DocumentCode
3360515
Title
Study on Braking Force Distribution of Electric Vehicles
Author
Guo, Jingang ; Wang, Junping ; Cao, Binggang
Author_Institution
Sch. of Mech. Eng., Xi´´an Jiaotong Univ., Xi´´an
fYear
2009
fDate
27-31 March 2009
Firstpage
1
Lastpage
4
Abstract
Braking force distribution of an electric vehicle has an important impact on braking performance and energy recovery. With the analysis of braking dynamics and the establishment of motor model, a braking force distribution strategy is proposed from the viewpoint of maximum energy recovery. From another point of view, how to distribute the braking force can be thought as a constrained optimization problem, in which the motor maximum power, the motor maximum angular speed and the requirements of vehicle stability are all taken into account. The task is to find the optimal distribution ratio of the regenerative braking torque and the friction braking torque so that the regenerated energy can be maximized. Genetic algorithm is used to solve the optimization problem. The simulation results show that the braking force distribution by optimization is in accordance with the proposed braking force distribution strategy. The strategy takes advantage of the motor maximum torque and can obtain maximum energy recovery.
Keywords
electric motors; electric vehicles; genetic algorithms; regenerative braking; stability; vehicle dynamics; braking dynamic analysis; braking force distribution strategy; electric vehicles; friction braking torque; genetic algorithm; maximum energy recovery; motor model; regenerative braking torque; vehicle stability; Axles; Constraint optimization; Distribution strategy; Electric vehicles; Friction; Genetic algorithms; Hybrid electric vehicles; Land vehicles; Torque; Vehicle dynamics;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location
Wuhan
Print_ISBN
978-1-4244-2486-3
Electronic_ISBN
978-1-4244-2487-0
Type
conf
DOI
10.1109/APPEEC.2009.4918806
Filename
4918806
Link To Document