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The rapid transition toward electric mobility has significantly increased the demand for efficient and durable energy storage systems. Conventional battery-based systems are often subjected to high stress due to dynamic load conditions, resulting in reduced lifespan and performance degradation. This paper presents the design and implementation of a Hybrid Energy Storage System (HESS) integrating a lithium-ion battery and an ultracapacitor, controlled using Direct Model Predictive Control (DMPC). The proposed system utilizes an ESP32 microcontroller for real-time monitoring and control. By predicting system behavior and optimizing switching states of bidirectional DC–DC converters, the system effectively reduces DC bus voltage fluctuations and battery stress. Experimental validation confirms improved system stability, efficiency, and reliability, making it suitable for low-cost electric vehicle applications and smart energy storage solutions.
Keywords:
Direct Model Predictive Control (DMPC), Hybrid Energy Storage System (HESS), Electric Vehicle (EV),Energy Management, Power Optimization, Voltage Stability
Cite Article:
"Direct Model Predictive Control of a Hybrid Energy Storage System for Electric Vehicle", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.c81-c84, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604284.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator