Abstract
Electric vehicles (EVs) have the main advantage of using sustainable forms of energy to operate and can be integrated into electrical power grids for better energy management. An essential part of the EV propulsion system is the type of motor used to propel the EV. Permanent magnet synchronous motors (PMSMs) have found extensive use due to various advantages such as high power density, excellent torque-to-weight ratio and smooth speed profile over the entire torque range. The objective of this paper was to improve the dynamic response in the speed profile for different driving conditions essential in EVs. This was done by using the finite control set model predictive control (FCS-MPC) algorithm for PMSM and by comparing and evaluating the control strategies of a PMSM used in an EV by taking two case studies. The classical control, namely field-oriented control (FOC), of PMSMs is slow to adopt the dynamic changes in the system. The proposed FCS-MPC algorithm for PMSMs provides an improved dynamic response and a good steady-state response for the different driving conditions shown in both cases. In addition, the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) is used to evaluate the FCS-MPC-controlled PMSM to depict its superior performance by matching its speed profile. The results are verified in the hardware in the loop strategy using OPAL-RT. Both the results confirm that the FCS-MPC algorithm, when compared with the conventional FOC, is superior in aspects of steady-state and dynamic responses for various torque and speed profiles.
Highlights
With an ever-increasing concern on the environmental impact of today’s vehicles and the limited resources of fuel available to power them, internal combustion (IC) enginepowered vehicles are slowly losing their value
Electric vehicles (EVs) are a great alternative to them due to their ability to be powered by energy generated from renewable sources such as solar, tidal, and wind energy, thereby removing their dependence on non-renewable fossil fuels
This paper focuses on evaluating the dynamic response of the finite control set model predictive control (FCS-Model predictive control (MPC)) algorithm by working on two scenarios
Summary
With an ever-increasing concern on the environmental impact of today’s vehicles and the limited resources of fuel available to power them, internal combustion (IC) enginepowered vehicles are slowly losing their value. Electric vehicles (EVs) are a great alternative to them due to their ability to be powered by energy generated from renewable sources such as solar, tidal, and wind energy, thereby removing their dependence on non-renewable fossil fuels. During acceleration while starting a vehicle, it is crucial to have high starting torque so that the vehicle can reach the top speed while driving the load. This is the region of constant torque. Once the maximum speed is reached, the vehicle operates in constant power. This puts a limit on the speed that can be attained by the vehicle while driving the given torque
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
