A chaotic particle swarm optimization algorithm for solving optimal power system problem of electric vehicle

Transportation of electrification has become a hot issue in recent decades and the large-scale deployment of electric vehicles has yet to be actualized. This article proposes a powertrain parameter optimization design approach based on chaotic particle swarm optimization algorithm. To improve the dr...

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Bibliographic Details
Published in:Advances in mechanical engineering 2019-03, Vol.11 (3)
Main Authors: Zhu, Tianjun, Zheng, Hongyan, Ma, Zonghao
Format: Article
Language:English
Subjects:
Algorithms
Automobile industry
Computer simulation
Design optimization
Design parameters
Electric power systems
Electric vehicles
Electrification
Optimization algorithms
Particle swarm optimization
Powertrain
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Summary:Transportation of electrification has become a hot issue in recent decades and the large-scale deployment of electric vehicles has yet to be actualized. This article proposes a powertrain parameter optimization design approach based on chaotic particle swarm optimization algorithm. To improve the driving and economy performance of pure electric vehicles, chaotic particle swarm optimization algorithm is adopted in this study to optimize principal parameters of vehicle power system. Vehicle dynamic performance simulations were carried out in the Cruise software, and the simulation results before and after optimization were compared. Simulation results show that optimized vehicles by chaotic particle swarm optimization can meet the expected dynamic performance and the driving range has been greatly improved. Meanwhile, it is also viable that the parameters of the optimal objective function can achieve the purpose of balancing the driving performance and economic performance, which provides a reference for the development of vehicle dynamic performance.
ISSN:1687-8132
1687-8140
DOI:10.1177/1687814019833500