| Issue |
E3S Web Conf.
Volume 692, 2026
3rd International Conference on Intelligent and Sustainable Power and Energy Systems (ISPES 2025)
|
|
|---|---|---|
| Article Number | 01011 | |
| Number of page(s) | 16 | |
| Section | Energy | |
| DOI | https://doi.org/10.1051/e3sconf/202669201011 | |
| Published online | 04 February 2026 | |
Frequency Decoupling-Based Energy Management System for Fuel Cell Hybrid Electric Vehicles Using State Machine Control Strategy
1 Electrical & Electronics Engineering, Seshadripuram Institute of Technology, Mysuru, India, 571311
2 Electrical & Electronics Engineering, Seshadripuram Institute of Technology, Mysuru, India, 571311
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Fuel cell hybrid electric vehicles (FCHEVs) encounter significant challenges in energy management due to the distinct dynamic characteristics of fuel cell systems, batteries, and supercapacitors. Standard methods of managing energy use can lead to excessive hydrogen production, shorten the lifespan of fuel cells, and fail to maintain battery charge effectively when driving conditions change. This paper presents a novel frequency decoupling-based energy management strategy (FDB-EMS) integrated with state machine control to address these limitations. The suggested method uses two low-pass filters to divide power demand into three frequency bands. The battery receives the medium-frequency parts, the fuel cell receives the low-frequency parts, and the supercapacitor receives the high-frequency transients. The state machine controller adjusts power distribution in real-time based on load and SOC limits. Simulations in MATLAB/Simulink demonstrate that the system operates effectively with both constant and variable load profiles. The system uses a 12.875 kW proton exchange membrane fuel cell, a 40 Ah lithium-ion battery, and a 15.6 F supercapacitor. The results show that FDB-EMS consumes 0.060 g/s of fuel, which is 7.7% more efficient than reinforcement learning methods and 16.7% more efficient than rule-based strategies. The system maintains the battery SOC between 62% and 78%, which means that the changes are only 1.8% instead of 4.5% as in fuzzy logic controllers. The transient response time is 140 milliseconds, resulting in power losses of 3.6%. The frequency decomposition does a good job of breaking up changes in the fuel cell that happen at high frequencies. This reduces stress and extends the device’s lifespan. The proposed FDB-EMS is a simple and efficient way to control energy in real-time, which makes the system more reliable and saves fuel.
Key words: Fuel cell hybrid electric vehicle / energy management strategy / frequency decoupling / state machine control / supercapacitor / hydrogen co_
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

