Improved-GWO designed FO based type-II fuzzy controller for frequency awareness of an AC microgrid under plug in electric vehicle

2020 ◽  
Author(s):  
Prakash Chandra Sahu ◽  
Ramesh Chandra Prusty ◽  
Sidhartha Panda
Keyword(s):  
Electric Vehicle ◽  
Fuzzy Controller ◽  
Type Ii ◽  
Ac Microgrid

Improved-salp swarm optimized type-II fuzzy controller in load frequency control of multi area islanded AC microgrid

2018 ◽  
Vol 16 ◽  
pp. 380-392 ◽  
Author(s):  
Prakash Chandra Sahu ◽  
Sonalika Mishra ◽  
Ramesh Chandra Prusty ◽  
Sidhartha Panda
Keyword(s):  
Fuzzy Controller ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Type Ii ◽  
Load Frequency ◽  
Ac Microgrid

Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming

2014 ◽  
Vol 556-562 ◽  
pp. 1472-1475 ◽  
Author(s):  
Bing Dong ◽  
Yan Tao Tian ◽  
Chang Jiu Zhou
Keyword(s):  
Dynamic Programming ◽  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management System ◽  
Control Method ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Energy Management System ◽  
Fuzzy Control Strategy

This thesis puts forward one optimal adaptive fuzzy control method based on the pure electric vehicle energy management system of the fuzzy control which has been founded already. By adding an optimizing researching model based on the conventional fuzzy control strategy, the thesis can pick up the valuable control rules based on the dynamic programming theory and also can adjust the parameter of the fuzzy controller automatically according to the system operating. These can make the sum of the energy loss reduce to the min. The experiment points out that this method makes the vehicle possess good economic performance in the same driving cycle.

scholarly journals Multi-objective Parameters Optimization for HEV Based on improved Particle Swarm Algorithm

2019 ◽  
Vol 118 ◽  
pp. 02005
Author(s):  
Ying Ai ◽  
Yuanjie Gao ◽  
dongsheng Liu
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Controller ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Energy Management Strategy ◽  
Multi Objective

Hybrid electric vehicle fuel consumption and emissions are closely related to its energy management strategy. A fuzzy controller of energy management using vehicle torque request and battery state of charge (SOC) as inputs, engine torque as output is designed in this paper foe parallel hybrid electric vehicle. And a multi-objective mathematical function which purpose on maximize fuel economy and minimize emissions is also established, in order to improve the adaptive ability and the control precision of basic fuzzy controller, this paper proposed an improved particle swarm algorithm that based on dynamic learning factor and adaptive inertia weight to optimize the control parameters. Simulation results based on ADVISOR software platform show that the optimized energy management strategy has a better distribution of engine and motor torque, which helps to improved the vehicle’s fuel economy and exhaust emission performance.

Electric vehicle powertrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle

Energy ◽  
2022 ◽  
Vol 238 ◽  
pp. 121979
Author(s):  
Matheus H.R. Miranda ◽  
Fabrício L. Silva ◽  
Maria A.M. Lourenço ◽  
Jony J. Eckert ◽  
Ludmila C.A. Silva
Keyword(s):  
Electric Vehicle ◽  
Real World ◽  
Fuzzy Controller ◽  
Driving Cycle ◽  
Dynamics Simulation ◽  
Simulation Based ◽  
Vehicle Powertrain

scholarly journals Optimal Slip Ratio Based Fuzzy Control of Acceleration Slip Regulation for Four-Wheel Independent Driving Electric Vehicles

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Guodong Yin ◽  
Shanbao Wang ◽  
Xianjian Jin
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Angular Acceleration ◽  
Slip Rate ◽  
Wheel Slip ◽  
Slip Ratio ◽  
Logic Control

To improve the driving performance and the stability of the electric vehicle, a novel acceleration slip regulation (ASR) algorithm based on fuzzy logic control strategy is proposed for four-wheel independent driving (4WID) electric vehicles. In the algorithm, angular acceleration and slip rate based fuzzy controller of acceleration slip regulation are designed to maintain the wheel slip within the optimal range by adjusting the motor torque dynamically. In order to evaluate the performance of the algorithm, the models of the main components related to the ASR of the four-wheel independent driving electric vehicle are built in MATLAB/SIMULINK. The simulations show that the driving stability and the safety of the electric vehicle are improved for fuzzy logic control compared with the conventional PID control.

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