Comparison of Cycle Reduction and Model Reduction Strategies for the Design Optimization of Hybrid Powertrains on Driving Cycles

Adham Kaloun (1, 2) , Stephane Brisset (1) , Maxime Ogier (3) , Mariam Ahmed (2) , Robin Vincent (2)

1 L2EP - Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697
2 VALEO
3 INOCS - Integrated Optimization with Complex Structure

Decision-making is a crucial and difficult step in the design process of complex systems such as the hybrid powertrain. Finding an optimal solution requires the system feedback. This can be, depending on the granularity of the models at the component level, highly time-consuming. This is even more true when the system’s performance is determined by its control. In fact, various possibilities can be selected to deliver the required torque to the wheels during a driving cycle. In this work, two different design strategies are proposed to minimize the fuel consumption and the cost of the hybrid powertrain. Both strategies adopt the iterative framework which allows for the separation of the powertrain design problem and its control while leading to system optimality. The first approach is based on model reduction, while the second approach relies on improved cycle reduction techniques. They are then applied to a parallel hybrid vehicle case study, leading to important cost reduction in reasonable delays and are compared using different metrics.

Mots clés: hybrid electric vehicle; model reduction; optimal control; optimal design; electric machines; Plant/Controller optimization; Cycle reduction

Domaines: Sciences de l'ingénieur [physics]; Energie électrique

Adham Kaloun, Stephane Brisset, Maxime Ogier, Mariam Ahmed, Robin Vincent. Comparison of Cycle Reduction and Model Reduction Strategies for the Design Optimization of Hybrid Powertrains on Driving Cycles. Energies, 2021, 14 (4), pp.948. ⟨10.3390/en14040948⟩. ⟨hal-03222773⟩