Eisuke Togashi, Shin-ichi Tanabe and Tomohiro Ataku
Bibliographic info:
Building Simulation, 2007, Beijing, China

A parameter adjustment method for an ammonia heat pump chiller using a genetic algorithm (GA) was developed. The parameters were automatically adjusted by the data of performance at rated point. Upon using the proposed adjustment method for parameters, output values of the simulation model agreed quite well with the performance data at rated point. The deviation of output was less than 1.2 [%] from the rated value. To speed up the adjustment process, a new approximation method with neural network was also proposed. This method decreases the calculation time required in obtaining refrigerant thermodynamic properties. The time required to calculate saturated and other refrigerant states were decreased by 14 times and 33 times respectively, while the average relative error was less than 0.04 [%] and 0.5 [%] when compared to the exact solution from REFPROP. The time required to calculate the refrigerant cycle decreased 20 times, while relative error was within 3 [%].