Induction Machine-Based EV Vector Control Model Using Mamdani Fuzzy Logic Controller
Source abstract
Abstract
The substantial rise in the demand for electric vehicles (EVs) has emphasized an environment-friendly and intelligent design for speed control strategies. In this paper, a Mamdani fuzzy logic controller (MFLC) was proposed to vigorously control the speed of EVs at discrete levels. MFLC member functions (MFs) are tuned for EVs operating at three different speed modes (40, 60, and 80 km/h). The proposed speed controller operation for the speed tracking of EVs was designed and tested in MATLAB (Simulink) environment. The proposed speed controller validated a remarkable improvement in dynamic speed control compared with existing P-I, FLC, Fuzzy FOPID (ACO), Fuzzy FOPID (GA), and Fuzzy FOPID (PSO) controllers. Its stability under a user-defined drive pattern is also observed. In this proposed work, the speed controller highlights the better tracking of user-defined speed response compared to the conventional aforementioned controllers. Moreover, the speed tracking of the designed model was tested for robustness against speed transients at predefined time instants, respectively. The comparison suggests that the MFLC model removes overshoot and significantly reduces the steady-state time.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electric and Hybrid Vehicle Technologies · Electric Vehicles and Infrastructure · Advanced Battery Technologies Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Electrical Engineering Department, HITEC University, Taxila 47080, Pakistan
Department of Computer Science, MNS-University of Agriculture, Multan 59341, Pakistan
Laboratory of Intelligent Agricultural Machines and Complexes, Don State Technical University, Rostov-on-Don 344000, Russia
Laboratory of Power Supply and Heat Supply, Federal Scientific Agroengineering Center VIM, Moscow 109428, Russia
Department of Computer Science, Faisalabad Campus, University of Engineering and Technology Lahore, Faisalabad 38000, Pakistan
Funding
RF state
References (38)
Show source-provided references
1. Electric vehicle technology impacts on energy
2. En route of electric vehicles with the vehicle to grid technique in distribution networks: Status and technological review10.1002/est2.115 ↗
3. Arfeen, Z.A., Abdullah, M.P., Sheikh, U.U., Azam, M.K., Sule, A.H., Fizza, G., and Khan, M.A. (2021). Novel Supervisory Management Scheme of Hybrid Sun Empowered Grid-Assisted Microgrid for Rapid Electric Vehicles Charging Area. Appl. Sci., 11.10.3390/app11199118 ↗
4. Exploring electric vehicle charging patterns: Mixed usage of charging infrastructure10.1016/j.trd.2020.102249 ↗
5. Adaptive charging networks: A framework for smart electric vehicle charging10.1109/TSG.2021.3074437 ↗
6. Electronically Tunable ACO Based Fuzzy FOPID Controller for Effective Speed Control of Electric Vehicle10.1109/ACCESS.2021.3080086 ↗
7. Power optimisation scheme of induction motor using FLC for electric vehicle10.1049/iet-est.2019.0151 ↗
8. ANFIS controller for vector control of three phase induction motor
9. Buticchi, G., Gerada, D., Alberti, L., Galea, M., Wheeler, P., Bozhko, S., and Gerada, C. (2019). Challenges of the optimization of a high-speed induction machine for naval applications. Energies, 12.10.3390/en12122431 ↗
10. Osorio, J., Ponce, P., and Molina, A. (November, January 27). Electric Vehicle Powertrain Control with Fuzzy Indirect Vector Control. Proceedings of the 2012 11th Mexican International Conference on Artificial Intelligence, San Luis Potos, Mexico.10.1109/MICAI.2012.33 ↗
11. Performance evaluation of membership functions on fuzzy logic controlled ac voltage controller for speed control of induction motor drive
12. George, M.A., Kamat, D.V., and Kurian, C.P. (2022). Electric vehicle speed tracking control using ANFIS based fractional order PID controller. J. King Saud Univ.-Eng. Sci.
13. Design of a novel adaptive TSK-fuzzy speed controller for use in direct torque control induction motor drives10.1016/j.asoc.2015.03.008 ↗
14. Sayed, K., and Gabbar, H.A. (2016). Electric vehicle to power grid integration using three-phase three-level AC/DC converter and PI-fuzzy controller. Energies, 9.10.3390/en9070532 ↗
15. Electrical vehicle speed control by AI technique10.33130/AJCT.2021v07i02.005 ↗
16. Sahbani, A., and Mahersia, H. (2021). Advanced Driving Assistance System for an Electric Vehicle Based on Deep Learning. New Perspectives on Electric Vehicles, IntechOpen.10.5772/intechopen.98870 ↗
17. Investigation of fault modes of voltage-fed inverter system for induction motor drive10.1109/28.297920 ↗
18. A review of parameter sensitivity and adaptation in indirect vector controlled induction motor drive systems10.1109/63.97770 ↗
19. Speed control of an induction motor by using indirect vector control method
20. Indirect field-oriented torque control of induction motor considering magnetic saturation effect: Error analysis10.1049/iet-epa.2016.0680 ↗
21. Closed loop torque SVM-DTC based on robust super twisting speed controller for induction motor drive with efficiency optimization10.1016/j.ijhydene.2017.04.034 ↗
22. A comparative study between vector control and direct torque control of induction motor using optimal controller
23. Prognosis of Electric Scooter With Intermittent Faults: Dual Degradation Processes Approach10.1109/TVT.2021.3131998 ↗
24. Driving cycle development for Kuala Terengganu city using k-means method
25. Speed control of induction motors using hybrid pi plus fuzzy controller
26. Concurrent PI controller design for indirect vector controlled induction motor10.1002/asjc.1911 ↗
27. Variable Speed Vector Control for Induction Motor of Electric Vehicle10.4028/www.scientific.net/AMM.699.759 ↗
28. Numerical investigation on fuzzy logic control energy management strategy of parallel hybrid electric vehicle10.1016/j.egypro.2019.02.016 ↗
29. Advanced controllers using fuzzy logic controller (FLC) for performance improvement
30. Ahmad, N.S. (2020). Robust H∞-Fuzzy Logic Control for Enhanced Tracking Performance of a Wheeled Mobile Robot in the Presence of Uncertain Nonlinear Perturbations. Sensors, 20.10.3390/s20133673 ↗
31. Fuzzy Logic Speed Control for Three-Wheel Electric Scooter
32. Real-time range estimation in electric vehicles using fuzzy logic classifier10.1016/j.compeleceng.2020.106577 ↗
33. Fuzzy logic field oriented control of double star induction motor drive10.1007/s00202-016-0377-2 ↗
34. Direct torque control versus indirect field-oriented control of induction motors for electric vehicle applications
35. Feed-forward modeling and real-time implementation of an intelligent fuzzy logic-based energy management strategy in a series–parallel hybrid electric vehicle to improve fuel economy10.1007/s00202-019-00914-6 ↗
36. Srikanth, R., Venkatesan, M., and Subba Rao, M. (2020). Design and performance evaluation of PID, Fuzzy logic and ANN controllers based MPPTs for hybrid electric vehicle applications. Int. J. Ambient. Energy, 1–15.10.1080/01430750.2020.1846076 ↗
37. Research on Driving Control Strategy and Fuzzy Logic Optimization of a Novel Mechatronics-Electro-Hydraulic Power Coupling Electric Vehicle10.1016/j.energy.2021.121221 ↗
38. Jafari, S., Shahbazi, Z., and Byun, Y.C. (2021). Traffic Control Prediction Design Based on Fuzzy Logic and Lyapunov Approaches to Improve the Performance of Road Intersection. Processes, 9.10.3390/pr9122205 ↗