Prasanta Kundu

An energy management system for a battery ultracapacitor Hybrid Electric Vehicle

In this paper, a simple and efficient power split rule based energy management algorithm is designed for optimal sharing of energy between different energy sources in parallel HEV. This algorithm is simulated in MATLAB for Indian driving cycle (urban drive cycle) and Indian express highway drive cycle. The results indicate that the split of power can allow the engine to operate at its best efficiency and the life of battery can also be improved significantly with the introduction of ultracapacitor by maintaining the battery state of charge (SOC) within desired limits.

Simulation and Analysis of Acoustic Wave Propagation due to Partial Discharge Activity

Acoustic detection of partial discharges is based on the retrieval and analysis of mechanical signals produced by partial discharges. Acoustic method is widely used in locating partial discharge sources in transformers. For source location constant velocity of acoustic signals is used. Acoustic method also has potential to classify the partial discharges for better assessment of insulation condition. This paper presents a computer simulation of acoustic signal and analysis of its propagation behavior. It is found that acoustic velocity is not constant over distances of practical interest. An algorithm proposed for source location with distance dependent acoustic velocity leads to reduction in location error. Acoustic pulse produced by partial discharges is deformed and attenuated while propagating through transformer to sensor. This change depends on propagation distance and medium. So, frequency spectrum of sensor output AE pulse is not true representation of source pulse frequency spectrum. Partial discharge classification based on the output acoustic signal can lead to wrong classification. Knowing the location of partial discharge source, frequency dependent attenuation characteristics and output acoustic signals frequency spectrum, an estimation of input pulse frequency spectrum and its parameters is made for the classification of partial discharges

Performance analysis of hybrid energy storage system using hybrid control algorithm with BLDC motor driving a vehicle

In recent trends of hybrid electric vehicle technology, selection and efficient utilization of electrical storage system is an important issue. In this paper power electronically controlled (DC-DC converter), Ultracapacitor-battery energy storage system is proposed which supply power to the BLDC motor to drive a vehicle. Whole system is simulated in MATLAB Simulink with input as vehicle drive cycle. Speed, Torque and power requirement of vehicle are calculated using vehicle dynamics and drive cycle information. Based on above calculation, selection of energy device will take place. Ultracapacitor is controlled through buck-boost converter to absorb/supply power from/to vehicle system under deceleration/acceleration mode. A new hybrid current control algorithm is proposed for boost mode operation to minimize voltage ripple at DC bus and to avoid chaotic mode operation under variable dc input voltage from Ultracapacitor as a function of load to the converter. A PI based BLDC motor controller is proposed with new topology to recharge Ultracapacitor efficiently under regenerative mode of operation.

Frequency domain analysis of acoustic emission signals for classification of partial discharges

Online monitoring of partial discharges (PD) can reduce the risk of catastrophic failure of power apparatus. Acoustic emission technique is advantageous for online PD measurement and is adopted here. Partial discharges are classified according to the origin of discharges and their effects on insulation deterioration are also different. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for analysis. The AE signals are analyzed in frequency domain for classification. Amplitude spectrum and power spectrum of acoustic signals are examined. The frequency domain parameters calculated are frequency at peak magnitude, median frequency & percentage signal energy in frequency band. These parameters are used for classification of partial discharges.

Identification and Localization of Multi-source Partial Discharges by Acoustic Measurements in Oil-pressboard Insulation System

Partial discharges (PD) deteriorate insulation of power apparatus and lead to final failure. Early detection and localization of PD can avoid unwanted failure of power apparatus. There are different techniques for PD detection. Acoustic emission technique for partial discharge detection is advantageous for online detection and source location. Normally, acoustic PD detection and location is based on the assumption of a single PD source. But in practice, more than one source of PD is present and they may be active simultaneously in a power apparatus. This paper addresses the identification and localization of two simultaneous PD sources employing acoustic emission technique in oil pressboard insulation system. The PDAE signals from two simultaneous PD sources are analyzed using wavelet analysis with time frequency resolution and Independent Component Analysis for identification and localization.

Improved Method for Characterization of Ultracapacitor by Constant Current Charging

Ultracapacitors are creating new horizons in the field of energy storage systems (ESS). The reason behind the popularity is its unmatched characteristics like very high power density, long cycle life, deep discharge capacity, high efficiency and low ESR. Hence these types of devices can be effectively used in pulse power applications in power system, communication system and hybrid electrical vehicles. Different types of Ultracapacitor models have been analysed and proposed since many years. This paper introduces a simplified three branch dynamic model of Ultracapacitor using constant current charging method .The detailed test procedure for 150 farad and 350 farad ultracapacitors was followed in the laboratory to develop dynamic model of ultracapacitors under charging current of 5A .The model includes R-C branches along with an inductance, EPR (Equivalent Parallel Resistor) and ESR (equivalent series resistance). Ultracapacitor equivalent model is built with the consideration of linear and nonlinear factors, temperature variation & effect of leakage current. The experiment has been implemented with simple laboratory instrument like constant current supply, voltage & current data logger and computer. Computational time required for parameters calculation is minimum & simple compared to other methods followed by different authors. Final results are verified by comparing experimental results with results obtained by simulating the derived equivalent circuit model in MATLAB/Simulink. Finally some applications of ultracapacitor are discussed.

