Battery and Super Capacitor Powered Energy Management Scheme for EV/HEV using Fuzzy Logic Controller and PID Controller

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Sabha Raj Arya ◽  
Shekhar Yadav ◽  
Nitesh Tiwari
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Super Capacitor ◽  
Management Scheme

scholarly journals Experts versus Algorithms? Optimized Fuzzy Logic Energy Management of Autonomous PV Hybrid Systems with Battery and H2 Storage

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1777
Author(s):  
Lisa Gerlach ◽  
Thilo Bocklisch
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Fuzzy Logic Controller ◽  
Expert Knowledge ◽  
Large Power ◽  
Hybrid Energy ◽  
Knowledge Based ◽  
Long Term Storage ◽  
Fuzzy Logic Approach

Off-grid applications based on intermittent solar power benefit greatly from hybrid energy storage systems consisting of a battery short-term and a hydrogen long-term storage path. An intelligent energy management is required to balance short-, intermediate- and long-term fluctuations in electricity demand and supply, while maximizing system efficiency and minimizing component stress. An energy management was developed that combines the benefits of an expert-knowledge based fuzzy logic approach with a metaheuristic particle swarm optimization. Unlike in most existing work, interpretability of the optimized fuzzy logic controller is maintained, allowing the expert to evaluate and adjust it if deemed necessary. The energy management was tested with 65 1-year household load datasets. It was shown that the expert tuned controller is more robust to changes in load pattern then the optimized controller. However, simple readjustments restore robustness, while largely retaining the benefits achieved through optimization. Nevertheless, it was demonstrated that there is no one-size-fits-all tuning. Especially, large power peaks on the demand-side require overly conservative tunings. This is not desirable in situations where such peaks can be avoided through other means.

scholarly journals Implementing Fuzzy Logic Controller and PID Controller to a DC Encoder Motor – “A case of an Automated Guided Vehicle”

2018 ◽  
Vol 20 ◽  
pp. 219-226 ◽  
Author(s):  
Priyam Parikh ◽  
Saurin Sheth ◽  
Rupesh Vasani ◽  
Jigar Kumar Gohil
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Automated Guided Vehicle

scholarly journals MATHEMATICAL ALGORITHM OF FUZZY LOGIC CONTROLLER FOR MULTILEVEL INVERTER CREATING VERTICAL DIVIDED VOLTAGE

2019 ◽  
Vol 59 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Erol Can
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Pid Controller ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Boost Converter ◽  
Multilevel Inverter ◽  
Logic Control ◽  
Multi Level

A 9-level inverter with a boost converter has been controlled with a fuzzy logic controller and a PID controller for regulating output voltage applications on resistive (R) and inductive (L), capacitance (C). The mathematical model of this system is created according to the fuzzy logic controlling new high multilevel inverter with a boost converter. The DC-DC boost converter and the multi-level inverter are designed and explained, when creating a mathematical model after a linear pulse width modulation (LPWM), it is preferred to operate the boost multi-level inverter. The fuzzy logic control and the PID control are used to manage the LPWM that allows the switches to operate. The fuzzy logic algorithm is presented by giving necessary mathematical equations that have second-degree differential equations for the fuzzy logic controller. After that, the fuzzy logic controller is set up in the 9-level inverter. The proposed model runs on different membership positions of the triangles at the fuzzy logic controller after testing the PID controller. After the output voltage of the converter, the output voltage of the inverter and the output current of the inverter are observed at the MATLAB SIMULINK, the obtained results are analysed and compared. The results show the demanded performance of the inverter and approve the contribution of the fuzzy logic control on multi-level inverter circuits.

scholarly journals Embedded Fuzzy Logic Controller and Wireless Communication for Home Energy Management Systems

Electronics ◽  
2018 ◽  
Vol 7 (9) ◽  
pp. 189 ◽  
Author(s):  
Aryuanto Soetedjo ◽  
Yusuf Nakhoda ◽  
Choirul Saleh
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Cost Reduction ◽  
Fuzzy Logic Controller ◽  
Management Systems ◽  
Fuzzy Membership ◽  
Membership Functions ◽  
Energy Management Systems ◽  
Fuzzy Membership Functions ◽  
Home Energy Management

Energy management systems in residential areas have attracted the attention of many researchers along the deployment of smart grids, smart cities, and smart homes. This paper presents the implementation of a Home Energy Management System (HEMS) based on the fuzzy logic controller. The objective of the proposed HEMS is to minimize electricity cost by managing the energy from the photovoltaic (PV) to supply home appliances in the grid-connected PV-battery system. A fuzzy logic controller is implemented on a low-cost embedded system to achieve the objective. The fuzzy logic controller is developed by the distributed approach where each home appliance has its own fuzzy logic controller. An automatic tuning of the fuzzy membership functions using the Genetic Algorithm is developed to improve performance. To exchange data between the controllers, wireless communication based on WiFi technology is adopted. The proposed configuration provides a simple effective technology that can be implemented in residential homes. The experimental results show that the proposed system achieves a fast processing time on a ten-second basis, which is fast enough for HEMS implementation. When tested under four different scenarios, the proposed fuzzy logic controller yields an average cost reduction of 10.933% compared to the system without a fuzzy logic controller. Furthermore, by tuning the fuzzy membership functions using the genetic algorithm, the average cost reduction increases to 12.493%.

Experimental validation of a type-2 fuzzy logic controller for energy management in hybrid electrical vehicles

2013 ◽  
Vol 26 (7) ◽  
pp. 1772-1779 ◽  
Author(s):  
Javier Solano Martínez ◽  
Jérôme Mulot ◽  
Fabien Harel ◽  
Daniel Hissel ◽  
Marie-Cécile Péra ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Experimental Validation ◽  
Fuzzy Logic Controller ◽  
Electrical Vehicles

Application of Hybrid Fuzzy-PID Control with Coupled Rules in the Hydraulic Positioning System

2012 ◽  
Vol 220-223 ◽  
pp. 402-405
Author(s):  
Li Hong Dong
Keyword(s):  
Fuzzy Logic ◽  
Hydraulic System ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Fast Response ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Positioning Control ◽  
Fuzzy Pid Controller ◽  
Hybrid Fuzzy Pid

According to the nonlinearity and time-variation of the positioning control in hydraulic system, a kind of Hybrid Fuzzy-PID Controller with Coupled Rules (HFPIDCR) is proposed. In this control system, the bulk modulus is considered as a variable. The novelty of this controller is to combine the fuzzy logic and PID controllers in a switching condition. Simulation results of the HFPIDCR are compared with the results of traditional PID, Fuzzy Logic Controller (FLC), and Hybrid Fuzzy-PID Controller (HFPID). It is demonstrated that the HFPIDCR has fast response, short adjustment time, high control precision and other advantages, and it can meet the requirements of the positioning control in hydraulic system.

Sign in / Sign up

Export Citation Format

Share Document