.A., Et al., Optimization of energy management strategy of PHEV based on chaos-genetic algorithm, Journal of Hunan University(Natural Sciences), 40, 4, pp. 42-48, (2013)
  • [6] Zhan S., Qin D.T., Zeng Y.P., A study on the parameter optimization of hybrid electric vehicle based on multiple driving cycles, Automotive Engineering, 38, 8, pp. 922-928, (2016)
  • [7] Wang R.C., He R., Yu J.B., Et al., Parameter optimization of PSHEV based on genetic algorithm, China Mechanical Engineering, 24, 18, pp. 2544-2549, (2013)
  • [8] Deng T., Lin C.S., Li Y.N., Et al., A multi-objective optimization method for energy management control of hybrid electric vehicles using NSGA-Ⅱalgorithm, Journal of Xi'an Jiaotong University, 49, 10, pp. 143-150, (2015)
  • [9] Zeng Y.P., Qin D.T., Su L., Et al., Cost, fuel consumption and emission multi-objective parameter optimization for the power train of a plug-in HEV, Automotive Engineering, 38, 4, pp. 397-402, (2016)
  • [10] Zhao X.Q., Study on energy management strategy for plug-in hybrid electrical vehicle with CVT, (2014)
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