Optimal Control Strategy for Hybrid Electric Vehicle Powertrain

An optimal control strategy is developed for the powertrain of hybrid electric vehicles (HEVs) to minimize the fuel consumption while maintaining good performance and drivability. A novel robust identifier using the generalized notion of power approach is developed and used to accurately predict the performance characteristics of the powertrain. The uniqueness of this model is its ability to represent both internal combustion engine (ICE) unit and electrical motor generator (EMG) unit of the powertrain system in one state space system of equations. Thus, it allows proper characterization of the interaction of both units considering the irreversibility of the entropy generation by the ICE unit, load small disturbances, and magnetic material nonlinearity as well as space and time harmonics of the EMG unit. The optimal control strategy is developed in two stages. The first uses a mathematical search algorithm based on the calculus of variation to minimize fuel consumption and develop needed torque to achieve a good performance. The second stage employs a fuzzy logic algorithm to ensure good drivability (comfort). The superiority of the optimization algorithm is demonstrated by applying it to a prototype HEV with split power configuration and by comparing simulation results with readily available benchmark data.