scholarly journals Hybrid Fuzzified-PID Controller for non-linear Control Surfaces for DC Motor to Improve the Efficiency of Electric Battery Driven Vehicles

2019 ◽  
Vol 8 (3) ◽  
pp. 2561-2568 ◽  
Keyword(s):  
Electric Vehicle ◽  
Pid Controller ◽  
Combustion Engine ◽  
Electrical Energy ◽  
Dc Motor ◽  
Lookup Table ◽  
Linear Control ◽  
Proportional Integral ◽  
Non Linear ◽  
Control Surfaces

The paper intends to deliver a structure of speed-control for electric DC motor widely being used in the electric rechargeable-battery vehicles. Electric vehicles are the need of the hour due to increasing environmental concerns and the dependency on fuels and oils. So as to promote this hybrid and electric vehicle technology and ensure its sustenance, the Ministry of Heavy Industry and Public Enterprises in the Gazette of India on 13th of March, 2015 approved the Scheme for Faster adoption and manufacture of (Hybrid &) Electric Vehicle in India referred as FAME-India under National Electric Mobility Mission (NEMM). This scheme intends to encourage the hybrid/electric motor driven vehicles in the market and also its manufacturing for the betterment of eco-system to be implemented over a period of six years till 2020. Electric-battery driven vehicle is sourced on the restricted electrical-energy delivered by the battery in circuit. Major contribution of this work is to propose control-strategy through Fuzzified-PID controller so that the performances of the electric vehicle is comparable to that of an internal combustion-engine vehicle. Feedback is the foundation of PID control. The target or the set point is compared with the resultant of the process. Then, correction is computed and applied for the difference identified. This procedure is carried on till the time recalculation is required. PID refers to the combined computation of proportional-integral-derivative. Controllers, in general do not apply all three mathematical functions. Maximum processes were being handled through the proportional-integral-terms. However, addition of derivative control for fine control plus to avoid overshoot are required. Following models: PID controller, hybrid Fuzzified-reasoning PID controllers for linear surfaces and non-linear control surfaces using n-D Lookup-Table data have been designed for a comparative study. It has been observed that hybrid model designed for non-linear control-surfaces provided better speed response and have zero steady state error. The simulation of these models is carried out using SIMULINK under varying state conditions.

A Hybrid Internal Combustion Engine/Battery Electric Passenger Car for Petroleum Displacement

1988 ◽  
Vol 202 (1) ◽  
pp. 51-64 ◽  
Author(s):  
I Foster ◽  
J R Bumby
Keyword(s):  
Internal Combustion Engine ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Electrical Energy ◽  
Internal Combustion ◽  
Hybrid Car ◽  
Environmentally Sensitive Areas ◽  
Environmentally Sensitive ◽  
Internal Combustion Engine Vehicle

This paper examines the potential of the hybrid electric vehicle in substituting petroleum fuel by broad-based electrical energy. In particular a hybrid car is considered. The way in which the powertrain can be controlled and the effect component ratings have on achieving the petroleum substitution objective are described. It is shown that a hybrid vehicle can be designed that can achieve a petroleum substitution of between 20 and 70 per cent of the equivalent internal combustion engine vehicle, be capable of entering environmentally sensitive areas and yet be capable of a range at high and intermediate speeds that is limited only by the size of its fuel tank.

Non-Linear Control of a DC Microgrid for Electric Vehicle Charging Stations

2020 ◽  
Vol 10 (2) ◽  
pp. 593 ◽  
Author(s):  
Abdelkarim Benamar ◽  
Pierre Travaillé ◽  
Jean-Michel Clairand ◽  
Guillermo Escrivá-Escrivá
Keyword(s):  
Electric Vehicle ◽  
Linear Control ◽  
Dc Microgrid ◽  
Electric Vehicle Charging ◽  
Non Linear ◽  
Vehicle Charging ◽  
Charging Stations

scholarly journals PENGGUNAAN PROPORTIONAL INTEGRAL DERIVATIVE ( PID ) CONTROLLER PADA FILTER AKTIF UNTUK MEREDAM HARMONISA AKIBAT BEBAN NON LINIER DI BALI NATIONAL GOLF RESORT

2018 ◽  
Vol 4 (2) ◽  
pp. 138
Author(s):  
I Gusti Made Widiarsana ◽  
I Wayan Rinas ◽  
I Wayan Arta Wijaya
Keyword(s):  
Electric Power ◽  
Pid Controller ◽  
Active Filter ◽  
Electric Power System ◽  
Wave Form ◽  
Proportional Integral ◽  
Linear Load ◽  
Non Linear ◽  
Non Linear Load ◽  
High Level

Bali National Golf Resort has a high level of non-linear load usage. A harmonic is emerged due to a high level of non-linear load usage which was the main problem on the quality of electric power. On the other hand, it is also lead to an adverse impact for the electric power system such as the wave form and voltage were not sinusoidal. Then, in order to reduce it, an active filter could be used as one of the best way. This research focused on the simulation of PID (Proportional Integral Derivate) Controller towards an active filter to reduce the harmonic and MATLAB R2013 software that applicated as the instrument. As the result,the usage of PID Controller on the active filter could reduce the THDi into 1.89% and THDv into 0.59 % as an average percentage at Bali National Golf Resort.

