• International Journal of Automotive Technology
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• 제8권5호
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• pp.563-573
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• 2007

Optimal design of an automotive catalytic converter for minimization of cold-start emissions is numerically performed using a micro genetic algorithm for two optimization problems: optimal geometry design of the monolith for various operating conditions and optimal axial catalyst distribution. The optimal design process considered in this study consists of three modules: analysis, optimization, and control. The analysis module is used to evaluate the objective functions with a one-dimensional single channel model and the Romberg integration method. It obtains new design variables from the control module, produces the CO cumulative emissions and the integral value of a catalyst distribution function over the monolith volume, and provides objective function values to the control module. The optimal design variables for minimizing the objective functions are determined by the optimization module using a micro genetic algorithm. The control module manages the optimal design process that mainly takes place in both the analysis and optimization modules.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.227-242
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• 2015

This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1626-1634
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• 2015

LCL filters are widely used in three-phase PWM converter for its advantages of small volume, low cost and inhibition of high frequency current harmonic. However, it is difficult to optimize its design because its parameters are mutually influenced while the value of each parameter for LCL filter has impacts on the converter's cost and size. In this paper, the target of optimization is to minimize the parameter values of LCL filter, and an optimization method for parameters of LCL filter of three-phase PWM converter based on least square method is proposed. With this method, a quantitative calculation of the harmonic component of the converter’s side phase voltage is performed first, and then the quantitative relationship between phase voltage harmonics and grid phase current harmonics is analyzed. After that, the attenuation requirement of each harmonic is obtained by taking into account the requirements for each harmonic component of grid current. Then according to the optimization objective, the objective function with minimum harmonic attenuation deviation is established, and least squares method is adopted for three-dimensional global searching of parameters for LCL filter. Thus, the designed harmonic attenuation curve approximates the minimum attenuation requirements, and the optimized LCL filter parameters are obtained. Finally, the effectiveness of the method is verified by the experiments.

• 한국자동차공학회논문집
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• 제20권5호
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• pp.145-151
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• 2012

New design of catalytic converter is proposed by optimization of DFSS (Design For Six Sigma) and DOE (Design Of Experiment) method which is based on taguchi matrix. As a result of the optimization of design of catalytic converter, this paper classifies Exhaust-downpipe shapes with 3 parameters to increase flow velocity uniformity of front catalytic substrate face from CFD results. after finishing with L9 Taguchi test matrix, it can be found the main effect of each design parameter of concept model, and optimal design level. in conclusion, it can be increase flow uniformity from 0.60 upto 0.80 with optimal diffuser shape for Turbo-charger.

• Journal of Power Electronics
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• 제16권2호
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• pp.610-620
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• 2016

The compound active clamp zero voltage soft switching (CACZVS) three-phase power factor correction (PFC) converter has many advantages, such as high efficiency, high power factor, bi-directional energy flow, and soft switching of all the switches. Triple closed-loop PI controllers are used for the three-phase power factor correction converter. The control objectives of the converter include a fast transient response, high accuracy, and unity power factor. There are six parameters of the controllers that need to be tuned in order to obtain multi-objective optimization. However, six of the parameters are mutually dependent for the objectives. This is beyond the scope of the traditional experience based PI parameters tuning method. In this paper, an improved chaotic particle swarm optimization (CPSO) method has been proposed to optimize the controller parameters. In the proposed method, multi-dimensional chaotic sequences generated by spatiotemporal chaos map are used as initial particles to get a better initial distribution and to avoid local minimums. Pareto optimal solutions are also used to avoid the weight selection difficulty of the multi-objectives. Simulation and experiment results show the effectiveness and superiority of the proposed method.

• Journal of Power Electronics
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• 제15권2호
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• pp.479-486
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• 2015

The application of soft-switching techniques is increasing in the DC/DC converter area. It is important to design soft-switching parameters to ensure the converter operates properly and efficiently. An optimized design method is presented in this paper. The objective function is the total power loss of a converter, while the variables are soft-switching parameters and the constraints are the electrical requirements for soft-switching. Firstly, a response surface methodology (RSM) model with a high precision is built, and the rough optimized parameters can be obtained with the help of a genetic algorithm (GA) in the solution space determined by the constraints. Secondly, a re-optimization is conducted with a SPICE model and a GA, and accurate optimized parameters can be obtained. Simulation and experiment results show that the proposed method performs well in terms of a wide adaptability, efficiency, and global optimization.

• 한국CDE학회논문집
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• 제12권3호
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• pp.163-170
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• 2007

A torque converter, connected to a transmission/transaxle input shaft, connects, multiplies and interrupts the flow of engine torque into the transmission. Damper springs are usually equipped in a torque converter to convert stably the torque power supplied from engine. Damper Springs generally have the most flexible design variables among vehicle transmission parts, so that they could be effective design factors to improve the entire vehicle's performance. Damper spring, however, has geometric complexity after it equipped in a torque converter. For that reason, modeling a damper spring requires expert's knowledge to determine many design parameters and satisfy the functional requirements at the same time. In this paper, we introduce an optimum design method applied in detailed-design stage to reduce design process and financial loss caused by adequate design. Many design variables have to be classified and structuralized for Optimization. This also could make designer concentrate on functional requirements of damper spring, not on design possibility. In addition, modeling an assembled spring has technical restriction with primitives of the current major CAD solutions because of complexity of assembled spring shape. Thus, one of modeling solution presented in this paper since detailed and exact modeling is important for CAE or DMU.

• Journal of Power Electronics
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• 제11권5호
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• pp.621-631
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• 2011

In space qualified DC-DC converters, optimization of the following electrical characteristics is of greater interest in comparison with other specifications; power loss/efficiency, output voltage ripple and volume/weight. The main goal of this paper is to present an appropriate solution for optimizing the above mentioned characteristics. For this purpose, a comprehensive power loss model of a DC-DC converter is fully developed. Proper models are also demonstrated for assessment of the output voltage ripple and the utilized transformer volume as the bulkiest component in a DC-DC converter. In order to provide a test bed for evaluation of the proposed models, a 50W push-pull DC-DC converter is designed and implemented. Finally, a novel cost function with three assigned weight functions is proposed in order to have a trade-off among the power loss, the output voltage ripple and the utilized transformer volume of the converter. The cost function is optimized for applications in which volume has the highest priority in comparison with power loss and ripple. The optimization results show that the transformer volume can be decreased by up to 51% and this result is verified by experimental results. The developed models and algorithms in this paper can be used for other DC-DC converter topologies with some minor modifications.

• Journal of Power Electronics
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• 제19권2호
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• pp.549-559
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• 2019

This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.643-653
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• 2017

The paper presents controller optimization algorithm for a 12-pulse voltage source converter (VSC) based high voltage direct current (HVDC) system. To get an optimum algorithm, three methods namely conventional-Zeigler-Nichols, linear-golden section search (GSS) and stochastic-particle swarm optimization (PSO) are applied to control of 12 pulse VSC based HVDC system and simulation results are presented to show the best among the three. The performance results are obtained under various dynamic conditions such as load perturbation, non-linear load condition, and voltage sag, tapped load fault at points-of-common coupling (PCC) and single-line-to ground (SLG) fault at input AC mains. The conventional GSS and PSO algorithm are modified to enhance their performances under dynamic conditions. The results of this study show that modified particle swarm optimization provides the best results in terms of quick response to the dynamic conditions as compared to other optimization methods.