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Real-time predictive control of hybrid fuel cell drive trains

: Bartholomäus, R.; Fischer, A.; Klingner, M.

International Federation of Automatic Control -IFAC-:
Fifth IFAC Symposium on Advances in Automotive Control 2007. CD-ROM : August 20-22, 2007, Aptos, California, USA
Aptos, Calif.: IFAC, 2007
Symposium on Advances in Automotive Control <5, 2007, Aptos, Calif.>
Fraunhofer IVI ()
predictive control; optimal control; hybrid fuel cell drive train; energy management; linear optimization

Optimal predictive control of hybrid drive trains offers improved characteristics compared to traditional control strategies.
Unfortunately that is obtained at cost of a significantly incrased computational effort, which makes it hard to fulfil the real-time requirements with current vehicle control units. The paper describes a predictive control algorithm for hybrid fuel cell drive trains which allows real-time control. First, the used predictor-optimizer structure of the controller is presented, which splits the control task into the prediction of the load power and the determination of the optimal control function. After a brief description of a worst-case predictor, the design of the optimzer is presented, which is the focus of the paper. The real-time ability is obbtained by an adapted modeling of the hybrid drive, which finally allows the application of linear optimizationin order to solve the optimal control problem. The characteristics of the resulting control algorithm are illustrated by a simulation example.