• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.886-890
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• 2011

Induction motors are relatively cheap and rugged machines. For the vector control of induction motors, a position or speed sensor is needed. But a speed sensor increases motor cost and reduces reliability in harsh environment. Recently, many studies have been performed for sensorless speed control. This paper investigates an improved flux observer with the parameter error compensation for a sensorless induction motor. The proposed algorithm is verified through simulation and experiment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.12
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• pp.1543-1549
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• 2012

This study focuses on the state space model and the design of a state observer for the slip dynamics between rolls in STS cold cluster mills. First, a mathematical model of the roll slip is given as a nonlinear differential equation. Then, by using a Taylor series expansion, it is linearized as a state space model. Next, by using Gopinath's algorithm, a minimal-order state observer based on the state space model is designed to estimate the angular speed of all idle rolls except for an actuated roll that is measureable. Finally, a computer simulation is used to validate that the proposed state space model very well describes slip dynamics between, and moreover, the state observer very well estimates the angular speed of the idle roll.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.16-20
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• 2022

Accurate state estimation is important for autonomous driving. However, the estimation error increases in situations that a lot of longitudinal slip occurs. Therefore, this paper presents a vehicle state estimation method using an Extended Kalman Filter. The filter estimates the states of the host vehicle robust to wheel slip. It utilizes the measurements of the four-wheel rotational speeds, longitudinal acceleration, yaw-rate, and steering wheel angle. Nonlinear measurement model is represented by Ackermann Model. The main advantage of this approach is the accurate estimation of yaw rate due to the measurement of the steering wheel angle. The proposed algorithm is verified in scenarios of autonomous emergency braking (AEB), lane change (LC), lane keeping (LK) using an automated vehicle. The results show that the proposed algorithm guarantees accurate estimation in such scenarios.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1308-1316
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• 2018

Accurate tuning of parameter is very important in vector-controlled induction motor. Among the parameters of induction motor, detuning of rotor resistance used in controller design deteriorates drive performance. This paper presents a novel rotor resistance estimation strategy using slip angular velocity in vector-controlled induction motor drives. The slip angular velocity can be calculated by two methods. Firstly, it can be induced from the rotor voltage equation. Secondly, it can be induced from the difference between synchronous angular velocity and rotor angular velocity. The first method includes the rotor resistance, while the second method dose not include this parameter. From this fact, the rotor resistance can be identified by comparing the slip angular velocities in the two methods. In the tuned states of the rotor resistance, performances of flux estimator and speed drive are discussed. The simulation and experimental results are given to verify the validity of the proposed method in various situations.