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A simple but reasonably accurate battery model is required for simulating the performance of electrical systems that employ a battery for example an electric vehicle, as well as for investigating their potential as an energy storage device. In this paper, a relatively simple equivalent circuit based model is employed for modeling the performance of a battery. A computer code utilizing a multi-objective genetic algorithm is developed for the purpose of extracting the battery performance parameters. The code is applied to several existing industrial batteries as well as to two recently proposed high performance batteries which are currently in early research and development stage. The results demonstrate that with the optimally extracted performance parameters, the equivalent-circuit based battery model can accurately predict the performance of various batteries of different sizes, capacities, and materials.

The ratio of the energy liberated during a flight to the revenue work done (ETRW) of an airplane can be employed as a key indicator to assess its environmental impact. It remains constant during the life cycle of the aircraft and is fixed by its designers. The goal of an environmentally optimum airplane is to minimize the ETRW. For an existing airplane, there are two major parameters that can greatly affect the ETRW, which are the ratio of actual payload to maximum possible payload “c” and the flight range R. The goal of this paper is to study the effect of c and R on ETRW and minimize it by using a genetic algorithm (GA). The study is performed on a Boeing 737-800 and a Boeing 747-400 aircraft. The optimization study is valuable in determining the payload and range of an existing aircraft for minimal environmental impact; it turns out that the maximum possible values of payload and range do not necessarily lead to a flight with minimal environmental impact.