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Automatic Generation of Online Optimal Energy Management Strategies for Hybrid Powertrain Simulation
Technical Paper
2017-24-0173
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
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.
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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.Also In
References
- Serrao L. , Sciarretta A. , Grondin O. , Chasse A. , Creff Y. , Di Domenico D. , Pognant-Gros P. , Querel C. , Thibault L. Open issues in supervisory control of hybrid electric L uses the vehicles: A unified approach using optimal control method s Oil & Gas Science and Technology 68 1 23 34 2013
- Guzzella L. , Sciarretta A. Vehicle propulsion systems. Introduction to modeling and optimizatio n 3rd Springer 2015
- Alix , G. , Dabadie , J. , and Font , G. An ICE Map Generation Tool Applied to the Evaluation of the Impact of Downsizing on Hybrid Vehicle Consumption SAE Technical Paper 2015-24-2385 2015 10.4271/2015-24-2385
- Abdelli , A. Optimal Design of an Interior Permanent Magnet Synchronous Motor for Wide Constant-Power Region Operation: Considering Thermal and Electromagnetic Aspects SAE Int. J. Alt. Power 3 1 129 138 2014 10.4271/2014-01-1889
- Le Berr F. , Abdelli A. , Postariu D.-M. and Benlamine R. Design and Optimization of Future Hybrid and Electric Propulsion Systems: An Advanced Tool Integrated in a Complete Workflow to Study Electric Devices OGST Journal 67 4 539 645
- Petit M , Marc N , Badin F , Mingant R , Sauvant-Moynot V A tool for vehicle electrical storage system sizing and modeling for system simulation VPPC Vehicle power and propulsion conference Coimbra, Portugal 27-30 october 2014
- Sciarretta A. , Dabadie J. , and Font G. Automatic Model-Based Generation of Optimal Energy Management Strategies for Hybrid Powertrains Proc of the SIA Powertrain Conf. Versailles, France 27-28 May 2015
- http://www.plm.automation.siemens.com/en_us/products/lms/imagine-lab/amesim
- http://toyotanews.pressroom.toyota.com/releases/2016+toyota+prius+technology.htm
- Musardo [X]C. , Rizzoni G. , Guezennec Y. , Staccia B. A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management European Journal of Control 11 4-5 509 524 2005
- Ambühl [Y] D. , Sciarretta A. , Onder C. , Guzzella L. , Sterzing S. , Mann K. , Kraft D. , Küsell M. A causal operation strategy for hybrid electric vehicles based on optimal control theory Proc. of the Braunschweig Symposium on Hybrid Vehicles and Energy Management Braunschweig, Germany 14-15 Feb. 2007