Model based development of torque control drive for induction motors for micro electric vehicles

Journal article


Al-Alawi, M. K. and Nikzadfar, K. 2022. Model based development of torque control drive for induction motors for micro electric vehicles. Automotive Science and Engineering. 12 (4), pp. 4003-4016.
AuthorsAl-Alawi, M. K. and Nikzadfar, K.
Abstract

Electric vehicles are attaining significant attention recently and the current legislation is forcing the automotive industry to electrify the productions. Regardless of electric energy accumulation technology, drive technology is one of the vital components of EVs. The motor drive technology has been mainly developed based on the application which required position/velocity control. In automotive application, however, torque control is an important aspect since the drivers have already used to drive the vehicle based on torque control approach in traditional powertrain system. In this article, a model-based approach is employed to develop a controller which can guarantee the precise control of the induction motors torque for a micro electric vehicle (EV) application regardless of operating conditions. The implementation of the control drive was conducted in MATLAB/Simulink environment, followed by Model In the Loop simulation and testing at various test conditions to confirm the robustness of the developed drive. Direct Torque Control (DTC) with optimum voltage vector selection method is employed to control the motor torque that requires fewer power electronics to process its operation and hence lowers the cost of implementation. The result shows the practicality of the designed control system and its ability to track reference torque commands. Vitally, the controlled approach shows fair abilities to control IMs to produce torque at both the motoring and regenerative modes which is a highly important requirement in electrical propulsion powertrains. Furthermore, the controller’s response time was within the industrial standard range which confirms its suitability for industrial implementation at low cost.

KeywordsElectric vehicle; Drive technology; Motor control; Induction motors; Direct Torque Control; Model based control design
Year2022
JournalAutomotive Science and Engineering
Journal citation12 (4), pp. 4003-4016
PublisherIran University of Science and Technology
ISSN2717-2023
Official URLhttp://ase.iust.ac.ir/article-1-614-en.html
Publication dates
Print05 Dec 2022
Publication process dates
Accepted05 Nov 2022
Deposited13 Apr 2023
Publisher's version
License
Output statusPublished
References

[1].Department for Business, Energy and Industrial Strategy. UK Energy In Brief 2020. UK Government, 2021.
[2].Department of Transport. Transport Energy Model Report. UK Government, 2018.
[3].Bosch. The Electric Drive: efficient, dynamic, and with zero local CO2 emissions. 2021.
[4]. Jisha, L.; Thomas, A.P. A comparative study on scalar and vector control of Induction motor drives. Proceedings of 2013 International conference on Circuits, Controls and
Communications (CCUBE), Bengaluru, India, 27-28 December 2013. IEEE: 2013. DOI: 10.1109/CCUBE.2013.6718554
[5]. Deshmukh, S..; Tiwari, N. ANN based DTC for Induction Motor Drive. IJERT 2014, 3, 1040-1044.
[6]. Ammar, A.; Benakcha, A.; Bourek, A.Closed Loop Torque SVM-DTC based on Robust Super Twisting Speed Controller of Induction Motor Drive with Efficiency Optimization. IJHYDENE 2017, 42, 17940 -17952. DOI:10.1016/j.ijhydene.2017.04.034.
[7]. Brandstetter, P.; Kuchar, M.; Vo, H.H.; Dong, C.S. Induction motor drive with PWM direct torque control. Proceedings of 18th International Scientific Conference on Electric Power Engineering (EPE), International conference on Circuits, Controls and Communications (CCUBE), Kouty nad Desnou, Czech Republic, 17-19 May 2017. IEEE: 2017. DOI: 10.1109/EPE.2017.7967268.
[8].Laskody, T.; Dobrucky, B.; Kascak, S.; Prazenica, M. 2-phase direct torque-controlled IM drive using SVPWM with torque ripple reduction: Motoring and regenerating. Proceedings of 23rd International Symposium on Industrial Electronics (ISIE), Istanbul, Turkey, 1-4 June 2014. IEEE: 2014. DOI: 10.1109/ISIE.2014.6864697.
[9].Raj, A.; Sharma, R. Improved Direct Torque Application. Proceedings of 8th I Power India International Conference (PIICON), Kurukshetra, India, 10-12 December 2018. IEEE:2018. DOI: 10.1109/POWERI.2018.8704469.
[10]. Muddineni, V.P.; Sandepudi, R.S.; Bonala,
A.K. Simplified finite control set model predictive control for induction motor drive without weighting factors. Proceedings of International Conference on Power Electronics,
Drives and Energy Systems (PEDES),Trivandrum, India, 14-17 December 2016. IEEE:2016. DOI: 10.1109/PEDES.2016.7914258. [11]. Kim, S. H. (2018) Electric Motor Control:
DC AC and BLDC Motors. Amsterdam: Elsevier. [12]. Rai, T.; Debre, P. Generalized modeling model of three phase induction motor. Proceedings of International Conference on Energy Efficient Technologies for Sustainability (ICEETS), Nagercoil, India, 7-8 April 2016.
IEEE: 2016. DOI:10.1109/ICEETS.2016.7583881.
[13].Makwana, J.A.; Agarwal, P.; Srivastava, S.K. Novel simulation approach to analyses the performance of in -wheel SRM for an Electrical Vehicle. International Conference on Energy, Automation and Signal (ICEAS), Bhubaneswar, India, 28-30 December 2011. IEEE. DOI: 10.1109/ICEAS.2011.6147103. [14]. ABB. Technical guide No. 1: Direct torque control– the world’s most advanced AC drive technology. ABB, 2011.

