Choosing the right charger for electric vehicles

Choosing the right charger for electric vehicles (EVs) is essential for optimized vehicle performance. One of the key components in this process is a non-isolated DC-DC converter. This converter serves to convert the input power into the output needed to efficiently charge the EV battery.

Non-isolated DC-DC converter

In EV charging, there are different types of non-isolated DC-DC converters. This paper discusses the important role of such converters in charging systems. These converters are designed to ensure the charging process runs smoothly and efficiently, reducing the time taken to charge the battery.

Machine learning-based control innovation

One of the advancements discussed was the integration of machine learning-based pulse width modulation (PWM) control into the DC-DC buck converter. Using machine learning algorithms, the charging system can adjust to different input and output conditions in real time. This makes the charging process more effective and improves the overall performance of the electric vehicle.

Energy optimization

This machine learning-based approach enables dynamic charging parameter optimization, thus ensuring more efficient energy use. As such, this innovation not only improves charging efficiency but also contributes to the longevity and reliability of EV batteries.

Energy management in hybrid systems

In addition, this research also explores energy management for hybrid energy storage systems that combine lithium-ion batteries and supercapacitors. The aim is to ensure a stable and high-quality electricity supply for electric vehicles. This management strategy uses a controller that applies metaheuristic techniques to optimize the control parameters. In this system, supercapacitor units manage the direct current (DC) bus, while lithium-ion batteries help balance the power distribution. This research highlights the benefits of the salp swarm algorithm technique that can improve control system performance.

Conclusion

By combining metaheuristic optimization methods and integral mode sliding control, power quality can be significantly improved. The proposed management algorithm optimizes resource allocation and protects them, ensuring a stable and high-quality power supply for EVs. Overall, this innovative approach promises to improve the efficiency and reliability of hybrid energy storage systems in electric vehicles, providing a robust solution to meet the growing demands of modern energy management.

By: I. Busthomi