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Vehicles based on genetic algorithm optimization of air-conditioning heat exchangers

Population evolved through survival of the fittest, with the highest fitness value of chromosome that is the best condenser structure. This example is taken from a General Motors automobile air conditioner models, the design conditions and requirements in Table 1. Iteration block diagram shown in Figure 2. Table 1 automobile air conditioning condenser design condition calculation, fin height, spacing and thickness ranges of 5 ~ 10ram, 3 ~ 5mm and 0.4 ~ 0.9mm factor and the West in the heat exchanger refrigerant-side volume △ p units of resistance were transformed into am and kPa, the volume and the weight coefficients of resistance were taken 0.6 and 0.4. Using genetic algorithm after 100 generations shown in Table 2. Optimized the volume of the condenser 61cm3, the resistance loss is 16kPa, while ensuring that the condenser can be volume and pressure loss. Table 2 Structural parameters of the condenser 3 Conclusion In this paper, parallel flow condenser model, based on the performance of the condenser is proposed evaluation factor. And use genetic algorithm to optimize the calculation of parallel flow condensers, get the following conclusion: To evaluate the performance of heat exchanger performance indicators and the main resistance to heat transfer losses, the volume of automotive air conditioning size is an important factor in meeting the conditions for the heat Obviously, power consumption and caused resistance to heat exchanger volume is more important. Performance evaluation factor taking into account the size of the heat exchanger and the refrigerant side pressure drop for the condenser in structure provides excellent performance evaluation criteria. Genetic algorithm can optimize the structure of the calculation of the condenser, heat exchanger performance in meeting the premise, making the vehicle dimensions and design of the condenser flow resistance is smaller, thereby reducing the condenser volume, improve vehicle air conditioning performance. References: [1] Chen Mengxiang. Development of automotive air conditioning (b) automobile and parts ,2002,28:24-25. [2] package Tao, Huang, Dong Yujun,[link widoczny dla zalogowanych], Xiu-Ling Yuan, et al. Advection condenser and condenser in the refrigeration segment car comparative analysis of the application of refrigeration and air conditioning and electrical machinery, 2005.26 (101) :25-27. [3] Gong weir Jue, Zhang group,[link widoczny dla zalogowanych], Zhengwei Zhi, Xiang-hui Yu. Parallel Flow Condenser Auto Air Conditioning computer-aided analysis of thermal performance Ⅲ. Beijing Technology and Business University, 2006,: 24 (6) :22-25. [4. Wang Xiaoping, Cao Liming. Genetic algorithm [M]. Xi'an: Xi'an Jiaotong University Press, 2004. Received :2007-11-16OptimizationforHeatExchangerofVechileAir-conditionBasedonGeneticAlgorithmrUEMin-nan, LIUJian-huaPowerEngineering, UniversityofShanghaiforScienceandTechnology,[link widoczny dla zalogowanych], Shanghai200093, China) Abstract: BasedoncharacteristicofvehicleairconditionScondenser, parallelflowcondenserSmathematicmodelissetup, performanceevaluateparameterconsideringbothheatexchangersvolumeandflowresistanceiuilt. Geneticalgorithmisalsointroducedintothestructureoptimizationofparallelflowcondenser. Thestructureparameteristransformedintochromosomeofgeneticalgorithm. Optimizationworkisca ~ iedoutbytheevaluationofthegroup. ThismethodistakenonthecertainvehicleScondenserandagoodresultisreached. Keywords: vehicleairconditioner; condenser; geneticalgorithm Author: Yue Minnan (1982 a),[link widoczny dla zalogowanych], female, Master; Liu Jianhua (1956 -), male, Professor, 8l Volume

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