2023
DOI: 10.3390/su15108219
|View full text |Cite
|
Sign up to set email alerts
|

Study on Multi-Objective Optimization of Power System Parameters of Battery Electric Vehicles

Abstract: The optimization of power parameters is the key to the design of pure electric vehicles. Reasonable matching of the relationship between various parameters can effectively reduce energy consumption and achieve energy sustainability. In this paper, several vehicle performance indexes such as maximum vehicle speed, acceleration time and power consumption per 100 km were used as optimization target vectors, and transmission ratio was used as optimization variable to establish the optimization problem of parameter… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
4
0

Year Published

2023
2023
2025
2025

Publication Types

Select...
6

Relationship

2
4

Authors

Journals

citations
Cited by 6 publications
(4 citation statements)
references
References 56 publications
0
4
0
Order By: Relevance
“…Researchers have invented many advanced optimization techniques to address these complications and optimize the control of MGs. Such as Enhanced Transient Search Optimization [22], the Coot bird metaheuristic optimizer (COOT) [19], the Enhanced Bald Eagle Search Algorithm [23], genetic algorithms [24], modified virtual rotor-based derivative technique supported with Jaya optimizer based on balloon effect [25], the Adaptive-Width Generalized Correntropy Diffusion Algorithm (AWGC-DA) [26], the Sunflower (SFO) algorithm [27], Enhanced Block-Sparse Adaptive Bayesian algorithm (EBS-ABA) [28], the Cuttlefish optimization algorithm [29], the ant colony algorithm [30], Circle Search Algorithm [31], the particle swarm optimization (PSO) [32], [33], and The least mean (LM) and the square root of exponential (SRE) [34]. These optimization methods aim to enhance decentralized controllers in MG systems, fine-tune parameters, and improve performance.…”
Section: B Research Gap and Motivationmentioning
confidence: 99%
“…Researchers have invented many advanced optimization techniques to address these complications and optimize the control of MGs. Such as Enhanced Transient Search Optimization [22], the Coot bird metaheuristic optimizer (COOT) [19], the Enhanced Bald Eagle Search Algorithm [23], genetic algorithms [24], modified virtual rotor-based derivative technique supported with Jaya optimizer based on balloon effect [25], the Adaptive-Width Generalized Correntropy Diffusion Algorithm (AWGC-DA) [26], the Sunflower (SFO) algorithm [27], Enhanced Block-Sparse Adaptive Bayesian algorithm (EBS-ABA) [28], the Cuttlefish optimization algorithm [29], the ant colony algorithm [30], Circle Search Algorithm [31], the particle swarm optimization (PSO) [32], [33], and The least mean (LM) and the square root of exponential (SRE) [34]. These optimization methods aim to enhance decentralized controllers in MG systems, fine-tune parameters, and improve performance.…”
Section: B Research Gap and Motivationmentioning
confidence: 99%
“…With the increasing global environmental pollution and the depletion of fossil fuels [1], the transport sector in various countries is seeking a sustainable development path [2][3][4]. Electric vehicles (EVs) with zero emissions and high-efficiency conversions hold great promise [5][6][7]. With the increasing penetration rate of EVs [8], the charging problems faced have also been intensely studied [9,10].…”
Section: Introductionmentioning
confidence: 99%
“…Through the SDN methodology, the merits like suppleness without affecting the advanced presentation [7], increased effectiveness among optimization steering, easy implementation, management, and preferred cost range [8]. The energy consumption rates of energy consuming were playing an important role in the whole evidence and the interaction method rate [9]. So many other methods were developed for improving the energy efficiency in the systems, International Journal of Intelligent Engineering and Systems, Vol.…”
Section: Introductionmentioning
confidence: 99%