scholarly journals PID-Based Design of DC Motor Speed Control

2021 ◽  
Vol 2 (1) ◽  
pp. 7
Author(s):  
Irfan Irhamni ◽  
Riries Rulaningtyas ◽  
Riky Tri Yunardi
Keyword(s):  
Transient Response ◽  
Pid Controller ◽  
Speed Control ◽  
Dc Motor ◽  
System Response ◽  
Motor Speed ◽  
Proportional Integral ◽  
Response Data ◽  
Dc Motors

DC motor is an easy-to-apply motor but has inconsistent speed due to the existing load. PID (Proportional Integral Differential) is one of the standard controllers of DC motors. This study aimed to know the PID controller's performance in controlling the speed of a DC motor. The results showed that the PID controller could improve the error and transient response of the system response generated from DC motor speed control. Based on the obtained system response data from testing and tuning the PID parameters in controlling the speed of a DC motor, the PID controller parameters can affect the rate of a DC motor on the setpoint of 500, 1000, 1500: Kp = 0.05, Ki = 0.0198, Kd = 0.05.

scholarly journals Optimization of Proportional Integral Derivative Parameters of Brushless Direct Current Motor Using Genetic Algorithm

2020 ◽  
pp. 24-32
Author(s):  
Isaiah Adebayo ◽  
David Aborisade ◽  
Olugbemi Adetayo
Keyword(s):  
Genetic Algorithm ◽  
Direct Current ◽  
Pid Controller ◽  
Absolute Error ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Brushless Dc

Optimal performance of the Brushless Direct Current (BLDC) motor is to be realized using an efficient Proportional Integral Derivative (PID) controller. However, conventional tuning technique fails to perform satisfactorily under parameter variations, nonlinear conditions and time delay. Also using conventional technique to tune the parameters gain of the PID controller is a difficult task. To overcome these difficulties, modern heuristic optimization technique are required to optimally tune the Proportional, Integral, Derivative of the controller for optimal speed control of three phase BLDC motor. Thus, genetic algorithm (GA) based PID controller was used to achieve a high dynamic control performance. The Brushless DC Motor mathematical equation which describes the voltage and corresponding rotational angular speed and torque of the brushless DC motor was employed using electrical DC Machines theorem. The Genetic algorithm was further analyzed by adopting the three common performance indices i.e. Integral Time Absolute Error (ITAE), Integral Square Error (ISE) and Integral Absolute Error (IAE) in order to capture and compare the most suitable BLDC Motor speed and torque control characteristics. All simulations were done using MATLAB (R2018a). The simulation result showed that the system with GA-PID controller had the better system response when compared with the existing technique of ZN-PID controller.

scholarly journals Linear and Non-Linear Control Design of Skid Steer Mobile Robot on an Embedded

2018 ◽  
Vol 7 (3) ◽  
pp. 185
Author(s):  
Jharna Majumdar ◽  
Sudip C Gupta ◽  
B Prassanna Prasath
Keyword(s):  
Mobile Robot ◽  
Pid Controller ◽  
Control Design ◽  
Linear Quadratic Regulator ◽  
Performance Comparison ◽  
Linear Control ◽  
Proportional Integral Derivative ◽  
Linear Quadratic ◽  
Non Linear ◽  
Lqr Controller

A detailed approach for a linear Proportional-Integral-Derivative (PID) controller and a non-linear controller - Linear Quadratic Regulator (LQR) is discussed in this paper. By analyzing several mathematical designs for the Skid Steer Mobile Robot (SSMR), the controllers are implemented in an embedded microcontroller - Mbed LPC1768. To verify the controllers, MATLAB-Simulink is used for the simulation of both the controllers involving motors - Maxon RE40. This paper compares between PID and LQR controller along with the performance comparison between Homogenous and Non-Homogenous LQR controllers.

scholarly journals Speed Control of DC Motor Using PID and Arduino

2020 ◽  
pp. 33-37
Author(s):  
Zaw Ngwe ◽  
Aye Aye Tun
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Dc Motor ◽  
Control Parameters ◽  
Proportional Integral ◽  
Pid Algorithm ◽  
Pid Controller Design ◽  
Optimal Values ◽  
Differential Control ◽  
Selection Of

This paper is aim to research the Proportional Integral Differential (PID) controller design and selection of various Proportional, Integral and Differential control parameters. MATLAB is allows matrix manipulations, plotting of functions and data, implementation of algorithms. An additional package, Simulink, adds graphical multi-domain simulation and model-based design for dynamic and embedded systems. MATLAB is used to implement the Proportional Integral Differential (PID) controller, it is used to control the speed of DC motor and bring it at the desired speed. PID parameters Kp , Ki and Kd are finely tuned to optimal values. And then a ARDUINO UNO microcontroller is programmed by adding the finely tuned PID algorithm to control the speed of DC motor.

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