Electrical & Computer Engineering, Department of


First Advisor

Yi Qian

Second Advisor

Sohrab Asgarpoor

Date of this Version



H. Li, “Enhanced control algorithms in permanent magnet synchronous machines,” Ph.D. dissertation, Dept. Elect. Comput. Eng., Univ. Nebraska-Lincoln, Lincoln, NE, 2020.


A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Doctor of Philosophy, Major: Electrical Engineering, Under the Supervision of Professors Yi Qian and Sohrab Asgarpoor. Lincoln, Nebraska: August 2020

Copyright 2020 Haibo Li


Permanent magnet synchronous machines (PMSMs) are gaining increasing popularity in various applications due to their advantages, such as high efficiency, high power density, and superior control performance. A well-designed machine control algorithm is indispensable for a PMSM system to secure its good performance.

In this work, enhanced control algorithms in PMSMs are developed. Online machine current trajectory tracking, source power management, hardware overcurrent regulation, and machine current sensor fault detection and isolation (FDI) are included in the developed algorithms. The online machine current trajectory tracking ensures the maximum torque per ampere (MTPA) or maximum torque per voltage (MTPV) control in a PMSM to maximize system efficiency or torque. The source power management regulates the power flow between a power source and a PMSM to enhance the reliability of power source and PMSM subsystems. The hardware overcurrent regulation limits the maximum machine current in a PMSM to reduce overcurrent risk in power inverter and electric machine. The sensor FDI checks various machine current sensor fault scenarios in a PMSM including single and multiple machine current sensor faults under the disturbance of non-sensor fault(s) to avoid unexpected system shutdown caused by machine current sensor fault(s).

The developed enhanced control algorithms in PMSMs have the advantages of providing online machine current MTPA/MTPV trajectory tracking without offline calibration, providing enhanced hardware protection for power source, inverter and electric machine, and mitigating the impact of machine current sensor fault(s) considering non-sensor fault(s) disturbance.

Advisors: Yi Qian and Sohrab Asgarpoor