MPC and Filtering-Based Energy Management in Fuel Cell/ Battery/ Supercapacitor Hybrid Source

Syahbana, Dwiky Fajri; Trilaksono, Bambang Riyanto

doi:10.1109/iceei47359.2019.8988849

Cited by 6 publications

(3 citation statements)

References 20 publications

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“…From this plot, the cut-off frequency (fc) is calculated using Eq. ( 17) [24][25][26][27]. This method was used by the study [24] to determine the cutoff frequency of LPF EMS before then they add an adaptation algorithm to improve the performance.…”

Section: Ragone Plotmentioning

confidence: 99%

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

Maghfiroh,

Wahyunggoro,

Cahyadi

2023

MMEP

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Mitigating pollution in the transportation sector necessitates the deployment of zeroemission 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 costeffectiveness of EVs.

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Section: Ragone Plotmentioning

confidence: 99%

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

Maghfiroh,

Wahyunggoro,

Cahyadi

2023

MMEP

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“…Highly sensitive to driving profiles Online applications 53,[89][90][91][92][93] MPC High accuracy online applications, Improved adaptivity and predictivity Accurate prediction of the driving cycle and highly sensitive to it, The necessity of high accuracy model Online application 52,[94][95][96][97][98][99][100] Learning-based RL Real-time and efficient online control, system modeling is not required EMS. 43 This gives the basic idea of the strategies of complete rule-based EMS.…”

Section: Ecms Online and Real-time Implementationsmentioning

confidence: 99%

A review on hybrid source energy management strategies for electric vehicle

Kashyap

Castelino

2021

Int J Energy Res

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Electric and hybrid electric vehicle technology demonstrates a performance to replace the internal combustion engines (ICE) in the current scenario. It attracts attention with improved fuel or energy efficiency with lower emissions. The overall system performance depends on powertrains, types of energy sources, electro-electronic interfaces, and energy management strategies (EMS). Significant issues of battery-powered electric vehicles (EV) are effects on the range, battery life, EV performance, battery maintenance, and replacement cost. Hybrid power source system (HPSS) solves EV challenges to a large extent. A hybrid combination of battery and supercapacitor (SC) to power the EV enhances the overall performance and life of the vehicle. Learning and integrated-based EMSs are gaining attention, with their ability in accurate and fast response in power handling among various sources. This paper analyses various DC-DC converter topologies of HPSS and compares multiple EMS with recent developments. In the context of challenges involved in EVs and research gaps that are discussed in the paper, EMSs need to be enhanced. The EMSs must consider the inputs for varying driving behaviors, road traffic, load, and environmental conditions to assure the flexibility of EV among different users across the globe. This is achieved by the management of SC power available to support the vehicle during sudden power requirements and enabling it to recuperate braking energy to improve the energy efficiency throughout the trip. Lastly, recommending precise research directions to achieve the development and improvement of the EMS and power electronic interfaces. K E Y W O R D Sbattery, electric vehicle (EV), energy management strategies (EMSs), hybrid power source systems (HPSS), supercapacitor (SC)

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“…Studies conducted by Syahbana and Trilaksono (32) and Snoussi et al (33) have demonstrated the validity of the Ragone plot. Three power sources-a fuel cell (FC), a battery (B), a supercapacitor (SC), and two low-pass filters (LPF)-are used (32). FC requires some of the power from the first LPF, while the remainder is transmitted to the second LPF, which outputs power for the battery.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Low-Pass Filter Energy Management with Adaptive State of Charge Limiter for Hybrid Energy Storage in Electric Vehicles

Maghfiroh,

Wahyunggoro,

Imam Cahyadi

2024

IJE

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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.

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MPC and Filtering-Based Energy Management in Fuel Cell/ Battery/ Supercapacitor Hybrid Source

Cited by 6 publications

References 20 publications

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

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

A review on hybrid source energy management strategies for electric vehicle

Enhancing Low-Pass Filter Energy Management with Adaptive State of Charge Limiter for Hybrid Energy Storage in Electric Vehicles

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