Permalink -

https://repository.canterbury.ac.uk/item/945vx/model-based-development-of-torque-control-drive-for-induction-motors-for-micro-electric-vehicles

Download files


Publisher's version
ase-v12n4p4003-en.pdf
License: CC BY-NC 4.0

  • 169
    total views
  • 92
    total downloads
  • 3
    views this month
  • 0
    downloads this month

Export as

Related outputs

A novel enhanced SOC estimation method for lithium-ion battery cells using cluster-based LSTM models and centroid proximity selection
Al-Alawi, M., Jaddoa, A., Cugley, J. and Hassanin, H. 2024. A novel enhanced SOC estimation method for lithium-ion battery cells using cluster-based LSTM models and centroid proximity selection. Journal of Energy Storage. 97 (B), p. 112866. https://doi.org/10.1016/j.est.2024.112866
Advancing safety and efficiency in critical infrastructure with a novel SOC estimation for battery storage systems: A focus on second life batteries
Al-Alawi, M., Cugley, J., Jaddoa, A. and Hassanin, H. 2024. Advancing safety and efficiency in critical infrastructure with a novel SOC estimation for battery storage systems: A focus on second life batteries.
Embracing sustainable farming: Unleashing the circular economy potential of second-life EV batteries in agricultural applications
Al-Alawi, M., Cugley, J. and Hassanin, H. 2023. Embracing sustainable farming: Unleashing the circular economy potential of second-life EV batteries in agricultural applications.
Using second-life batteries and solar power to help farms become energy efficient.
Al-Alawi, M., Cugley, J. and Hassanin, H. 2023. Using second-life batteries and solar power to help farms become energy efficient. Canterbury Christ Church University.
Techno-economic feasibility of retired electric-vehicle batteries repurpose/reuse in second-life applications: A systematic review
Hassanin, H., Al-Alawi, M. and Cugley, J. 2022. Techno-economic feasibility of retired electric-vehicle batteries repurpose/reuse in second-life applications: A systematic review. Energy and Climate Change. 3 (100086). https://doi.org/10.1016/j.egycc.2022.100086
Planning, operation, and design of market-based virtual power plant considering uncertainty
Hassanin, H., Ullah, Z., Arshad, Cugley, J. and Al-Alawi, M. 2022. Planning, operation, and design of market-based virtual power plant considering uncertainty. Energies. 19 (15), p. 7290. https://doi.org/10.3390/en15197290