Adaptive Low‐Pass Filter Energy Management is a B.Tech project topic for Electrical Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Adaptive Low‐Pass Filter Energy Management Project Details
| Abstract |
Heavy‑duty machines such as hybrid electric mining haul trucks need energy‑storage systems that provide both high energy and high power density. This study tackles that need by evaluating a lithium‑battery‑supercapacitor hybrid energy storage system (HESS) that is controlled with an adaptive low‑pass filter (LPF) and fuzzy‑logic logic. The core method uses online Fast Fourier Transform (FFT) analysis to change the LPF’s cutoff frequency on the fly. This dynamic adjustment optimizes how power is split between the battery and the supercapacitor in real time. To keep the DC‑bus voltage steady during sudden load changes, a fuzzy‑logic voltage‑compensation block is added. The approach is validated with Model‑in‑the‑Loop (MIL) simulation and Hardware‑in‑the‑Loop (HIL)
testing. In high‑power pulse tests, the adaptive strategy boosted the supercapacitor’s pulse‑power contribution by 27.2 % compared with a fixed‑parameter method, and it markedly improved the output‑voltage stability of the combined power source. For B.Tech students, this framework offers a practical basis for building active power‑sharing topologies and real‑time filter‑tuning algorithms in MATLAB/Simulink.
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| Reference Paper |
Adaptive Low‐Pass Filter Energy Management With Fuzzy Logic Control for Hybrid Energy Storage System |
| Domain |
Electrical Engineering |
| Sub-Domain |
Energy Management Systems |
| PDF Download |
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