| Abstract |
To obtain highest efficiency and to extend the lifetime of the battery in electric vehicles, a battery buffer system can be implemented. It consists of double layer capacitors and a dc-dc converter. In case of regenerative braking operation the capacitors have to be able to accept energy, in case of acceleration they have to deliver energy. To ensure availability of the system anytime, the ultracapacitors state of charge has to be kept in a predefined range. Therefore a powermanagement has to be set up. The goal of the powermanagement is the intelligent power distribution between battery and super capacitors to reduce as well the maximum as the average battery power. In this paper, the design of a powermanagement is presented. Here, the design is exemplarily presented for an electric lift truck, but it can also be adapted for road vehicles. First, a common fuzzy controller to be applied in the powermanagement is derived. Accordingly, the fuzzy parameters are tuned by means of a genetic algorithm. This paper shows that a powermanagement by means of a fuzzy controller can be used to define a reasonable energy flow in a dual source electric vehicle autonomously. Furthermore it is shown that the success of the system can be strictly dependent on the genetic algorithm optimization method. Methods by means of predefined-base- and a stand-alone-genetic optimization are analyzed as well as the success for membership function tuning, fuzzy rule tuning and for a combined tuning in each case. The powermanagement is finally tested in a lift truck propulsion system test bench. |
