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Management Strategy Based on Genetic Algorithm Optimization for PHEV

초록

영어

Aiming at the refitted HAFEI hybrid electric vehicle (HEV), fuzzy logic energy management strategy is constructed based on genetic algorithm optimization. The difference value D between the total require torque Tr of path and the target required torque Te of engine, the intelligence quotient value with Tr is selected as the first input variable of fuzzy controller, the SOC of battery as the second input variable; torque control coefficient C is selected as output variable, meanwhile two input variable membership function is improved on genetic algorithm. To further evaluate the control strategy, dynamic programming control strategy is used as standard; the simulation experiments show that every kind of gas emission is obviously reduced by 12% to 47% in fuzzy control strategy B based on genetic algorithm optimization compared to strategy A based on determinacy rules. Compared to dynamic programming, fuel economy in strategy A is only 45.09% of standard value which is not ideal, the utilization of fuel is low and the gas emission is serious, while in strategy B fuel economy is 78.89% of standard value and effect is improved obviously.

목차

Abstract
 1. Introduction
 2. Design of Fuzzy Controller based on Particle Swarm Optimization with Compressibility Factor
  2.1. The Design Principle of Fuzzy Logic Control Strategy
  2.2. The Fuzzy Logic Control Strategy Model
  2.3. Fuzzy Logic Control Based on Genetic Algorithm Optimization
 3. Research on Dynamic Programming Control Strategy
  3.1. The PHEV Model Establishment
  3.2. PHEV Optimization Strategy Establishment
  3.3. The Simulation Experiments Test of Control Strategy
 Acknowledgement
 References

저자정보

  • Zhang Yu Department of Electrical Engineering, Harbin University of Science and Technology, Harbin 150080, China
  • Meng Dawei Department of Electrical Engineering, Harbin University of Science and Technology, Harbin 150080, China
  • Zhou Meilan Department of Electrical Engineering, Harbin University of Science and Technology, Harbin 150080, China
  • Lu Dengke Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China

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