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Multistage adaptive nonlinear control of battery-UC based plugin hybrid electric vehicles

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dc.contributor.author Azeem, Muhammad Kashif
dc.date.accessioned 2023-08-27T10:15:37Z
dc.date.available 2023-08-27T10:15:37Z
dc.date.issued 2020
dc.identifier.other 274243
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/37623
dc.description Supervisor: Dr. Iftikhar Ahmad Rana en_US
dc.description.abstract Plugin hybrid electric vehicles (PHEVs) are getting the attention of electric transportation market and the end-users. They comprise of smart charging mechanism and a hybrid energy storage system (HESS). In this study, a topology for HESS based on battery/ultracapacitor (UC), coupled with two bi-directional DC-DC buck-boost converters has been considered. For controlled integrated charging and smooth execution of energy management algorithm, a unidirectional DC-DC converter has been used. The mathematical model of the complete HESS with integrated charging unit for PHEV has been designed. A nonlinear controller termed as adaptive terminal sliding mode control (ATSMC) along with adaptive law has been proposed. The controller parameters have been tuned using genetic algorithm. Also an algorithm of high level control has been presented to switch between static and dynamic behaviors of the PHEV. The objective of the proposed control strategy is to adapt the unknown parameters of the system, deliver power for load well in time, output DC bus voltage regulation and smooth tracking of reference currents for the battery and UC with varying demands of the vehicle. The asymptotic stability of the system has been ensured by using Lyapunov stability theory. Finally, the energy management algorithm using the state of charge (SoC) as decisive factor is incorporated to maintain the stability of the system under varying load conditions. The performance of proposed controller has been compared with conventional sliding mode controller (SMC) and finite time synergetic controller (FTSC) using MATLAB/Simulink. The performance of the system is further verified by testing it on real-time hardware-in-loop setup. en_US
dc.language.iso en en_US
dc.publisher School of Electrical Engineering and computer Science (SEECS), NUST en_US
dc.title Multistage adaptive nonlinear control of battery-UC based plugin hybrid electric vehicles en_US
dc.type Thesis en_US


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