Automatic Generation of Online Optimal Energy Management Strategies for Hybrid Powertrain Simulation 2017-24-0173
Due to more and more complex powertrain architectures and the necessity to optimize them on the whole driving conditions, simulation tools are becoming indisputable for car manufacturers and suppliers. Indeed, simulation is at the basis of any algorithm aimed at finding the best compromise between fuel consumption, emissions, drivability, and performance during the conception phase. For hybrid vehicles, the energy management strategy is a key driver to ensure the best fuel consumption and thus has to be optimized carefully as well.
In this regard, the coupling of an offline hybrid strategy optimizer (called HOT) based on Pontryagin’s minimum principle (PMP) and an online equivalent-consumption-minimization strategy (ECMS) generator is presented. Additionally, methods to estimate the efficiency maps and other overall characteristics of the main powertrain components (thermal engine, electric motor(s), and battery) from a few design parameters are shown.
Finally, the use of such tool chain to automatically generate the optimal energy management strategy for a given hybrid powertrain configuration, for which the main components are sufficiently specified and characterized is presented. The powertrain configuration illustrating this work is an input-split hybrid configuration.
Citation: Dabadie, J., Sciarretta, A., Font, G., and Le Berr, F., "Automatic Generation of Online Optimal Energy Management Strategies for Hybrid Powertrain Simulation," SAE Technical Paper 2017-24-0173, 2017, https://doi.org/10.4271/2017-24-0173. Download Citation
Author(s):
Jean-Charles Dabadie, Antonio Sciarretta, Gregory Font, Fabrice Le Berr
Affiliated:
IFP Energies Nouvelles, Institut Carnot IFPEN TE
Pages: 9
Event:
13th International Conference on Engines & Vehicles
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Electric motors
Fuel consumption
Hybrid electric vehicles
Powertrains
Optimization
Simulation and modeling
Mathematical models
Vehicle drivers
Suppliers
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