Artificial Intelligence-Based Electric Vehicle Smart Charging System in Malaysia

被引:6
|
作者
Shern, Siow Jat [1 ]
Sarker, Md Tanjil [1 ]
Ramasamy, Gobbi [1 ]
Thiagarajah, Siva Priya [2 ]
Al Farid, Fahmid [3 ]
Suganthi, S. T. [4 ]
机构
[1] Multimedia Univ, Fac Engn, Ctr Elect Energy & Automat, Cyberjaya 63100, Malaysia
[2] Multimedia Univ, Fac Engn, Ctr Wireless Technol, Cyberjaya 63100, Malaysia
[3] Multimedia Univ, Fac Engn, Ctr Digital Home, Cyberjaya 63100, Malaysia
[4] Kumaraguru Coll Technol, Dept Elect & Elect Engn, Coimbatore 641001, India
来源
WORLD ELECTRIC VEHICLE JOURNAL | 2024年 / 15卷 / 10期
关键词
artificial intelligence (AI); electrical vehicle charging system (EVCS); smart charging systems; battery management systems (BMS); demand response; optimization methods; renewable energy integration; BATTERY; MANAGEMENT; ALGORITHM; ENERGY; STATE;
D O I
10.3390/wevj15100440
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The worldwide transition to electric vehicles (EVs) is gaining momentum, propelled by the imperative to reduce carbon emissions and foster sustainable transportation. In Malaysia, the government is facilitating this transformation through targeted initiatives aimed at promoting the use of electric vehicles (EVs) and developing the required infrastructure. This paper investigates the crucial role of artificial intelligence (AI) in developing intelligent electric vehicle (EV) charging infrastructure, specifically focusing on the context of Malaysia. The paper examines the current electric vehicle (EV) charging infrastructure in Malaysia, highlights advancements led by artificial intelligence (AI), and references both local and international case studies. Fluctuations in the Total Industry Volume (TIV) and Total Industry Production (TIP) reflect changes in market demand and production capabilities, with notable peaks in March 2023 and March 2024. The research reveals that AI technologies, such as machine learning and predictive analytics, can enhance charging efficiency, improve user experience, and support grid stability. A mathematical model for an AI-based smart charging system was developed, and the implemented system achieved 30% energy savings and a 20.38% reduction in costs compared to traditional methods. These findings underscore the system's energy and cost efficiency. In addition, we outline the potential advantages and challenges associated with incorporating artificial intelligence (AI) into Malaysia's electric vehicle (EV) charging infrastructure. Furthermore, we offer recommendations for researchers, industry stakeholders, and regulators. Malaysia can enhance the uptake of electric vehicles and make a positive impact on the environment by leveraging artificial intelligence (AI) to enhance its electric vehicle charging system (EVCS).
引用
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页数:30
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