Russian Scientists Develop Self-Tuning Algorithm for Electric Motors
The technology could help elevators and electric vehicles move more smoothly and precisely.

Scientists at Perm National Research Polytechnic University have developed a self-tuning algorithm designed to help elevators and electric vehicles operate without jerks, according to Russia’s Ministry of Science and Higher Education.
The algorithm developed by the Perm researchers adapts the regulator to the motor’s real load conditions. The controller was trained to “sense” changes in operating conditions so the algorithm can instantly adjust the current supply, allowing the motor to run smoothly without jerks.
This allows the control system to adapt even to sharp changes in load.
“Digital Observer” in Action
Sergey Storozhev, associate professor at the Automation and Telemechanics department at Perm National Research Polytechnic University and a candidate of technical sciences, added that the regulator was enhanced with a special algorithm that functions as a “digital observer.”
The effectiveness of the development was tested through computer simulation, comparing the behavior of a conventional motor and a motor using the new algorithm when the load increased sharply.
While both controllers with baseline settings produced identical results under normal load, when conditions changed the classical regulator began operating unstably, whereas the adaptive system continued to control the motor precisely, quickly and smoothly returning it to the target speed, said Alexander Yuzhakov, head of the Automation and Telemechanics department at the university and a professor with a doctorate in engineering sciences.
The new algorithm improved control quality by nearly 15%. In the future, the development could make elevators and electric vehicles smoother, and washing machines quieter and more stable. This would require only a software update in an existing microcontroller.








































