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Equivalent Consumption Minimization Strategy for Mild Hybrid Electric Vehicles with a Belt Driven Motor
Technical Paper
2017-01-1177
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
It will be a challenge to satisfy CO2 regulations in 2020 with conventional powertrains based on a gasoline or diesel engine. In order to reduce CO2-emission until upcoming 2020, it has been suggested that new powertrain systems should be developed. One of them is mild hybrid electric vehicle (MHEV) system with a belt driven motor (BDM). MHEV system with a BDM has an advantage of costs in contrast to full hybrid systems, because fuel efficiency of the powertrain is able to be increased by simply substituting the belt driven motor for an alternator. In this following paper, the simulator is developed for testing MHEV system which is consist of a belt driven motor(BDM). This simulator is used for evaluating fuel efficiency of mild hybrid system that has equivalent consumption minimization strategy (ECMS) algorithm for BDM type. The ECMS is an efficient strategy to manage electric and fuel energy between the battery and the internal combustion engine. It needs less time to calibrate than that of map-based algorithm such as distributing the motor and the engine power by battery SOC, gear ratio and driver demand torque. It will be proposed that a suitable ECMS for MHEV with a belt driven motor. In addition, fuel economy of MHEV applied with the ECMS will be compared with the results of map-based algorithm.
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Jun, Y., Jeon, B., and Youn, W., "Equivalent Consumption Minimization Strategy for Mild Hybrid Electric Vehicles with a Belt Driven Motor," SAE Technical Paper 2017-01-1177, 2017, https://doi.org/10.4271/2017-01-1177.Data Sets - Support Documents
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References
- Sciarretta , A. , and Guzzella , L. Control of hybrid electric vehicles IEEE Control Systems Magazine 60 70 April 2007
- Paganelli , G. , Ercole , G. , Brahma , A. , Guezennec , Y. , and Rizzoni , G. General supervisory control policy for the energy optimization of charge-sustaining hybrid electric vehicles JSAE Review 22 4 511 518 2001
- 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 vehicles: A unified approach using optimal control methods Oil Gas Sci. Technol. Rev. IFP Energies Nov. 2013
- Simona , O. , Lorenzo , S. , Giorgio , R. Adaptive Equivalent Consumption Minimization Strategy for Hybrid Electric Vehicles DSCC2010 Sep. 12-15 2010