Fuzzy-PID control design and performance analysis for PMSM drives in electric vehicles

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dc.contributor.authorKalyankolo, Umaru
dc.contributor.authorNafuna, Ritah
dc.contributor.authorMugabe, Rodney
dc.contributor.authorNansukusa, Yudaya
dc.contributor.authorAsikuru, Salaama
dc.contributor.authorOchima, Noah
dc.contributor.authorMutaburura, Pison
dc.contributor.authorKalyankolo, Zaina
dc.date.accessioned2026-01-06T12:19:56Z
dc.date.available2026-01-06T12:19:56Z
dc.date.issued2025-12-28
dc.descriptionThe study on advanced Fuzzy-PID control for permanent magnet synchronous motors enhances electric vehicle performance by improving stability, response time, and energy efficiency, offering potential gains for Uganda’s transport and energy sectors. By supporting the adoption of more efficient electric propulsion technologies, the research contributes to the NDP IV objectives of promoting sustainable industrial development, green technologies, and innovation. It also aligns with SDG 7 (Affordable and Clean Energy) through improved energy use, SDG 9 (Industry, Innovation and Infrastructure) by advancing technological solutions, and SDG 11 (Sustainable Cities and Communities) by supporting cleaner mobility options.
dc.description.abstractThe increasing demand for high performance and energy efficient electric vehicles has driven research into advanced motor control strategies for Permanent Magnet Synchronous Motors. This study investigates the design and performance evaluation of a Fuzzy PID controller as the speed regulator to address the limitations of the typical PID controllers in EV propulsion and a field-oriented control strategy is used. A conventional PID controller is initially implemented and tuned using the Ziegler-Nichols closed loop method. A Fuzzy Inference System is developed and then integrated with the PID controller to form a hybrid Fuzzy PID controller capable of adjusting the PID gains in real time. The performance of both controllers is evaluated under various test scenarios including speed variations, load disturbances, and parameter changes. Simulation results demonstrate that the Fuzzy PID controller significantly reduced overshoot by 0.5%, reduced rise time by 32.04%, improved settling time by 8.04%, and therefore enhanced system stability and responsiveness compared to the typical PID controller. These improvements validate the effectiveness of fuzzy logic in managing the uncertainties associated with PMSM control in EV applications.
dc.identifier.citationKalyankolo, U., Nafuna, R., Mugabe, R.,Nansukusa, Y., Asikuru, S.,Ochima, N., Mutaburura, P.,Kalyankolo, Z. (2025). Fuzzy-PID control design and performance analysis for PMSM drives in electric vehicles. Journal of Engineering, Technology, and Applied Science (JETAS), 7(3), 127-148.
dc.identifier.issn2721-8090
dc.identifier.urihttps://dir.muni.ac.ug/handle/20.500.12260/855
dc.language.isoen
dc.publisherLamintang Education and Training (LET) Centre
dc.subjectFOC
dc.subjectFuzzy Logic
dc.subjectMATLAB
dc.subjectPID Controller
dc.subjectPMSM
dc.titleFuzzy-PID control design and performance analysis for PMSM drives in electric vehicles
dc.typeArticle

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