Temperatures Estimation System of Electrical Machines
on Wireless Sensor Networks
vorgelegt von
M.Sc.
Yi Huang
an der Fakultät IV - Elektrotechnik und Informatik
der Technische Universität Berlin
zur Erlangung des akademischen Grades
Doktor der Ingenieurwissenschaften
-Dr.-Ing.-
genehmigte Dissertation
Promotionsausschuss
Vorsitzender: Prof. Dr.-Ing. Reinhold Orglmeister
Gutachter: Prof. Dr.-Ing. Clemens Gühmann
Gutachter: Prof. Dr.-Ing. Uwe Schäfer
Gutachter: Prof. Dr. Ruijuan Chi
Tag der wissenschaftlichen Aussprache: 6. Juli 2020
Berlin 2021
Acknowledgments
First and foremost, I would like to express my deepest appreciation to my doctoral
thesis supervisor, professor Dr.-Ing. Clemens Gühmann, head of the chair, who has not
only granted me the precious chance to be his doctoral student but also provided me with
invaluable guidance as well as steady and strong support. I owe so much to his unwavering
encouragement, which has spurred my initiatives into full swing to reach effective fruition
and guided me through my doctoral studies.
Additionally, I am very grateful to professor Dr.-Ing. Uwe Schäfer from the Technical
University of Berlin, professor Dr.-Ing. Reinhold Orglmeister from the Technical Univer-
sity of Berlin and professor Dr. Ruijuan Chi from China Agriculture University for their
very supportive guidance. Their advice and their participation in the committee of exam-
iners must be duly acknowledged.
Next, I owe my speedy adaptation to the environment of my laboratory and extensive
comprehension of the outcome of my research to the support of all my colleagues, espe-
cially Dr.-Ing Jürgen Funck, who provided me with so much help during my research.
I must also express my appreciation to my students, Mr. Thilo Geismar, Mr. Yuan Gao,
Ms. Wenjun Zhu, Mr. Zhecheng Jin, just to name a few. They have helped me to bring my
research into a deeper level.
Last but not least, I am most thankful for the support of my family. Hearty thanks
to my parents for their unlimited spiritual support, and for bringing me up. I must also
thanks to my wife Jing Yuan, whose constant encouragement provided a source of moti-
vation throughout my studies. I also acknowledge Chinese Scholarship Council (CSC) for
granting me financial support during my Ph.D. studies.
Abstract
This dissertation proposes a model-based software method to develop a temperatures
estimation system for an asynchronous machine, which is implemented in wireless sensor
networks (WSN). The system can estimate the temperatures of the stator winding, the rotor
cage and the stator core.
Firstly, a physical model of an asynchronous machine is built and validated in Dymola.
The electrical, mechanical and the thermal behaviors performed well in the Dymola sim-
ulation model. Based on the physical model, an efficient and reliable thermal model for
tracking the temperatures of the stator winding, the rotor cage and the stator core is built
using Dymola. All the thermal parameters of the asynchronous machine are identified. One
of the most difficult tasks is to identify the reference stator core losses and reference fric-
tion losses, which can be determined by a no-load test and load test on the test bench. The
conductance values are calculated by the losses and temperatures at the steady state of the
machine. The best-fit capacitances are found by using Genopt, an optimization program.
Two different algorithms are used for the temperatures estimation. A 4th-order Kalman
filter (KF) algorithm and a 9th-order extended Kalman filter (EKF) are first implemented
based on the state-space equations in MATLAB/SIMULINK. The Model-in-the-Loop (MiL)
method is used to verify the algorithms. The physical model in Dymola and the algorithms
are connected together in the simulation using SIMULINK. After the verification of the
algorithm, both are implemented in a wireless sensor network (WSN), which is based on
the IEEE1451 standard using Contiki OS. To estimate the respective temperatures of the
stator winding, the rotor cage and the stator core of an asynchronous machine, KF and EKF
algorithms are implemented into the resource restricted embedded system.
Finally, under different experiment conditions, the temperatures estimation system in
WSN are tested on the test bench. The real-time WSN temperature estimation system is
independent from the control algorithm and functional under any load condition, as long
as the current of the stator is a nonzero system and measured with very high accuracy.
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