This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
A Heuristic Supervisory Controller for a 48V Hybrid Electric Vehicle Considering Fuel Economy and Battery Aging
Technical Paper
2019-01-0079
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
Most studies on supervisory controllers of hybrid electric vehicles consider only fuel economy in the objective function. Taking into consideration the importance of the energy storage system health and its impact on the vehicle’s functionality, cost, and warranty, recent studies have included battery degradation as the second objective function by proposing different energy management strategies and battery life estimation methods. In this paper, a rule-based supervisory controller is proposed that splits the torque demand based not only on fuel consumption, but also on the battery capacity fade using the concept of severity factor. For this aim, the severity factor is calculated at each time step of a driving cycle using a look-up table with three different inputs including c-rate, working temperature, and state of charge of the battery. The capacity loss of the battery is then calculated using a semi-empirical capacity fade model. Eventually, the fuel economy, and capacity loss as two of the most important objectives are compared with and without implementing the proposed controller. In the comparative study, four customized driving cycles are considered, including calm/aggressive drivers and low/high vehicle speeds. The results suggest improvement in the objectives and trade-off between fuel economy and battery aging. The proposed heuristic controller can be implemented in different types of hybrid electric vehicles.
Recommended Content
Authors
Citation
Malmir, F., Xu, B., and Filipi, Z., "A Heuristic Supervisory Controller for a 48V Hybrid Electric Vehicle Considering Fuel Economy and Battery Aging," SAE Technical Paper 2019-01-0079, 2019, https://doi.org/10.4271/2019-01-0079.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 | ||
Unnamed Dataset 3 | ||
Unnamed Dataset 4 | ||
Unnamed Dataset 5 | ||
Unnamed Dataset 6 |
Also In
References
- Bao , R. , Avila , V. , and Baxter , J. 2017
- Guzzella , L. and Sciarretta , A. Vehicle Propulsion Systems Third Berlin Springer 2013
- Tang , L. 2017
- M. Sabri , M.F. , Danapalasingam , K.A. , and Rahmat , M.F. A Review on Hybrid Electric Vehicles Architecture and Energy Management Strategies Renew. Sustain. Energy Rev. 53 1433 1442 2016
- Suri , G. and Onori , S. A Control-Oriented Cycle-Life Model for Hybrid Electric Vehicle Lithium-Ion Batteries Energy 96 644 653 2016
- Ramadass , P. , Haran , B. , Gomadam , P.M. , White , R. et al. Development of First Principles Capacity Fade Model for Li-Ion Cells J. Electrochem. Soc. 151 2 A196 2004
- Serrao , L. and Onori , S. Optimal Energy Management of Hybrid Electric Vehicles Including Battery Aging Proceedings of the American Control Conference 2011 2125 2130
- Wang , J. et al. Cycle-Life Model for Graphite-LiFePO 4 Cells J Power Sources 196 8 3942 3948 Apr. 2011
- Ebbesen , S. , Elbert , P. , and Guzzella , L. Battery State-of-Health Perceptive Energy Management for Hybrid Electric Vehicles IEEE Trans. Veh. Technol. 61 7 2893 2900 Sept. 2012
- Todeschini F. , Onori S. , and Rizzoni G. 2012
- Groot , J. 2012
- Spagnol , P. , Onori , S. , Madella , N. , Guezennec , Y. et al. Aging and Characterization of Li-Ion Batteries in a HEV Application for Lifetime Estimation IFAC Proc. 43 7 186 191 July 2010
- Crolla , D. , Foster , D.E. , Kobayashi , T. , and Vaughan , N. Encyclopedia of Automotive Engineering Chichester, UK John Wiley & Sons, Ltd 2014
- Nikolian , A. et al. Classification of Electric Modeling and Characterization Methods of Lithium-Ion Batteries for Vehicle Applications European Electric Vehicle Congress 2014
- ANR26650 Lithium Ion Cylindrical Cell http://a123batteries.com/anr26650-lithium-ion-cylindrical-cell-anr26650m1-b/
- Xu , B. et al. Transient Dynamic Modeling and Validation of an Organic Rankine Cycle Waste Heat Recovery System for Heavy Duty Diesel Engine Applications Appl. Energy 205 260 279 Nov. 2017
- Dynamometer Drive Schedules https://www.epa.gov/vehicle-and-fuel-emissions-testing/dynamometer-drive-schedules
- Liu , Z. , Ivanco , A. , and Filipi , Z.S. Impacts of Real-World Driving and Driver Aggressiveness on Fuel Consumption of 48V Mild Hybrid Vehicle SAE Int. J. Alt. Power. 5 2 249 258 2016 10.4271/2016-01-1166