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.

Performance analysis on an air-conditioning system installed with and without a fuzzy logic thermostat in an office building

2018 ◽  
Vol 232 (8) ◽  
pp. 1079-1092 ◽  
Author(s):  
YH Yau ◽  
CP Chang
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Performance Analysis ◽  
Fuzzy Logic Control ◽  
Air Conditioning ◽  
System Simulation ◽  
Simulation Tool ◽  
Air Conditioning System ◽  
Logic Control ◽  
Transient System

The current research presents the study of the proposed thermostat setting developed in the previous work through a numerical simulation project using transient system simulation tool. The transient system simulation tool code is used to integrate the fuzzy logic to optimise a room thermostat with the multi-zone building model (Type56a). A set of equations is designed in the transient system simulation tool project to represent the fuzzy logic control system of the proposed thermostat setting. The performance analysis for the air-conditioning system installed with and without the application of the control system in terms of the operative zone temperature, the sensible cooling demand, the solar radiation, and the internal gains for a thermal zone for recent years or 2000s, and for the years 2020, 2050 and 2080 were comprehensively examined. Estimations of both predicted mean vote and predicted percentage of dissatisfied persons of the zone were also investigated. The findings indicate that a considerable amount of sensible cooling demand of approximately 8420 kJ/h or equivalent to 3.54% can be saved with the application of the proposed thermostat setting. The predicted mean vote is in the range from −0.22 to 0.72 with its average between 0.20 and 0.26 for the AC system installed with fuzzy logic control. These results further suggest that the thermal comfort of occupants can be improved taking into account their activity level, clothing insulation, indoor air temperature, air velocity, mean radiant temperature and relative humidity.

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
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