Battery-supercapacitor electric vehicles energy management using DP based predictive control algorithm

Author

Lin Xiaofeng ; Hu Meipin ; Song Shaojian ; Yang Yimin

Author_Institution

Coll. of Electr. Eng., Guangxi Univ., Nanning, China

fYear

2014

fDate

9-12 Dec. 2014

Firstpage

30

Lastpage

35

Abstract

To achieve a reasonable power split scheme of Li battery pack and supercapacitor hybrid electric vehicles, we propose dynamic programming (DP) based predictive control algorithm (PCA) in this paper. First, the model of the vehicle plant is established consisting of mathematical models of supercapacitor and Li battery pack. Then, the PCA based control system is designed in order to make full use of future road information. Thirdly, a DP-based-controller is proposed to minimize the cost function which consists of power loss and constrains of output. The simulation suggests that the proposed strategy can generate reasonable power split by taking the power loss, constraints of two sources and flatness of power output of Li battery pack into account.

Keywords

dynamic programming; energy management systems; hybrid electric vehicles; predictive control; secondary cells; supercapacitors; DP based predictive control; Li; Li battery pack; battery supercapacitor; cost function; dynamic programming; electric vehicles energy management; future road information; hybrid electric vehicles; mathematical models; power loss; power split scheme; vehicle plant; Batteries; Cost function; Mathematical model; Predictive control; Roads; Supercapacitors; Vehicles; Li battery pack; dynamic programming; electric vehicle; energy management; predictive control algorithm; supercapacitor;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Vehicles and Transportation Systems (CIVTS), 2014 IEEE Symposium on

Conference_Location

Orlando, FL

Type

conf

DOI

10.1109/CIVTS.2014.7009474

Filename

7009474