Sizing of a Plug-In Hybrid Electric Vehicle with the Hybrid Energy Storage System

Tu, Jing; Bai, Zhongxiang; Wu, Xiaolan

doi:10.3390/wevj13070110

Cited by 5 publications

(5 citation statements)

References 30 publications

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“…In related work, the particle swarm optimization (PSO) algorithm was used to determine the size of a PHEV with a BU and UC [7]. The goal of this study was the minimization of the drive train cost, including the investment cost and BU replacement cost.…”

Section: A Ice-hevmentioning

confidence: 99%

“…Hence, most rule-based EMSs rely on the SoC of the BU. The CD-CS modes of power management operation have been widely used [7], [83], [84], [91], [101], [108]. In the CD mode, power is drawn from the BU, so the SoC of the BU continuously decreases.…”

Section: Rule-based Approachmentioning

confidence: 99%

“…Therefore, a thorough examination of the dynamic models of various sources employed in EV is crucial. Various research has considered distinctive features and formulated the associated objective function for multiple source size optimization in HEV [7], [8].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Sizing and Dynamic Energy Source Characteristics of Hybrid Electric Vehicles: A Comprehensive Review and Future Directions

Prasanthi,

Shareef,

Errouissi

et al. 2024

IEEE Access

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The automobile industry is regarded as one of the primary producers of greenhouse gas emissions. Hence, one major approach for promoting global sustainability is vehicle electrification. Energy source hybridization is imperative in vehicle electrification because no alternative clean energy source can match the performance of vehicles with internal combustion engines. For a compact energy source system with minimal source degradation and low operational costs, it is crucial to determine the optimal sizing of multiple sources in a hybrid electric vehicle (HEV). The objective of this article is to conduct a thorough assessment of the optimal energy source sizing methodology for HEV alongside an analysis of energy management systems. The importance of dynamic energy source characteristics in the optimal source design is explained and the dynamic modelling of these sources is investigated in detail. Moreover, this paper discusses the dynamic source degradation models used in the literature. This analysis on HEV component sizing provides a comprehensive picture of the current state-of-the-art and highlights several shortcomings, difficulties, and knowledge gaps. The findings indicate that the establishment of an energy management system and energy source sizing are interdependent activities that can prolong the usable life of the energy sources and reduce energy consumption. The aging, temperature, depth of discharge, and charging state are found to be essential characteristics of vehicle energy sources, yet these dynamic aspects have largely been neglected in previous papers. Additionally, if the source deterioration and associated factors are considered throughout the design phase, the HEV system can be built with long-life characteristics. The assessment conclusions highlight the significance of continued analysis to overcome obstacles and improve the hybrid automobile sector.

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Section: A Ice-hevmentioning

confidence: 99%

Section: Rule-based Approachmentioning

confidence: 99%

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Optimal Sizing and Dynamic Energy Source Characteristics of Hybrid Electric Vehicles: A Comprehensive Review and Future Directions

Prasanthi,

Shareef,

Errouissi

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The PSO algorithm follows some steps to solve an optimization problem. Firstly, the algorithm allocates initial random velocities and positions to all particles in space, the best particle of the particular (pbest), and the best particle of the swarm (gbest) to upgrade the position of each particle in turn [50]. The procedure is written as the following equations:…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Optimal Design of Energy Sources for a Photovoltaic/Fuel Cell Extended-Range Agricultural Mobile Robot

et al. 2023

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Powertrain electrification in the agricultural vehicles is still in the initial stages. This article analyzes the energy behavior of a Photovoltaic/Fuel Cell Agricultural Mobile Robot (PV/FCAMR) as the preliminary step before development. This concept incorporates three energy storage sources for the powertrain: a battery pack, a Fuel Cell (FC) system, and a Photovoltaic (PV) system. This paper proposes an approach based on the Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms to determine the sizes of the FC and battery of an FCAMR. A differential drive mobile robot was used as a case study to extract the typical working cycles of farming applications. The FCAMR vehicle model was developed in MATLAB/Simulink to evaluate vehicle energy consumption and performance. For the energy analysis and evaluation, the FCAMR was tested based on two realistic working cycles comprising circular and rectangular moving patterns. The results showed that the proposed arrangement could extend the FCAMR autonomy by 350% as opposed to the pure electric system. This allows for at least 8 h of work with a tank filled with 150 g hydrogen and a PV system with a 0.5 m2 monocrystalline solar panel. The simulation results have demonstrated the relevance and robustness of this approach in relation to various working cycles. The cost comparison between the theoretical and optimization sizing methods showed at least an 8% decrease for the FCAMR. Furthermore, adding the PV system extended the vehicle’s range by up to 5%. This study provides an optimal solution for energy sources sizing of mobile robots as futuristic agricultural vehicles.

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“…The sizing of the sources must be compatible with the HEV power and energy requirements [10]; otherwise, there is a risk of over/under-sizing the sources. Hence, an optimal procedure that minimizes these power sources' size and costs is necessary [13,14]. Usually, in the literature, these methodologies aim for a cost-effective system of hybrid power sources [2,10,15].…”

Section: Introductionmentioning

confidence: 99%

Sizing of Autonomy Source Battery–Supercapacitor Vehicle with Power Required Analyses

Lopes,

Pomilio,

Ferreira

2024

WEVJ

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The combined use of batteries and supercapacitors is an alternative to reconcile the higher energy density of batteries with the high power density of supercapacitors. The optimal sizing of this assembly, especially with the minimization of mass, is one of the challenges of designing the power system of an electric vehicle. The condition of the unpredictability of the power demand determined by the vehicle driver must also be added, which must be met by the power system without exceeding safe operating limits for the devices. This article presents a methodology for minimizing the mass of the electrical energy storage system (ESS) that considers the various aspects mentioned and a variety of battery technologies and supercapacitor values. The resulting minimum mass dimensioning is verified by simulation for different driving cycles under conditions of maximum power demand. The system also includes a tertiary source, such as a fuel cell, responsible for the vehicle’s extended autonomy. In addition to sizing the ESS, the article also proposes a management strategy for the various sources to guarantee the vehicle’s expected performance while respecting each device’s operational limits.

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Sizing of a Plug-In Hybrid Electric Vehicle with the Hybrid Energy Storage System

Cited by 5 publications

References 30 publications

Optimal Sizing and Dynamic Energy Source Characteristics of Hybrid Electric Vehicles: A Comprehensive Review and Future Directions

Optimal Sizing and Dynamic Energy Source Characteristics of Hybrid Electric Vehicles: A Comprehensive Review and Future Directions

Optimal Design of Energy Sources for a Photovoltaic/Fuel Cell Extended-Range Agricultural Mobile Robot

Sizing of Autonomy Source Battery–Supercapacitor Vehicle with Power Required Analyses

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