Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming

Bing Dong; Yan Tao Tian; Chang Jiu Zhou

doi:10.4028/www.scientific.net/AMM.556-562.1472

Paper Titles

The Achievement of Intelligent Lubrication Adjustment Function of CNC Machine Tools Based on SSAS
p.1454

The Design of a New Type of Spindle Vibration Test Device
p.1460

Physical Simulation Experiment Research of Steam and Gas Assisted Gravity Drainage
p.1464

Simulation on Influence of Two-Stage Warhead Penetration at Different Obliquity Angles
p.1468

Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming
p.1472

Design of the Portable Abrasive Water Jet Rescue and Fire-Fighting Device
p.1476

Design of Quasi Free Surface Secondary Optical Lens for LED Auto Taillights
p.1483

The Analysis of Some Problems of Environmental Stress Screening of Electronic Equipment
p.1487

Design of Resistance Touch Screen Based on S3C6410 Embedded System
p.1491

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Energy Management System Optimal Strategy for Pure...

Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming

Abstract:

This thesis puts forward one optimal adaptive fuzzy control method based on the pure electric vehicle energy management system of the fuzzy control which has been founded already. By adding an optimizing researching model based on the conventional fuzzy control strategy, the thesis can pick up the valuable control rules based on the dynamic programming theory and also can adjust the parameter of the fuzzy controller automatically according to the system operating. These can make the sum of the energy loss reduce to the min. The experiment points out that this method makes the vehicle possess good economic performance in the same driving cycle.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

1472-1475

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.1472

Citation:

Cite this paper

Online since:

May 2014

Authors:

Bing Dong*, Yan Tao Tian, Chang Jiu Zhou

Keywords:

Dynamic Programming, Energy Management System, Pure Electric Vehicle

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] JianCao. A NewBattery/UltraCapacitor Hybrid Energy Storage System for Electric, Hybrid, and Plug-In Hybrid Electric Vehicle[J]. IEEE transactionson power electrics, Vol. 27, (2012).

DOI: 10.1109/tpel.2011.2151206

Google Scholar

[2] N. Omar, J. Van Mierlo, B. Verbrugge, and P. Van den Bossche. Power and life enhancement of a battery electrical double layer capacitor for hybrid electric and charge depleting plug-in vehicle applications [J]. Elecrtochimca Acta, Vol 55, 2010: 7524-7531.

DOI: 10.1016/j.electacta.2010.03.039

Google Scholar

[3] GU Zhongli, WANG Suzhen, LI Junqiu, Energy Management Strategy of Multiple Objects Control for Hybrid Electric Vehicle[J]．Transactions of Beijing Institute of Technology, (2006).

Google Scholar

[4] JOHANNESSON L, ASBOGARD M, EGARDT B. Assessing the potential of predictive control for hybrid vehicle powertrains using stochastic dynamic programming[J]. IEEE Transactions on Intelligent Transportation Systems, 2007, 8(1)：71-83.

DOI: 10.1109/tits.2006.884887

Google Scholar

[5] ZOU Yuan, CHEN Rui, HOU Shijie, HU Xiaosong, Energy Management Strategy for Hybrid Electric Tracked Vehicle Based on Stochastic Dynamic Programming[J]. Journal of mecha-nical engineering, Vol. 48, No. 14, 2012, 7: 91-96.

DOI: 10.3901/jme.2012.14.091

Google Scholar