Improving regenerative braking strategy using genetic algorithm for electric vehicles / H. Taleghani ... [et al.]

Taleghani, H. and Hassan, M.K and Abdul Rahman, R. Z. and Che Soh, A. (2018) Improving regenerative braking strategy using genetic algorithm for electric vehicles / H. Taleghani ... [et al.]. Journal of Mechanical Engineering (JMechE), SI 6 (1). pp. 121-130. ISSN 18235514


The regenerative braking system is one of the most fundamental advantages of electric vehicles compared with internal combustion vehicles. With a proper regenerative braking strategy, a fraction of vehicle’s kinetic energy is harvested by the electric motor, which is configured as a generator during braking. The strategy distributes the required braking force between friction brakes of both axles and regenerative breaks. This study presents a genetic algorithm brake force distribution strategy to increase energy recovery, considering the Economic Commission for Europe (ECE) regulations. The performance of the proposed regenerative braking control algorithm is evaluated by the ADVISOR which is based on MATLAB/Simulink environment. The results indicate that the driving range has maximum increased to 25 percent with regards to the drive cycle.


Item Type: Article
Email / ID Num.
Taleghani, H.
Hassan, M.K
Abdul Rahman, R. Z.
Che Soh, A.
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Algorithms
T Technology > TJ Mechanical engineering and machinery
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Mechanical Engineering
Journal or Publication Title: Journal of Mechanical Engineering (JMechE)
UiTM Journal Collections: UiTM Journal > Journal of Mechanical Engineering (JMechE)
ISSN: 18235514
Volume: SI 6
Number: 1
Page Range: pp. 121-130
Keywords: Regenerative Braking, Genetic Algorithm, Electric Vehicles, Braking Force Distribution Strategy
Date: 2018
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