• The Transactions of the Korean Institute of Power Electronics
• /
• v.17 no.3
• /
• pp.222-229
• /
• 2012

The SOC estimation method based on Kalman Filter(KF) requires the accurate battery model to express the electrical characteristics of the battery. However, the performance of KF SOC estimator can hardly be improved because of the nonlinear characteristic of the battery. This paper proposes the new KF SOC estimator of Lithium-Polymer Battery(LiPB), which considers the variation of parameters based on the hysteresis effect, the magnitude of SOC, the charging/discharging mode and the on/off load conditions. The proposed SOC estimation method is verified with the PSIM simulation combined the experimental data of the LiPB.

• Journal of Electrical Engineering and information Science
• /
• v.1 no.2
• /
• pp.119-124
• /
• 1996

Variable step size LMS(VS-LMS) algorithms improve performance of LMS algorithm by means of varying the step size. This paper presents a new VS-LMS algorithm using normalized absolute estimation error. Normalizing the estimation error to the expected valus of the desired signal, we determined the step size using the relative size of estimation error, Because parameters and computational load are less, our algorithm is easy to implement in hardware. The performance of the proposed algorithm is analyzed theoretically and estimated through simulations. Based on the theoretical analysis and computer simulations, the proposed algorithm is shown to be effective compared to conventional VS-LMS algorithms.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2005.11a
• /
• pp.47-48
• /
• 2005

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2006.11a
• /
• pp.357-360
• /
• 2006

Under sustained load, the stress variation occurs due to creep and shrinkage of concrete on the sections of steel-concrete composite girders. In standard specification for highway bridge, the method of stress estimation considering time effects is based on the concept of Yassumi method. In this study, comparing the analysis results using the AEMM and Yassumii method long-term behaviors, the rationality of specified requirements is checked.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.9
• /
• pp.865-872
• /
• 2008

Spacecraft attitude estimation using the nonlinear unscented filter is addressed to fully utilize capabilities of the unscented transformation. To release significant computational load, an efficient technique is proposed by reasonably removing correlation between random variables. This modification introduces considerable reduction of sigma points and computational burden in matrix square-root calculation for most nonlinear systems. Unscented filter technique makes use of a set of sample points to predict mean and covariance. The general QUEST(QUaternion ESTimator) algorithm preserves explicitly the quaternion normalization, whereas extended Kalman filter(EKF) implicitly obeys the constraint. For spacecraft attitude estimation based on quaternion, an approach to computing quaternion means from sampled quaternions with guarantee of the quaternion norm constraint is introduced applying a constrained optimization technique. Finally, the performance of the new approach is demonstrated using a star tracker and rate-gyro measurements.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.50 no.3
• /
• pp.101-108
• /
• 2001

Frequency is an important operating parameter of a power system. Electric power systems sustain transient frequency swings whenever the balance between generation and load does not no longer hold. To cope with this constraints, it requires an accurate and high speedy frequency deviation estimation technique and suitable adjustment to obtain the Power system energy balance. This paper describes a digital signal processing technique for measuring the operating frequency of a power system. The fundamental frequency component of 3-phase signal is first extracted by using an algorithm based on FIR filter. The rate change of the phase angle is used for estimation. To confirm the validity of the proposed algorithm, the simulation studies carried out on a typical 154KV double T/L system by using EMTP software. Some test results are presented in the paper.

• Proceedings of the KIEE Conference
• /
• 1995.11a
• /
• pp.271-273
• /
• 1995

This paper proposes the efficiency improvement method of vvcf-induction motor drives, which operates always at rated speed, regardless of load conditions, with counter emf estimation. The counter emf is estimated by detecting the fundamental component of motor input current, which is employed in speed control algorithm through the comparison with the actual counter emf during the nonconduction interval. The input power reduction by speed control is confirmed through simulations and experimental results.

• Proceedings of the KIEE Conference
• /
• 1995.07a
• /
• pp.388-390
• /
• 1995

A new control scheme based on dead beat control with adaptive parameter estimation for PWM Inverter is proposed. The proposed scheme updates dead beat control parameters continouously, and make PWM inverter excellent performance at any load or parameter condition. Simulation results show very attractive features in this proposed scheme.

• Proceedings of the KIEE Conference
• /
• 2007.11c
• /
• pp.160-164
• /
• 2007

MRAS observer, which is based on adaptive control theory, estimates speed and position by using optimal observer gains on the basis of Lyapunov stability theory. However, in case of MRAS theory, position estimation error is in existence because of non-linearity for inductance variation and limit cycles for position estimation. The adaptive sliding observer based on the variable structure control theory estimates the speed and position for zero of estimation error by using the sliding surface equal to the error between speed and position estimation. The binary observer estimates the rotor speed and rotor flux with alleviation of the high-frequency chattering, and retains the benefits achieved in the conventional sliding observer, such as robustness to parameter and disturbance variations. The speed and position sensorless control of SRM under the load and inductance variation is verified by the experimental results.

• Journal of Ubiquitous Convergence Technology
• /
• v.2 no.2
• /
• pp.78-87
• /
• 2008

Received signal strength indicator (RSSI) is used as one of the ranging techniques to locate dynamic sensor nodes in wireless sensor network. Before it can be used for position estimation, RSSI values must be converted to distances using path loss model. These distances among sensor nodes are combined using trilateration method to find position. This paper presents an idea which attempts to integrate both path loss model and trilateration as one algorithm without going through RSSI-distance conversion. This means it is not simply formulas combination but a whole new model was developed. Several advantages were found after integration: it is able to reduce processing load, and ensure that all values do not exceed the maximum range of 16-bit signed or unsigned numbers due to antilog operation in path loss model. The results also show that this method is able to reduce estimation error while inaccurate environmental parameters are used for RSSI-distance conversion.