Optimizing Low Pass Filter Cut-off Frequency for Energy Management in Electric Vehicles with Hybrid Energy Storage Systems

Mitigating pollution in the transportation sector necessitates the deployment of zero-emission solutions, such as electric vehicles (EVs). One significant challenge with EVs is the limited lifespan of the battery, a key and costly component. To circumvent this issue, a potential solution lies in the integration of batteries with supercapacitors to create a Hybrid Energy Storage System (HESS). This combination can notably decrease the peak current of the battery, thereby prolonging its lifespan, and ultimately, contributing to the long-term cost-effectiveness of EVs. A critical component of the HESS is the Energy Management Strategy (EMS), tasked with optimizing energy distribution. A Low-Pass Filter (LPF) serves as an uncomplicated, real-time EMS. The current study introduces a novel approach for determining the optimal cut-off frequency of the LPF, termed the Ragone Plot with Fine Tuning (RPFT). The Ragone plot provides a general cut-off frequency for the battery and drive cycle, while fine-tuning is employed to optimize it. Simulation results reveal that the RPFT method outperforms the Fast Fourier Transform (FFT) method, thereby proving its efficacy. The application of RPFT resulted in a reduction of battery peak current and battery current root mean square (BCRMS) by up to 29.80% and 9.99%, respectively. This study offers valuable insights for improving energy management in electric vehicles and underscores the potential of the RPFT method in extending battery lifespan and enhancing the cost-effectiveness of EVs.