International Summerschool Computer Science 2014: Proceedings of Summerschool 7.7. - 13.7.2014

Proceedings of International Summerschool Computer Science 201

Model Based Design Environment for the Embedded System Case Study: Inverter Power Supply

学位記番号：工博甲43

Performance Enhancement in Active Power Filter (APF) by FPGA Implementation

The generated electrical power in present days is not able to meet its end-user requirement as power demand is gradually increasing and expected to be increasing more in future days. In the power quality management, the parameters/factors like harmonic currents (HC) and reactive power (RP) yields the major issues in the power distribution units causing transformer heating, line losses, and machine vibration. To overcome these issues, several control mechanisms have been presented and implemented in recent past. The control algorithm based on synchronous reference frame (SRF) offers a better response by dividing the HC and RP. But the SRF based control algorithm requires better synchronization among the utility voltage and input current. To achieve this, the existing researches have used digital signal processing (DSP) and microcontroller, but these systems fail to provide better performance as they face issues like limited sampling time, less accuracy, and high computational complexity. Thus, to enhance the performance of active power filter (APF), we present an FPGA based approach. Also, to validate the performance of the proposed approach, we have used Xilinx 14.7 and Modelsim (6.3f) simulator and compared with other previous work. From the results analysis, it is found that the approach has good performance

Direct sequence spread spectrum based PWM strategy for harmonic reduction and communication

Switched mode power supplies (SMPSs) are essential components in many applications, and electromagnetic interference is an important consideration in the SMPS design. Spread spectrum based PWM strategies have been used in SMPS designs to reduce the switching harmonics. This paper proposes a novel method to integrate a communication function into spread spectrum based PWM strategy without extra hardware costs. Direct sequence spread spectrum (DSSS) and phase shift keying (PSK) data modulation are employed to the PWM of the SMPS, so that it has reduced switching harmonics and the input and output power line voltage ripples contain data. A data demodulation algorithm has been developed for receivers, and code division multiple access (CDMA) concept is employed as communication method for a system with multiple SMPSs. The proposed method has been implemented in both Buck and Boost converters. The experimental results validated the proposed DSSS based PWM strategy for both harmonic reduction and communication

DC-DC Converter Control System for the Energy Harvesting from Exercise Machines System

Current exercise machines create resistance to motion and dissipate energy as heat. Some companies create ways to harness this energy, but not cost-effectively. The Energy Harvesting from Exercise Machines (EHFEM) project reduces the cost of harnessing the renewable energy. The system architecture includes the elliptical exercise machines outputting power to DC-DC converters, which then connects to the microinverters. All microinverter outputs tie together and then connect to the grid. The control system, placed around the DC-DC converters, quickly detects changes in current, and limits the current to prevent the DC-DC converters and microinverters from entering failure states. An artificial neural network learns to mitigate incohesive microinverter and DC-DC converter actions. The DC-DC converter outputs 36 V DC operating within its specifications, but the microinverter drops input resistance looking for the sharp decrease in power that a solar panel exhibits. Since the DC-DC converter behaves according to Ohm’s Law, the inverter sees no decrease in power until the voltage drops below the microinverter’s minimum input voltage. Once the microinverter turns off, the converter regulates as intended and turns the microinverter back on only to repeat this detrimental cycle. Training the neural network with the back propagation algorithm outputs a value corresponding to the feedback voltage, which increases or decreases the voltage applied from the resistive feedback in the DC-DC converter. In order for the system to react well to changes on the order of tens of microseconds, it must read ADC values and compute the output neuron value quicker than previous control attempts. Measured voltages and currents entering and leaving the DC-DC converter constitute the neural network’s input neurons. Current and voltage sensing circuit designs include low-pass filtering to reduce software noise filtering in the interest of speed. The complete solution slightly reduces the efficiency of the system under a constant load due to additional component power dissipation, while actually increasing it under the expected varying loads

Measurements, Models, Systems and Design

531 s.

Analysis of acoustic noise spectrum of domestic induction heating systems controlled by phase-accumulator modulators

In domestic induction heating (IH) applications, the modulation technique applied to the inverter has a high influence on the acoustic noise emissions. These noise emissions must be avoided since they may be audible and annoying to the final user. This paper analyzes the acoustic noise emissions that appear when a series half-bridge resonant inverter is operated with a phase-accumulator based modulator. This modulation technique has the advantage of operating in the frequency domain, and it is compared with the classical PWM modulator regarding the audible noise generated. The frequencies of the tones in the acoustic noise spectrum are theoretically calculated from the parameters of the phaseaccumulator based modulator. The SFM (Spectral Flatness Measure) is used to quantify the number of cases in which tones are generated by the modulation. Two techniques are applied to the phase-accumulator based modulator and their effect is tested. Theoretical results are experimentally verified