Geometry optimization of thermoelectric coolers using simplified conjugate-gradient method

Yu, Hongxing; Wang, Xiao Dong; Cheng, Chin‐Hsiang; Lin, David T.W.

doi:10.1016/j.energy.2013.06.069

Cited by 94 publications

(43 citation statements)

References 34 publications

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“…Unfortunately, the optimal applied currents corresponding to Q c,max and COP max are not the same, which means that Q c,max and COP max always cannot be reached simultaneously. Similarly, with the same operating conditions, as the TECs geometry is varied, ROR and COP are all varied, but maybe cannot reach the maximums simultaneously [8].…”

Section: Mathematical Modeling Of Tecsmentioning

confidence: 99%

“…Huang [8] developed an optimization approach which integrates a complete multiphysics TEC model and a simplified conjugate-gradient method [8]. Under a wide range of operating conditions of temperature difference and applied current, the geometric properties of STECs as search variables are optimized to reach the maximum TEC cooling rate.…”

Section: Geometry Properties Optimization Issuementioning

confidence: 99%

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Optimization Of Thermo-Electric Coolers Using Hybrid Genetic Algorithm And Simulated Annealing

Khanh¹,

Vasant²,

Elamvazuthi³

et al. 2014

Archives of Control Sciences

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Thermo-electric Coolers (TECs) nowadays are applied in a wide range of thermal energy systems. This is due to their superior features where no refrigerant and dynamic parts are needed. TECs generate no electrical or acoustical noise and are environmentally friendly. Over the past decades, many researches were employed to improve the efficiency of TECs by enhancing the material parameters and design parameters. The material parameters are restricted by currently available materials and module fabricating technologies. Therefore, the main objective of TECs design is to determine a set of design parameters such as leg area, leg length and the number of legs. Two elements that play an important role when considering the suitability of TECs in applications are rated of refrigeration (ROR) and coefficient of performance (COP). In this paper, the review of some previous researches will be conducted to see the diversity of optimization in the design of TECs in enhancing the performance and efficiency. After that, single-objective optimization problems (SOP) will be tested first by using Genetic Algorithm (GA) and Simulated Annealing (SA) to optimize geometry properties so that TECs will operate at near optimal conditions. Equality constraint and inequality constraint were taken into consideration.

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Section: Mathematical Modeling Of Tecsmentioning

confidence: 99%

Section: Geometry Properties Optimization Issuementioning

confidence: 99%

Optimization Of Thermo-Electric Coolers Using Hybrid Genetic Algorithm And Simulated Annealing

Khanh¹,

Vasant²,

Elamvazuthi³

et al. 2014

Archives of Control Sciences

View full text Add to dashboard Cite

show abstract

“…Base on the work of Huang [31], the authors claimed that by using a fixed ∆T, cooling rate and COP are increased firstly and decreased then as the supplied current is increased. For the same supplied current, the maximum cooling rate and maximum COP cannot always be reached simultaneously.…”

Section: Mathematical Modelling Of Stecsmentioning

confidence: 99%

“…Huang [31] introduced an optimization approach forming a complete multi-physics STEC model and a method of simplified conjugate-gradient, which is not a metaheuristic. Like in Cheng's work, the geometric properties of the STEC were optimized as search variables in order to achieve the maximum cooling rate considering many operating conditions of temperature difference and applied current.…”

Section: Author Application Advantages and Disadvantagesmentioning

confidence: 99%

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Metaheuristic Techniques in Enhancing the Efficiency and Performance of Thermo-Electric Cooling Devices

2017

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Abstract:The objective of this paper is to focus on the technical issues of single-stage thermo-electric coolers (TECs) and two-stage TECs and then apply new methods in optimizing the dimensions of TECs. In detail, some metaheuristics-simulated annealing (SA) and differential evolution (DE)-are applied to search the optimal design parameters of both types of TEC, which yielded cooling rates and coefficients of performance (COPs) individually and simultaneously. The optimization findings obtained by using SA and DE are validated by applying them in some defined test cases taking into consideration non-linear inequality and non-linear equality constraint conditions. The performance of SA and DE are verified after comparing the findings with the ones obtained applying the genetic algorithm (GA) and hybridization technique (HSAGA and HSADE). Mathematical modelling and parameter setting of TEC is combined with SA and DE to find better optimal findings. The work revealed that SA and DE can be applied successfully to solve single-objective and multi-objective TEC optimization problems. In terms of stability, reliability, robustness and computational efficiency, they provide better performance than GA. Multi-objective optimizations considering both objective functions are useful for the designer to find the suitable design parameters of TECs which balance the important roles of cooling rate and COP.

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Geometric optimization of trapezoidal thermoelectric heat pump considering contact resistances through genetic algorithm

2017

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Summary An alternate option for improving the performance of the thermoelectric heat pump (TEHP) is the variation in thermoelectric leg configuration. In this paper, the thermodynamic model based on first and second law of thermodynamics for an exoreversible TEHP including influence of Thomson effect as well as leg geometry on the coefficient of performance and heating load of the device has been developed and optimized. Modified expressions have been derived analytically for dimensionless heating load, irreversibilities, figure of merit, energy, and exergy efficiency. The effects of operating and geometry parameters such as shape parameter (Ac/Ah), temperature ratio (Tc/Th), Thomson effect, thermal and electrical contact resistances on the coefficient of performance, and heating load of the TEHP have been analysed. The results indicate that the Thomson effect has adverse effect on heating load of the system. The optimal parameters obtained through GA optimization process have been compared with the optimal parameters obtained through analytical method which proved the validity of GA optimization method for optimization of TEHP. After the testing, the GA optimization has been performed to determine the optimum parameters corresponding to maximum energy efficiency and maximum heating load. It was found that the GA population converges quickly after 20 runs only which proved the GA as time and cost‐effective optimization tool. This study will be useful for designing of practical TEHP systems of different leg geometries.

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Geometry optimization of thermoelectric coolers using simplified conjugate-gradient method

Cited by 94 publications

References 34 publications

Optimization Of Thermo-Electric Coolers Using Hybrid Genetic Algorithm And Simulated Annealing

Optimization Of Thermo-Electric Coolers Using Hybrid Genetic Algorithm And Simulated Annealing

Metaheuristic Techniques in Enhancing the Efficiency and Performance of Thermo-Electric Cooling Devices

Geometric optimization of trapezoidal thermoelectric heat pump considering contact resistances through genetic algorithm

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