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Within the current industrial context, companies aim to decrease the design process time and cost. The multidisciplinary design optimization (MDO) appears as a solution to accelerate the process and support designers in different stages of the design cycle. However, this relatively new concept needs to be integrated efficiently in the industrial environment and issues related to collaboration, data management, traceability and reuse need to be overcome.

The aim of this work is to efficiently integrate the MDO in the industrial design cycle by means of knowledge management (KM) techniques. To take into account the industrial environment, the methodology was applied in a collaborative software.

An example of collaborative design and optimization of an electronic throttle body (ETB) controller is presented with industrial requirements. The design problem was solved successfully and demonstrates the efficiency of the methodology in collaborative environments.

The contributions of this work lie in the structuration of the knowledge to support MDO and the definition of a general way to connect the existent MDO tools to the knowledge base. This methodology will enable to freely link different steps of the design process and reduce considerably the setting time of MDO in industries.

The purpose of this paper is to propose two energy management strategies (EMS) for hybrid electric vehicle, the power system is an hybrid architecture (fuel cell (FC)/battery) with two-converters parallel configuration.

First, the authors present the EMS uses a power frequency splitting to allow a natural frequency decomposition of the power loads and second the EMS uses the optimal control theory, based on the Pontryagin’s minimum principle.

Thanks to the optimal approach, the control objectives will be easily achieved: hydrogen consumption is minimized and FC health is protected.

The simulation results show the effectiveness of the control strategy using optimal control theory in term of improvement of the fuel consumption based on a comparison analysis between the two strategies.