Optimization Strategy of the Electric Vehicle Power Battery Based on the Convex Optimization Algorithm

With the development of the electric vehicle industry, electric vehicles have provided more choices for people. However, the performance of electric vehicles needs improvement, which makes most consumers take a wait-and-see attitude. Therefore, finding a method that can effectively improve the perfo...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Processes Ročník 11; číslo 5; s. 1416
Hlavní autori: Wang, Xuanxuan, Ji, Wujun, Gao, Yun
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 06.05.2023
Predmet:
Algorithms
Automobiles
Automobiles, Electric
Computational geometry
Consumption
Convex analysis
Convexity
Deep learning
Efficiency
Electric vehicles
Energy consumption
Energy management
Fuel cells
Hybrid vehicles
Mathematical optimization
Methods
Optimization
Optimization algorithms
Performance enhancement
Simulation
Transportation equipment industry
China
ISSN:2227-9717, 2227-9717
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:With the development of the electric vehicle industry, electric vehicles have provided more choices for people. However, the performance of electric vehicles needs improvement, which makes most consumers take a wait-and-see attitude. Therefore, finding a method that can effectively improve the performance of electric vehicles is of great significance. To improve the current performance of electric vehicles, a convex optimization algorithm is proposed to optimize the motor model and power battery parameters of electric vehicles, improving the overall performance of electric vehicles. The performance of the proposed convex optimization algorithm, dual loop DP optimization algorithm, and nonlinear optimization algorithm is compared. The results show that the hydrogen consumption of electric vehicles optimized by the convex optimization algorithm is 95.364 g. This consumption is lower than 98.165 g of the DCDP optimization algorithm and 105.236 g of the nonlinear optimization algorithm before optimization. It is also significantly better than the 125.59 g of electric vehicles before optimization. The calculation time of the convex optimization algorithm optimization is 4.9 s, which is lower than the DCDP optimization algorithm and nonlinear optimization algorithm. The above results indicate that convex optimization algorithms have better optimization performance. After optimizing the power battery using a convex optimization algorithm, the overall performance of electric vehicles is higher. Therefore, this method can effectively improve the performance of current electric vehicle power batteries, make new energy vehicles develop rapidly, and improve the increasingly serious environmental pollution and energy crisis in China.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2227-9717
2227-9717
DOI:10.3390/pr11051416