dSPACE Improved Direct Torque Control of Induction Motor Using Fuzzy Logic Self-Tuning Proportional Integral Regulator For Electric Vehicle Propulsion Chain

2019 ◽  
Author(s):  
Chaymae Laoufi ◽  
Ahmed Abbou ◽  
Mohammed Akherraz
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Electric Vehicle ◽  
Direct Torque Control ◽  
Torque Control ◽  
Proportional Integral ◽  
Vehicle Propulsion ◽  
Self Tuning

Fuzzy logic-based direct torque control for improvement of the fault-tolerant drive of a five-phase induction motor

2021 ◽  
pp. 014233122110155
Author(s):  
Umakanta Mahanta ◽  
Bhabesh Chandra Mohanta ◽  
Anup Kumar Panda ◽  
Bibhu Prasad Panigrahi
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fault Tolerant ◽  
Direct Torque Control ◽  
Cost Effective ◽  
Torque Ripple ◽  
Torque Control ◽  
Open Phase ◽  
Ripple Reduction ◽  
Multi Phase

Torque ripple reduction is one of the major challenges in switching table-based direct torque control (DTC) while operating for open phase faults of an induction motor, as the switching vectors are unevenly distributed. This can be minimized by increasing the level of the inverter and with the use of multi-phase motors. Fuzzy logic-based DTC is another solution to the above problem. In this paper, a comparative analysis is done between switching table-based DTC (ST-DTC) and fuzzy logic-based DTC for increasing the performance during open phase faults of a five-phase induction motor. The result shows that in fuzzy logic-based DTC with a two-level inverter, the torque ripple is reduced by 5.164% as compared with ST-DTC with a three-level inverter. The fuzzy logic-based DTC with the three-level inverter also gives better performance as compared with fuzzy logic-based DTC with the two-level inverter. The current ripple also reduced by 9.605% with respect to ST-DTC. Thus, fuzzy logic-based DTC is more suitable and cost effective for open phase fault-tolerant drives.

Investigation of Motor-Generator Integration System for Electric Vehicle Based on Induction Motor and Fuzzy Control

2011 ◽  
Vol 328-330 ◽  
pp. 2172-2180 ◽  
Author(s):  
Zhi Long Xing ◽  
Yang Liu ◽  
Yun Feng Liu
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Induction Motor ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Direct Torque Control ◽  
Torque Control ◽  
Torque Control Strategy ◽  
Ac Induction Motor

Aiming to solve the energy saving problem in modern electric vehicle, we propose a motor-generator integration control system based on the induction motor and the fuzzy control theory in this paper. A motor-generator hardware platform is built up using the four quadrant characteristic of AC induction motor. The AC induction motor works both as driving motor of the electric vehicle and as well as the energy recovery generator. Specifically, the fuzzy direct torque control strategy is adopted in the motor state, and fuzzy instantaneous torque control strategy in power generation state. A simulation is carried out to analyze the practicality of the proposed control method, the simulation results show that the fuzzy torque control technology is well performed. Finally, a simulative energy recovery experimental platform is built up to test the proposed integration control system, and results shown that the efficiency of energy recovery could be up to 97.3%.

Proportional Integral Estimator of the Stator Resistance for Direct Torque Control Induction Motor Drive

2017 ◽  
Vol 8 (4) ◽  
pp. 1631
Author(s):  
Jagdish Gangadharrao Chaudhari ◽  
Sanjay Bhauraoji Bodkhe ◽  
Mohan V. Aware
Keyword(s):  
Induction Motor ◽  
Estimation Error ◽  
Direct Torque Control ◽  
Estimation Method ◽  
Operating Conditions ◽  
Torque Control ◽  
Proportional Integral ◽  
Stator Current ◽  
Current Estimation ◽  
Stator Resistance

In this paper, an improved proportional integral stator resistance estimation for a direct torque controlled induction motor is proposed. This estimation method is based on an on-line stator resistance correction regarding the variations of the stator current estimation error. In fact, the input variable of the PI estimator is the stator current estimation error. The main idea is to tune accurately the stator resistance value relatively to the evolution of the stator current estimation error gradient to avoid the drive instability and ensure the tracking of the actual value of the stator resistance. But there is an unavoidable steady state error between the filtered stator current modulus and its estimated value from the dq model of the machine which is due to pseudo random commutations of the inverter switches. An offset has been introduced in order to overcome this problem, for different speed command values and load torques. Simulation results show that the proposed estimator was able to successfully track the actual value of the stator resistance for different operating conditions

Sign in / Sign up

Export Citation Format

Share Document