Intelligent control of complex electrochemical systems with a neuro-fuzzy-genetic approach

This paper describes different hybrid approaches for controlling the battery charging process. The hybrid approaches combine soft computing techniques to achieve the goal of controlling the temperature of the battery during the electrochemical charging process. We have reduced the time required for charging a battery with the use of fuzzy logic, neural networks, and genetic algorithms. In the neuro-fuzzy-genetic approach, neural networks are used for modeling the electrochemical process, fuzzy logic is used for controlling the process, and genetic algorithms are used to optimize the fuzzy system.