Behavior of Acoustic Partial Discharge Signal in Oil-Pressboard Insulation System

Online monitoring of partial discharges (PD) can reduce the risk of catastrophic failure of power apparatus. Acoustic emission technique is advantageous for online PD measurement. PDs are classified according to the origin of discharges and their effects on insulation deterioration are also different. Acoustic emission (AE) signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for analysis. PDAE signal propagates from source to sensor through oil and pressboard insulation. This paper discusses the effects of different thicknesses of pressboard insulation barrier on the propagation path of partial discharge acoustic emission signal. PD may occur at surface of insulation having different thickness at different voltages. This paper also discusses the effect of insulation thickness on surface discharge. The behavior of PDAE signal at different voltage level is also discussed. The AE signals are analyzed using FFT and DWT. The parameters calculated are frequency at peak magnitude & median frequency from FFT data and percentage signal energy in different frequency bands from DWT data. Effect of applied voltage beyond PD inception voltage is also examined. Acoustic PD magnitude (mV) and electrical PD magnitude (pC) relation for different electrode system is investigated.

Design and control of hybrid power supply for HEV

Energy storage is a major concern in todays hybrid vehicular technology. The HEV operates with common load profile, described by relatively high peak to average power required. The complete system demands power source to be compact, lightweight and efficient with acceptable life cycle. Power source consisting of batteries which have high energy density and ultracapacitor which have high power density, specialized for the various power segments within a vehicular operating bandwidth becomes a viable solution. Ultracapacitor(UC) stored energy is directly proportional to square of terminal voltage. Under load condition terminal voltage of UC is continuously varying, so to operate DC bus with constant voltage the power electronic interface (dc-dc buck-boost converter) is needed which allows controllable power flow with better regulation of DC bus voltage. The power flow during boost mode operation is controlled by Dynamic evaluation control algorithm. This algorithm compensates all variations in the input/output voltages and load current to maintain DC bus voltage constant with a ripple of ± 2V under continuously varying load and input voltage condition. Energy saving under regeneration improves the efficiency of the complete system. The rate of transfer of energy from load to source has been controlled using hysteresis current control scheme.

New approach of sensor positioning for optimizing source location of partial discharge

Transformers are one of the most important and costly components of any power system and thus proper monitoring of the health of a transformer is indispensable. Online monitoring of partial discharges (PD) is one of the ways by which the risk of catastrophic failure of a power apparatus can be reduced. In order to assess severity of the PD, location of the PD needs to be determined. Study of available literature shows that in case of acoustic methods of PD location, various source location algorithms have been formulated, but for their optimal implementation, it is of utmost importance to have the exact time difference of acoustically emitted (AE) signals. It has been observed that none of the experimental methods have been able to conclusively determine the exact time difference due to the complex nature of the peaks present in the experimental signals obtained. Thus it can be concluded that the experimentally obtained time difference may be only a close approximation of the exact value. Taking cognizance of this problem, usually a time range, within which the exact time difference is expected to lie, is assigned in the source location algorithm. By increasing the time range, the probability of the exact time difference lying in it increases. But increasing the time range also increases the detection of a number of points, which are not faulty, as probable PD points hence require a different approach towards PD source location. This paper proposes a method in which the acoustic sensors are placed in a helical manner, surrounding the transformer tank. The paper also establishes the fact that the proposed method is more efficient than the conventional method. Hence the errors induced in the time difference by the digital filters can be compensated by using the techniques proposed in the paper.

Classification of acoustic emission based partial discharge in oil pressboard insulation system using Fractal Features

Oil pressboard insulation used in transformer deteriorates due to partial discharge (PD). This paper reports experimental results and analysis for classification of PDs using acoustic emission (AE) signal of laboratory simulated PDs in oil pressboard insulation system using three different electrode systems. AE signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using Fractal Features. A variety of algorithms are available for computation of Fractal Dimension. In this paper, Box counting and Higuchis algorithm for the determination of fractal dimension, Lacunarity and Approximate Entropy are used for the extraction of fractal features from the time domain PD AE signals. There are significant overlaps of few features for different types of PDs. But few features are distinct for different types of PDs. These features are used for the classification PDs.