• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.198-206
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• 2017

This paper presents a novel scheme to estimate the rotor position of a single-phase hybrid switched reluctance motor (HSRM). The back-EMF generated by the permanent magnet (PM) field whose performance is motor parameter independent is adopted as an index to achieve the sensorless control. The differential value of back-EMF is calculated by hardware and processed by DSP to capture a fixed rotor position four times for every mechanical cycle. In addition, to accomplish the normal starting of HSRM, the determination method of the turn-off time position at the first electrical cycle is also proposed. In this way, a sensorless operation scheme with adjustable turn on/off angle can be achieved without substantial computation. The experimental verification using a prototype drive system is provided to demonstrate the viability of the proposed position estimation scheme.

• Journal of Power Electronics
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• v.18 no.2
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• pp.492-501
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• 2018

In the rotor-flux oriented control used in induction motors, the electrical parameters of the motors should be identified. Among these parameters, the mutual inductance and rotor resistance should be accurately tuned for better operations. However, they are more difficult to identify than the stator resistance and stator transient inductance. The rotor resistance and mutual inductance can change in operations due to flux saturation and heat generation. When detuning of these parameters occurs, the performance of the control is degenerated. In this paper, a novel method for the concurrent identification of the two parameters is proposed based on recursive least square estimation and model reference adaptive control.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.126-127
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• 2017

An accurate State Of Charge (SOC) estimation of battery is the most important technique for Electric Vehicles (EVs) and Energy Storage Systems (ESSs). In this paper a new integrated Unscented Kalman Filter-Particle Filter (UKF-PF) is employed to estimate the SOC of a $LiFePO_4$ battery cell and a significant improvement is obtained as compared to the other methods. The parameters of the battery is modeled by the second order Auto Regressive eXogenous (ARX) model and estimated by using Recursive Least Square (RLS) method to calculate value of each element in the model. The proposed algorithm is established by combining a parameter identification technique using RLS method with ARX model and an SOC estimation technique using UKF-PF.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.12
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• pp.630-637
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• 2002

This paper proposed a new diffusion model considering DSM rebate program's support conditions. The proposed method used some aspects of the rebate program such as support qualifications, annual support volume, and support level per appliance as following : The support qualifications were limited as the consumer which can get the rebate program's benefit, the annual support volume was constrained as the fixing budget and the support level per appliance was considered by high-efficient appliance actuality price. This paper also proposed a new method that used neural network as its parameter estimation moth[,4 for the diffusion model. The diffusion model and its parameter estimation method are expected to be able to analyze the diffusion characteristics of high-efficient appliance through the rebate program and the effects of rebate program's support conditions. Also, these will be able to evaluate the impacts and to analyze the cost-effectiveness of Energy Efficiency Demand-Side Management(EEDSM) resources. The case study is performed on the high-efficient lighting appliance rebate program of Korea by using the suggested diffusion model and estimation method and thus verified its validity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.858-865
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• 2008

In this paper, Capacitive Telemetry RF Sensor System using Recursive Least Square (RLS) algorithm was proposed. General Telemetry RF Sensor System means that it should be "wireless", "implantable" and "batterless". Conventional Telemetry RF Sensor System adopts Integrated Circuit type, but there are many defects like complexity of structure and the limitation of large power consumption in some cases. In order to overcome these disadvantages, Telemetry RF Sensor System based on inductive coupling principle was proposed in this paper. Proposed Telemetry RF Sensor System is very simple because it consists of R, L and C and measures the changes of environment like pressure and humidity in the type of capacitive value. This system adopted RLS algorithm for estimation of this capacitive parameter. For the purpose of applying RLS algorithm, proposed system was mathematically modelled with phasor method and was quasi-linearized. As two parameters such as phase and amplitude of output voltage for estimation were needed, Phase Difference Detector and Amplitude Detector were proposed respectively which were implemented using TMS320C2812 made by Texas Instrument. Finally, It is verified that the capacitance of proposed telemetry RF Sensor System using RLS algorithm can be estimated efficiently under noisy environment.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.6
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• pp.445-451
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• 2019

An input power estimation method of a three-phase inverter for the high-efficiency operation of AC motors is proposed. Measuring devices, such as DC link voltage and input current sensors, are required to obtain the input power of the inverter. In the proposed method, the input power of the inverter can be estimated without the input current sensor by using the phase current information of the AC motor and the switching pattern of the inverter. The proposed method is more robust to parameter error than conventional method. The validity of the input power estimation method is verified through experiments conducted on a 1 kW permanent-magnet synchronous motor drive system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.137-143
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• 2002

Because Block Pulse functions are used in a variety of fields such as the analysis and controller design of systems, it is necessary to find the more exact value of the Block Pulse series coefficients. This paper presents a method for the state estimation of the time-invariant linear systems via the improved estimation method for the Block Pulse coefficients by using the Simpson's rule. The proposed method using the Simpson's rule improve the accuracy of the Block Pulse coefficients.

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

• Transactions on Electrical and Electronic Materials
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• v.18 no.3
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• pp.136-140
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• 2017

The state of charge (SOC) is an important parameter in a battery-management system (BMS), and is very significant for accurately estimating the SOC of a battery. Li-ion batteries boast of excellent performance, and can only remain at their best working state by means of accurate SOC estimation that gives full play to their performances and raises their economic benefits. This paper summarizes some measures taken in SOC estimation, including the discharge experiment method, the ampere-hour integral method, the open circuit voltage method, the Kalman filter method, the neural network method, and electrochemical impedance spectroscopy (EIS. The principles of the various SOC estimation methods are introduced, and their advantages and disadvantages, as well as the working conditions adopted during these methods, are discussed and analyzed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.276-283
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• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.