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Abstract: When designing very complex control strategy using hybrid technology, one usually faces the challenge of balancing effective realization of multi-control modeling with design simplicity. To better manage this difficulty we have used the agent paradigm as a simple and powerful bridge between asynchronous/distributed computation and Matlab environment. The proposed architecture has been used to design a complex hybrid control environment using multi-objective, fuzzy c-means, and genetic algorithms optimization to design hybrid control strategies suitable for the energy flows management on board of hybrid electric vehicles. [Copyright &y& Elsevier]

In this paper, a generalized fuzzy logic controller (FLC) is used to optimize the fuel economy and reduce the emissions of hybrid vehicles with parallel configuration. Using the driver input, the state of charge (SOC) of the energy storage, the motor/generator speed, the current gear ratio and vehicle speed, a set of 44 rules have been developed, in a fuzzy controller, to effectively determine the power split between the electric machine and the internal combustion engine (ICE). The underlying theme of the fuzzy controller is to optimize the fuel flow and reduce NOx emission. The parameters in the fuzzy rules can be adjusted to trade-off the fuel economy and the NOx emission of the vehicle.Simulation results are used to assess the performance of the controller. A forward-looking hybrid vehicle simulation model is used to implement the control strategies. By using fuzzy logic, trade-off between fuel economy and emission improvement has been shown. [Copyright &y& Elsevier]