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.
Mallaiah et al. (Wed,) studied this question.
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