Performance prediction of a solar driven ejector-absorption cycle using fuzzy logic

SÖZEN A., Kurt M., Akcayol M. A., Ozalp M.

RENEWABLE ENERGY, vol.29, no.1, pp.53-71, 2004 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 29 Issue: 1
  • Publication Date: 2004
  • Doi Number: 10.1016/s0960-1481(03)00172-1
  • Journal Name: RENEWABLE ENERGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.53-71
  • Gazi University Affiliated: Yes


Theoretical performance analysis of the absorption systems is very complex because of analytic functions used for calculating the properties of fluid couples and simulation programs. To simplify this complex process, this paper proposes a new approach to performance analysis of solar driven ejector-absorption refrigeration system (EARS) operated aqua/ammonia. Performance of EARS was predicted using fuzzy logic controller at different working conditions instead of complex rules and mathematical routines. Fuzzy logic's linguistic terms provide a feasible method for defining the operational characteristics of EARSs. Input data for fuzzy logic are experimental results performed in the climate condition of Ankara in Turkey. In the comparison of performance analysis results between analytic equations and by means of fuzzy logic controller, deviations coefficient of performance (COP), exergetic coefficient of performance (ECOP) and circulation ratio (F) for all working temperatures are less than 2, 5 and 0.2%, respectively. The statistical coefficient of multiple determinations (R-2 value) equals to 1, 0.9996, 1 for the COP, ECOP and F, respectively. These accuracy degrees are acceptable in design of EARS. This study is considered to be helpful in predicting the performance of an EARS prior to its setting up in an environment where the temperatures are known. Also, this study provides a fast and accurate means of determining the performance under transient operating regimes without the need to resort to classical physical modeling. (C) 2003 Elsevier Ltd. All rights reserved.