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

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 d...

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Bibliographic Details
Main Authors: Taleghani, H. (Author), Hassan, M.K (Author), Abdul Rahman, R. Z. (Author), Che Soh, A. (Author)
Format: Book
Published: Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM), 2018.
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100 1 0 |a Taleghani, H.  |e author 
700 1 0 |a Hassan, M.K  |e author 
700 1 0 |a Abdul Rahman, R. Z.  |e author 
700 1 0 |a Che Soh, A.  |e author 
245 0 0 |a Improving regenerative braking strategy using genetic algorithm for electric vehicles / H. Taleghani ... [et al.] 
260 |b Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM),   |c 2018. 
500 |a https://ir.uitm.edu.my/id/eprint/41026/1/41026.pdf 
520 |a 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. 
546 |a en 
690 |a Algorithms 
690 |a TJ Mechanical engineering and machinery 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
787 0 |n https://ir.uitm.edu.my/id/eprint/41026/ 
856 4 1 |u https://ir.uitm.edu.my/id/eprint/41026/  |z Link Metadata