Adhesion Control Method Based on Fuzzy Logic Control for Four-Wheel Driven Electric Vehicle

2010 ◽  
Vol 3 (1) ◽  
pp. 217-225 ◽  
Author(s):  
Hui Chen ◽  
Jiantao Yang ◽  
Zhiqiang Du ◽  
Wei Wang
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Fuzzy Logic Control ◽  
Control Method ◽  
Logic Control ◽  
Adhesion Control

Modeling of Electric Vehicle Air Conditioning System and Analysis of Energy Consumption

2012 ◽  
Vol 516-517 ◽  
pp. 1164-1170 ◽  
Author(s):  
Jin Rui Nan ◽  
Yao Wang ◽  
Zhi Chai ◽  
Jun Kui Huang
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Electric Vehicle ◽  
Fuzzy Logic Control ◽  
Air Conditioning ◽  
Control Method ◽  
Air Conditioning System ◽  
Logic Control ◽  
Ac Motor ◽  
Total Vehicle

An simulation model for pure electric vehicle air conditioning system is established in MATLAB/ Simulink environment. The critical component of air conditioning system is selected and simulated. Fuzzy logic control method is used in AC motor controlling strategy. Combined with ADVISOR, the total vehicle energy consumption and AC energy consumption are simulated and calculated. The research indicate that by using Fuzzy logic control led AC system, the vehicle’s economcial effeciency improved. Life mileage is longer than the EV with traditional AC system and a better effect of energy saving is achieved.

DC Motor Speed Modeling and Simulation Using Fuzzy Logic Control Method

2021 ◽  
Author(s):  
Desi Fatkhi Azizah ◽  
Khen Dedes ◽  
Agung Bella Putra Utama ◽  
Aripriharta
Keyword(s):  
Fuzzy Logic ◽  
Modeling And Simulation ◽  
Fuzzy Logic Control ◽  
Control Method ◽  
Dc Motor ◽  
Motor Speed ◽  
Logic Control

Decentralized Fuzzy Logic Control of Microgrid for Electric Vehicle Charging Station

2018 ◽  
Vol 6 (2) ◽  
pp. 726-737 ◽  
Author(s):  
Pablo Garcia-Trivino ◽  
Juan P. Torreglosa ◽  
Luis M. Fernandez-Ramirez ◽  
Francisco Jurado
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Fuzzy Logic Control ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Logic Control ◽  
Vehicle Charging

Optimized Fuzzy Logic Control Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

2013 ◽  
Vol 274 ◽  
pp. 345-349 ◽  
Author(s):  
Mei Lan Zhou ◽  
Deng Ke Lu ◽  
Wei Min Li ◽  
Hui Feng Xu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Membership Functions ◽  
Logic Control

For PHEV energy management, in this paper the author proposed an EMS is that based on the optimization of fuzzy logic control strategy. Because the membership functions of FLC and fuzzy rule base were obtained by the experience of experts or by designers through the experiment analysis, they could not make the FLC get the optimization results. Therefore, the author used genetic algorithm to optimize the membership functions of the FLC to further improve the vehicle performance. Finally, simulated and analyzed by using the electric vehicle software ADVISOR, the results indicated that the proposed strategy could easily control the engine and motor, ensured the balance between battery charge and discharge and as compared with electric assist control strategy, fuel consumption and exhaust emissions have also been reduced to less than 43.84%.

scholarly journals An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Chao Tan ◽  
Rongxin Xu ◽  
Zhongbin Wang ◽  
Lei Si ◽  
Xinhua Liu
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Control Method ◽  
Improved Genetic Algorithm ◽  
Roulette Wheel Selection ◽  
Logic Control ◽  
Roulette Wheel ◽  
Manual Adjustment ◽  
Tangent Function ◽  
Memory Cutting

In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement of coal floor deformation is analyzed and a model is built. Then, the framework of proposed approach is built. Moreover, the constituents of GA such as tangent function roulette wheel selection (Tan-RWS) selection, uniform crossover, and nonuniform mutation are employed to enhance the performance of GFLC. Finally, two simulation examples and an industrial application example are carried out and the results indicate that the proposed method is feasible and efficient.

Fuzzy Logic Control Strategy for an Extended-Range Electric Vehicle

2012 ◽  
Vol 220-223 ◽  
pp. 968-972 ◽  
Author(s):  
Ji Gao Niu ◽  
Su Zhou
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
High Efficiency ◽  
Control Strategies ◽  
Vehicle Performance ◽  
Logic Control ◽  
Extended Range ◽  
Avl Cruise

This paper presents a Fuzzy Logic Control Strategy (FLCS) for an Extended-range Electric Vehicle (E-REV) with series structure. The control strategy design objective of the E-REV is fuel economy. Based on the State of Charge (SOC) of the battery and the desired power for driving, the power required by the vehicle is split between the engine/generator set and the battery by the FLCS. The engine can be operated consistently in a very high efficiency area and the SOC of the battery can be maintained at a reasonable level. Some standard driving cycles and two control strategies of Power Follower Control Strategy (PFCS) and FLCS were simulated with AVL-Cruise and Matlab/Simulink to analyze the vehicle performance. Some simulation results are compared and discussed: the FLCS indicates better performance in terms of fuel consumption.

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