| Abstrak/Abstract |
Electric vehicles (EVs) have become a vital solution for environmental transportation; however,
challenges related to battery life and power density persist. In pursuit of enhanced EV performance and
cost-effectiveness, researchers advocate for Hybrid Energy Storage Systems (HESS), integrating various
Energy Storage Systems (ESS). An efficient Energy Management Strategy (EMS) is crucial for optimal
power distribution within the HESS. This study introduces a real-time, simple, and practical EMS using
a low-pass filter (LPF). However, the LPF lacks State of Charge (SoC) control, necessitating the addition
of a SoC Limiter. The static SoC Limiter, while effective, faces challenges in predicting peak loads,
leading to suboptimal power-sharing performance. To address this limitation, LPF with Adaptive SoC
Limiter (LPF-ASL) is proposed. The LPF-ASL accommodates the peak load by saving some portion of
supercapacitor (SC) power for peak load. In an unpredictable initial SC SoC test, LPF-ASL achieves
substantial reductions in maximum battery current compared to LPF and Fuzzy Logic Control (FLC) by
up to 21.30% and 21.14%, respectively. This underscores the effectiveness of LPF-ASL in optimizing
battery life and enhancing power distribution within HESS-equipped EVs |
