Title :
Genetic optimization of a fuzzy system for charging batteries
Author :
Surmann, Hartmut
Author_Institution :
German Nat. Res. Center for Inf. Technol., St. Augustin, Germany
fDate :
10/1/1996 12:00:00 AM
Abstract :
A large variety of nickel-cadmium (Ni-Cd) batteries have been developed to meet a wide range of user needs, ranging from low-current-level uses like emergency power sources for semiconductor memories to very high-power applications such as motor-operated cordless drills. This paper presents a genetic algorithm approach to optimize a fuzzy rule-based system for charging such high-power Ni-Cd batteries. For the optimization of the fuzzy system, a special objective function is developed which is based on the entropy of a fuzzy system. The resulting fuzzy system is able to charge high-power Ni-Cd batteries in about 10 min with a current of 6 A
Keywords :
battery chargers; cadmium; control system synthesis; fuzzy control; genetic algorithms; knowledge based systems; nickel; optimal control; power engineering computing; secondary cells; voltage control; 10 min; 6 A; Ni-Cd; Ni-Cd secondary batteries; algorithms; battery charging; control design; fuzzy rule-based system; fuzzy system entropy; genetic algorithm approach; objective function; optimization; test results; voltage regulation; Batteries; Cadmium; Entropy; Fuzzy control; Fuzzy sets; Fuzzy systems; Genetic algorithms; Humans; Knowledge based systems; Nickel;
Journal_Title :
Industrial Electronics, IEEE Transactions on
