Multiobjective optimal placement of convectively cooled electronic components on printed wiring boards

Queipo, Néstor V.; Humphrey, J. A. C.; Ortega, Alfonso

doi:10.1109/95.679044

Cited by 30 publications

(4 citation statements)

References 30 publications

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“…The power devices are placed irregularly as shown in Fig. 3 to reflect the fact that the placement of devices is a compromise between thermal and electrical design [7]. Rather than populate the board with power MOSFETs, power resistors are used.…”

Section: Methodsmentioning

confidence: 99%

Prediction of device temperatures in an electric vehicle battery charger system by analysis of device thermal cross-coupling

Davidson

Stone

Foster

et al. 2013

2013 15th European Conference on Power Electronics and Applications (EPE)

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This paper presents a practical implementation of the measurement and use of thermal cross-coupling data. Thermal cross-coupling, the thermal transfer impedance between the heat generation of one power device and the temperature of another, is characterised using pseudo-random binary sequences for a typical H-bridge arrangement. Knowledge of the cross-coupling between each pair of devices allows temperature profiles to be predicted for arbitrary input power waveforms. The technique is verified by applying arbitrary power waveforms to all devices in the experimental arrangement and measuring the temperature response. Good agreement is shown between predicted and practical device temperature waveforms, demonstrating the viability of the technique.

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Section: Methodsmentioning

confidence: 99%

Prediction of device temperatures in an electric vehicle battery charger system by analysis of device thermal cross-coupling

Davidson

Stone

Foster

et al. 2013

2013 15th European Conference on Power Electronics and Applications (EPE)

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“…The electrical performance is assumed to be expressed by the maximum attainable clock frequency, , which is an inverse of clock cycle, , such that (4) where , is the delay due to packaging, is the clock skew, and is the delay of internal logic of the system. The delay due to properties of PWB, is usually defined as a time necessary for signal to travel along the board diagonal and to reach the switching threshold.…”

Section: B Estimation Of Electrical Performancementioning

confidence: 99%

“…The miniaturization requires more advanced package technology resulting in cost increase [2]. Cooling technology becomes challenging as Manuscript [3] and Queipo et al [4] considered two objectives for PWB design: 1) the minimization of the failure rate of the system; 2) the total wiring length. The design decision influencing the performance criteria in these papers was the choice of modules placement on PWB.…”

Section: Introductionmentioning

confidence: 99%

Application of multiobjective optimization in selection of printed wiring boards

Li¹,

Palusinski

2003

IEEE Trans. Adv. Packag.

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This paper presents an application of multiobjective optimization in optimal selection of number of signal layers in printed wiring board (PWB). The criteria considered in optimization are: cost, electrical performance, and reliability. The reliability of system is influenced by the operating temperature, which is determined by the power dissipated in parts placed on the board, ambient temperature, and cooling technology. In evaluating cooling and calculation of junction temperature both heat conduction through the board and forced air cooling are considered. Designers have to deal with multiple, conflicting criteria because of variety of requirements that packaging should meet. However, sophisticated methods developed for multiobjective optimization are not yet used in packaging design. This paper describes some of the methods used in solving multicriteria optimization and gives an example of application to design of PWB.The weighting method is applied to find the optimal solution first. The graphical form of optimality of different weights for different criteria is presented. The distance based methods, which include 1 -distance, 2 -distance, -distance, and the geometric distance method, are also applied to determine the optimal number of signal layers. The results from different methods are compared and discussed.Index Terms-Design of printed wiring board, distance based methods, multicriteria optimization, multilayer board, weighting method.

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“…Osteman et al [3] developed a force directed placement methodology to solve coupled reliability and routability placement procedure for arranging electronic components on a convectively cooled two-dimensional workspace. Queipo et al [4] introduced a genetic algorithm for the search of optimal or near optimal placement solutions on printed wiring boards. Deb et al [5] use evolutionary algorithms to solve a twoobjective optimization problem including minimizing the overall wire length and minimizing the failure rate of the board.…”

Section: Introductionmentioning

confidence: 99%

MCM placement problem with GASA multi-objective optimization strategy

Lin

Huang

2007

2007 International Conference on Electronic Materials and Packaging

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Placement of multiple dies on an MCM substrate is a difficult combinatorial task in which multiple criteria need to be considered simultaneously to obtain a true multi-objective optimization. In this paper we described a MCM placement model for the multi-objective optimization problem and solved this model by the simulated annealing SA algorithm and the hybrid optimization strategy GASA (namely the combination of genetic algorithm and simulated annealing) respectively. Our design methodologies consider multiobjective component placement based on thermal reliability, routing length and chip area criteria for multi-chip module. The purpose of the multi-objective optimization placement is to enhance the system performance, reliability and reduce the substrate area by obtaining an optimal cost during multi-chip module placement design phase. For reliability considerations, the design methodology focuses on the placement of the power dissipating chips to achieve uniform thermal distribution. For route-ability consideration, the total wire length minimization is estimated by bounding box approximation method. For substrate area consideration, the area is estimated by minimum area contains all chips. The cost function is formulated by the weight sum calculation. For design flexibility, different weights can be assigned depending on designer's considerations. Various methods including simulated annealing and hybrid generic algorithm are applied to solve the placement solutions. 3-D Finite Element Analysis (FEA) is carried out to assess thermal distribution in MCM substrate. The optimization results of various weighting assignments obtained by different algorithms are compared. In addition, an auto generated optimal placement layout based on the analytical solution is also presented.

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Multiobjective optimal placement of convectively cooled electronic components on printed wiring boards

Cited by 30 publications

References 30 publications

Prediction of device temperatures in an electric vehicle battery charger system by analysis of device thermal cross-coupling

Prediction of device temperatures in an electric vehicle battery charger system by analysis of device thermal cross-coupling

Application of multiobjective optimization in selection of printed wiring boards

MCM placement problem with GASA multi-objective optimization strategy

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