A thorough review of energy management and an advanced control techniques for Bi-directional DC-DC converters in electric vehicle applications
Bi-directional DC-DC converters are essential components in electric vehicles (EVs), facilitating efficient power transfer between the battery and the motor for key operations such as voltage regulation, energy recovery during braking (regenerative braking), and battery charging. This review analyse...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025027938 |
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| Summary: | Bi-directional DC-DC converters are essential components in electric vehicles (EVs), facilitating efficient power transfer between the battery and the motor for key operations such as voltage regulation, energy recovery during braking (regenerative braking), and battery charging. This review analyses prominent control strategies employed for these converters, including Sliding Mode Control (SMC), Model Predictive Control (MPC), and Predictive Function Control (PFC), considering their respective merits and drawbacks under diverse operating conditions. The study highlights the significance of adaptable and high-performing control systems for managing the dynamic behaviour of EV powertrains. It also investigates how bidirectional converters optimize regenerative braking to extend driving range and enable vehicle-to-grid (V2G) capabilities, which contribute to grid stability. Furthermore, the review proposes a new hybrid control architecture that combines traditional control methods with machine learning to enhance system adaptability and overall effectiveness. Ultimately, this review summarizes recent advancements, emerging trends, and potential future research areas in bidirectional DC-DC converter control for EVs, aiming to contribute to the development of more efficient, dependable, and environmentally friendly electric mobility solutions. |
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| ISSN: | 2590-1230 |